>> Narrator: TheCUBE's live coverage is made possible by funding from Dell Technologies. Creating technologies that drive human progress. (light airy music) >> Hi, everybody, welcome back to the Fira in Barcelona. My name is Dave Vellante. I'm here with my co-host Dave Nicholson. Lisa Martin is in the house. John Furrier is pounding the news from our Palo Alto studio. We are super excited to be talking about cloud at the edge, what that means. Charles Tsai is here. He's the Senior Director of product management at Dell Technologies and Peter Fetterolf is the Chief Technology Officer at ACG Business Analytics, a firm that goes deep into the TCO and the telco space, among other things. Gents, welcome to theCUBE. Thanks for coming on. Thank you. >> Good to be here. >> Yeah, good to be here. >> So I've been in search all week of the elusive next wave of monetization for the telcos. We know they make great money on connectivity, they're really good at that. But they're all talking about how they can't let this happen again. Meaning we can't let the over the top vendors yet again, basically steal our cookies. So we're going to not mess it up this time. We're going to win in the monetization. Charles, where are those monetization opportunities? Obviously at the edge, the telco cloud at the edge. What is that all about and where's the money? >> Well, Dave, I think from a Dell's perspective, what we want to be able to enable operators is a solution that enable them to roll out services much quicker, right? We know there's a lot of innovation around IoT, MEG and so on and so forth, but they continue to rely on traditional technology and way of operations is going to take them years to enable new services. So what Dell is doing is now, creating the entire vertical stack from the hardware through CAST and automation that enable them, not only to push out services very quickly, but operating them using cloud principles. >> So it's when you say the entire vertical stack, it's the integrated hardware components with like, for example, Red Hat on top- >> Right. >> Or a Wind River? >> That's correct. >> Okay, and then open API, so the developers can create workloads, I presume data companies. We just had a data conversation 'cause that was part of the original stack- >> That's correct. >> So through an open ecosystem, you can actually sort of recreate that value, correct? >> That's correct. >> Okay. >> So one thing Dell is doing, is we are offering an infrastructure block where we are taking over the overhead of certifying every release coming from the Red Hat or the Wind River of the world, right? We want telcos to spend their resources on what is going to generate them revenue. Not the overhead of creating this cloud stack. >> Dave, I remember when we went through this in the enterprise and you had companies like, you know, IBM with the AS400 and the mainframe saying it's easier to manage, which it was, but it's still, you know, it was subsumed by the open systems trend. >> Yeah, yeah. And I think that's an important thing to probe on, is this idea of what is, what exactly does it mean to be cloud at the edge in the telecom space? Because it's a much used term. >> Yeah. >> When we talk about cloud and edge, in sort of generalized IT, but what specifically does it mean? >> Yeah, so when we talk about telco cloud, first of all it's kind of different from what you're thinking about public cloud today. And there's a couple differences. One, if you look at the big hyperscaler public cloud today, they tend to be centralized in huge data centers. Okay, telco cloud, there are big data centers, but then there's also regional data centers. There are edge data centers, which are your typical like access central offices that have turned data centers, and then now even cell sites are becoming mini data centers. So it's distributed. I mean like you could have like, even in a country like say Germany, you'd have 30,000 soul sites, each one of them being a data center. So it's a very different model. Now the other thing I want to go back to the question of monetization, okay? So how do you do monetization? The only way to do that, is to be able to offer new services, like Charles said. How do you offer new services? You have to have an open ecosystem that's going to be very, very flexible. And if we look at where telcos are coming from today, they tend to be very inflexible 'cause they're all kind of single vendor solutions. And even as we've moved to virtualization, you know, if you look at packet core for instance, a lot of them are these vertical stacks of say a Nokia or Ericson or Huawei where you know, you can't really put any other vendors or any other solutions into that. So basically the idea is this kind of horizontal architecture, right? Where now across, not just my central data centers, but across my edge data centers, which would be traditionally my access COs, as well as my cell sites. I have an open environment. And we're kind of starting with, you know, packet core obviously with, and UPFs being distributed, but now open ran or virtual ran, where I can have CUs and DUs and I can split CUs, they could be at the soul site, they could be in edge data centers. But then moving forward, we're going to have like MEG, which are, you know, which are new kinds of services, you know, could be, you know, remote cars it could be gaming, it could be the Metaverse. And these are going to be a multi-vendor environment. So one of the things you need to do is you need to have you know, this cloud layer, and that's what Charles was talking about with the infrastructure blocks is helping the service providers do that, but they still own their infrastructure. >> Yeah, so it's still not clear to me how the service providers win that game but we can maybe come back to that because I want to dig into TCO a little bit. >> Sure. >> Because I have a lot of friends at Dell. I don't have a lot of friends at HPE. I've always been critical when they take an X86 server put a name on it that implies edge and they throw it over the fence to the edge, that's not going to work, okay? We're now seeing, you know we were just at the Dell booth yesterday, you did the booth crawl, which was awesome. Purpose-built servers for this environment. >> Charles: That's right. >> So there's two factors here that I want to explore in TCO. One is, how those next gen servers compare to the previous gen, especially in terms of power consumption but other factors and then how these sort of open ran, open ecosystem stacks compared to proprietary stacks. Peter, can you help us understand those? >> Yeah, sure. And Charles can comment on this as well. But I mean there, there's a couple areas. One is just moving the next generation. So especially on the Intel side, moving from Ice Lake to the Sapphire Rapids is a big deal, especially when it comes to the DU. And you know, with the radios, right? There's the radio unit, the RU, and then there's the DU the distributed unit, and the CU. The DU is really like part of the radio, but it's virtualized. When we moved from Ice lake to Sapphire Rapids, which is third generation intel to fourth generation intel, we're literally almost doubling the performance in the DU. And that's really important 'cause it means like almost half the number of servers and we're talking like 30, 40, 50,000 servers in some cases. So, you know, being able to divide that by two, that's really big, right? In terms of not only the the cost but all the TCO and the OpEx. Now another area that's really important, when I was talking moving from these vertical silos to the horizontal, the issue with the vertical silos is, you can't place any other workloads into those silos. So it's kind of inefficient, right? Whereas when we have the horizontal architecture, now you can place workloads wherever you want, which basically also means less servers but also more flexibility, more service agility. And then, you know, I think Charles can comment more, specifically on the XR8000, some things Dell's doing, 'cause it's really exciting relative to- >> Sure. >> What's happening in there. >> So, you know, when we start looking at putting compute at the edge, right? We recognize the first thing we have to do is understand the environment we are going into. So we spend with a lot of time with telcos going to the south side, going to the edge data center, looking at operation, how do the engineer today deal with maintenance replacement at those locations? Then based on understanding the operation constraints at those sites, we create innovation and take a traditional server, remodel it to make sure that we minimize the disruption to the operations, right? Just because we are helping them going from appliances to open compute, we do not want to disrupt what is have been a very efficient operation on the remote sites. So we created a lot of new ideas and develop them on general compute, where we believe we can save a lot of headache and disruptions and still provide the same level of availability, resiliency, and redundancy on an open compute platform. >> So when we talk about open, we don't mean generic? Fair? See what I mean? >> Open is more from the software workload perspective, right? A Dell server can run any type of workload that customer intend. >> But it's engineered for this? >> Environment. >> Environment. >> That's correct. >> And so what are some of the environmental issues that are dealt with in the telecom space that are different than the average data center? >> The most basic one, is in most of the traditional cell tower, they are deployed within cabinets instead of racks. So they are depth constraints that you just have no access to the rear of the chassis. So that means on a server, is everything you need to access, need to be in the front, nothing should be in the back. Then you need to consider how labor union come into play, right? There's a lot of constraint on who can go to a cell tower and touch power, who can go there and touch compute, right? So we minimize all that disruption through a modular design and make it very efficient. >> So when we took a look at XR8000, literally right here, sitting on the desk. >> Uh-huh. >> Took it apart, don't panic, just pulled out some sleds and things. >> Right, right. >> One of the interesting demonstrations was how it compared to the size of a shoe. Now apparently you hired someone at Dell specifically because they wear a size 14 shoe, (Charles laughs) so it was even more dramatic. >> That's right. >> But when you see it, and I would suggest that viewers go back and take a look at that segment, specifically on the hardware. You can see exactly what you just referenced. This idea that everything is accessible from the front. Yeah. >> So I want to dig in a couple things. So I want to push back a little bit on what you were saying about the horizontal 'cause there's the benefit, if you've got the horizontal infrastructure, you can run a lot more workloads. But I compare it to the enterprise 'cause I, that was the argument, I've made that argument with converged infrastructure versus say an Oracle vertical stack, but it turned out that actually Oracle ran Oracle better, okay? Is there an analog in telco or is this new open architecture going to be able to not only service the wide range of emerging apps but also be as resilient as the proprietary infrastructure? >> Yeah and you know, before I answer that, I also want to say that we've been writing a number of white papers. So we have actually three white papers we've just done with Dell looking at infrastructure blocks and looking at vertical versus horizontal and also looking at moving from the previous generation hardware to the next generation hardware. So all those details, you can find the white papers, and you can find them either in the Dell website or at the ACG research website >> ACGresearch.com? >> ACG research. Yeah, if you just search ACG research, you'll find- >> Yeah. >> Lots of white papers on TCO. So you know, what I want to say, relative to the vertical versus horizontal. Yeah, obviously in the vertical side, some of those things will run well, I mean it won't have issues. However, that being said, as we move to cloud native, you know, it's very high performance, okay? In terms of the stack, whether it be a Red Hat or a VMware or other cloud layers, that's really become much more mature. It now it's all CNF base, which is really containerized, very high performance. And so I don't think really performance is an issue. However, my feeling is that, if you want to offer new services and generate new revenue, you're not going to do it in vertical stacks, period. You're going to be able to do a packet core, you'll be able to do a ran over here. But now what if I want to offer a gaming service? What if I want to do metaverse? What if I want to do, you have to have an environment that's a multi-vendor environment that supports an ecosystem. Even in the RAN, when we look at the RIC, and the xApps and the rApps, these are multi-vendor environments that's going to create a lot of flexibility and you can't do that if you're restricted to, I can only have one vendor running on this hardware. >> Yeah, we're seeing these vendors work together and create RICs. That's obviously a key point, but what I'm hearing is that there may be trade offs, but the incremental value is going to overwhelm that. Second question I have, Peter is, TCO, I've been hearing a lot about 30%, you know, where's that 30% come from? Is it Op, is it from an OpEx standpoint? Is it labor, is it power? Is it, you mentioned, you know, cutting the number of servers in half. If I can unpack the granularity of that TCO, where's the benefit coming from? >> Yeah, the answer is yes. (Peter and Charles laugh) >> Okay, we'll do. >> Yeah, so- >> One side that, in terms of, where is the big bang for the bucks? >> So I mean, so you really need to look at the white paper to see details, but definitely power, definitely labor, definitely reducing the number of servers, you know, reducing the CapEx. The other thing is, is as you move to this really next generation horizontal telco cloud, there's the whole automation and orchestration, that is a key component as well. And it's enabled by what Dell is doing. It's enabled by the, because the thing is you're not going to have end-to-end automation if you have all this legacy stuff there or if you have these vertical stacks where you can't integrate. I mean you can automate that part and then you have separate automation here, you separate. you need to have integrated automation and orchestration across the whole thing. >> One other point I would add also, right, on the hardware perspective, right? With the customized hardware, what we allow operator to do is, take out the existing appliance and push a edge optimized server without reworking the entire infrastructure. There is a significant saving where you don't have to rethink about what is my power infrastructure, right? What is my security infrastructure? The server is designed to leverage the existing, what is already there. >> How should telco, Charles, plan for this transformation? Are there specific best practices that you would recommend in terms of the operational model? >> Great question. I think first thing is do an inventory of what you have. Understand what your constraints are and then come to Dell, we will love to consult with you, based on our experience on the best practices. We know how to minimize additional changes. We know how to help your support engineer, understand how to shift appliance based operation to a cloud-based operation. >> Is that a service you offer? Is that a pre-sales freebie? What is maybe both? >> It's both. >> Yeah. >> It's both. >> Yeah. >> Guys- >> Just really quickly. >> We're going to wrap. >> The, yeah. Dave loves the TCO discussion. I'm always thinking in terms of, well how do you measure TCO when you're comparing something where you can't do something to an environment where you're going to be able to do something new? And I know that that's always the challenge in any kind of emerging market where things are changing, any? >> Well, I mean we also look at, not only TCO, but we look at overall business case. So there's basically service at GLD and revenue and then there's faster time to revenues. Well, and actually ACG, we actually have a platform called the BAE or Business Analytics Engine that's a very sophisticated simulation cloud-based platform, where we can actually look at revenue month by month. And we look at what's the impact of accelerating revenue by three months. By four months. >> So you're looking into- >> By six months- >> So you're forward looking. You're just not consistently- >> So we're not just looking at TCO, we're looking at the overall business case benefit. >> Yeah, exactly right. There's the TCO, which is the hard dollars. >> Right. >> CFO wants to see that, he or she needs to see that. But you got to, you can convince that individual, that there's a business case around it. >> Peter: Yeah. >> And then you're going to sign up for that number. >> Peter: Yeah. >> And they're going to be held to it. That's the story the world wants. >> At the end of the day, telcos have to be offered new services 'cause look at all the money that's been spent. >> Dave: Yeah, that's right. >> On investment on 5G and everything else. >> 0.5 trillion over the next seven years. All right, guys, we got to go. Sorry to cut you off. >> Okay, thank you very much. >> But we're wall to wall here. All right, thanks so much for coming on. >> Dave: Fantastic. >> All right, Dave Vellante, for Dave Nicholson. Lisa Martin's in the house. John Furrier in Palo Alto Studios. Keep it right there. MWC 23 live from the Fira in Barcelona. (light airy music)

(upbeat music) >> Hello, welcome back to theCUBE's AWS RE:Invent 2022 Coverage. I'm John Furrier, host of theCUBE. Got a great lineup here, Itamar Ankorion SVP Technology Alliance at Qlik and Peter McDonald, vice President, cloud partnerships and business development Snowflake. We're going to talk about bringing SAP data to life, for joint Snowflake, Qlik and AWS Solution. Gentlemen, thanks for coming on theCUBE Really appreciate it. >> Thank you. >> Thank you, great meeting you John. >> Just to get started, introduce yourselves to the audience, then going to jump into what you guys are doing together, unique relationship here, really compelling solution in cloud. Big story about applications and scale this year. Let's introduce yourselves. Peter, we'll start with you. >> Great. I'm Peter MacDonald. I am vice president of Cloud Partners and business development here at Snowflake. On the Cloud Partner side, that means I manage AWS relationship along with Microsoft and Google Cloud. What we do together in terms of complimentary products, GTM, co-selling, things like that. Importantly, working with other third parties like Qlik for joint solutions. On business development, it's negotiating custom commercial partnerships, large companies like Salesforce and Dell, smaller companies at most for our venture portfolio. >> Thanks Peter and hi John. It's great to be back here. So I'm Itamar Ankorion and I'm the senior vice president responsible for technology alliances here at Qlik. With that, own strategic alliances, including our key partners in the cloud, including Snowflake and AWS. I've been in the data and analytics enterprise software market for 20 plus years, and my main focus is product management, marketing, alliances, and business development. I joined Qlik about three and a half years ago through the acquisition of Attunity, which is now the foundation for Qlik data integration. So again, we focus in my team on creating joint solution alignment with our key partners to provide more value to our customers. >> Great to have both you guys, senior executives in the industry on theCUBE here, talking about data, obviously bringing SAP data to life is the theme of this segment, but this reinvent, it's all about the data, big data end-to-end story, a lot about data being intrinsic as the CEO says on stage around in the organizations in all aspects. Take a minute to explain what you guys are doing as from a company standpoint. Snowflake and Qlik and the solutions, why here at AWS? Peter, we'll start with you at Snowflake, what you guys do as a company, your mission, your focus. >> That was great, John. Yeah, so here at Snowflake, we focus on the data platform and until recently, data platforms required expensive on-prem hardware appliances. And despite all that expense, customers had capacity constraints, inexpensive maintenance, and had limited functionality that all impeded these organizations from reaching their goals. Snowflake is a cloud native SaaS platform, and we've become so successful because we've addressed these pain points and have other new special features. For example, securely sharing data across both the organization and the value chain without copying the data, support for new data types such as JSON and structured data, and also advance in database data governance. Snowflake integrates with complimentary AWS services and other partner products. So we can enable holistic solutions that include, for example, here, both Qlik and AWS SageMaker, and comprehend and bring those to joint customers. Our customers want to convert data into insights along with advanced analytics platforms in AI. That is how they make holistic data-driven solutions that will give them competitive advantage. With Snowflake, our approach is to focus on customer solutions that leverage data from existing systems such as SAP, wherever they are in the cloud or on-premise. And to do this, we leverage partners like Qlik native US to help customers transform their businesses. We provide customers with a premier data analytics platform as a result. Itamar, why don't you talk about Qlik a little bit and then we can dive into the specific SAP solution here and some trends >> Sounds great, Peter. So Qlik provides modern data integration and analytics software used by over 38,000 customers worldwide. Our focus is to help our customers turn data into value and help them close the gap between data all the way through insight and action. We offer click data integration and click data analytics. Click data integration helps to automate the data pipelines to deliver data to where they want to use them in real-time and make the data ready for analytics and then Qlik data analytics is a robust platform for analytics and business intelligence has been a leader in the Gartner Magic Quadrant for over 11 years now in the market. And both of these come together into what we call Qlik Cloud, which is our SaaS based platform. So providing a more seamless way to consume all these services and accelerate time to value with customer solutions. In terms of partnerships, both Snowflake and AWS are very strategic to us here at Qlik, so we have very comprehensive investment to ensure strong joint value proposition to we can bring to our mutual customers, everything from aligning our roadmaps through optimizing and validating integrations, collaborating on best practices, packaging joint solutions like the one we'll talk about today. And with that investment, we are an elite level, top level partner with Snowflake. We fly that our technology is Snowflake-ready across the entire product set and we have hundreds of joint customers together and with AWS we've also partnered for a long time. We're here to reinvent. We've been here with the first reinvent since the inaugural one, so it kind of gives you an idea for how long we've been working with AWS. We provide very comprehensive integration with AWS data analytics services, and we have several competencies ranging from data analytics to migration and modernization. So that's our focus and again, we're excited about working with Snowflake and AWS to bring solutions together to market. >> Well, I'm looking forward to unpacking the solutions specifically, and congratulations on the continued success of both your companies. We've been following them obviously for a very long time and seeing the platform evolve beyond just SaaS and a lot more going on in cloud these days, kind of next generation emerging. You know, we're seeing a lot of macro trends that are going to be powering some of the things we're going to get into real quickly. But before we get into the solution, what are some of those power dynamics in the industry that you're seeing in trends specifically that are impacting your customers that are taking us down this road of getting more out of the data and specifically the SAP, but in general trends and dynamics. What are you hearing from your customers? Why do they care? Why are they going down this road? Peter, we'll start with you. >> Yeah, I'll go ahead and start. Thanks. Yeah, I'd say we continue to see customers being, being very eager to transform their businesses and they know they need to leverage technology and data to do so. They're also increasingly depending upon the cloud to bring that agility, that elasticity, new functionality necessary to react in real-time to every evolving customer needs. You look at what's happened over the last three years, and boy, the macro environment customers, it's all changing so fast. With our partnerships with AWS and Qlik, we've been able to bring to market innovative solutions like the one we're announcing today that spans all three companies. It provides a holistic solution and an integrated solution for our customer. >> Itamar let's get into it, you've been with theCUBE, you've seen the journey, you have your own journey, many, many years, you've seen the waves. What's going on now? I mean, what's the big wave? What's the dynamic powering this trend? >> Yeah, in a nutshell I'll call it, it's all about time. You know, it's time to value and it's about real-time data. I'll kind of talk about that a bit. So, I mean, you hear a lot about the data being the new oil, but it's definitely, we see more and more customers seeing data as their critical enabler for innovation and digital transformation. They look for ways to monetize data. They look as the data as the way in which they can innovate and bring different value to the customers. So we see customers want to use more data so to get more value from data. We definitely see them wanting to do it faster, right, than before. And we definitely see them looking for agility and automation as ways to accelerate time to value, and also reduce overall costs. I did mention real-time data, so we definitely see more and more customers, they want to be able to act and make decisions based on fresh data. So yesterday's data is just not good enough. >> John: Yeah. >> It's got to be down to the hour, down to the minutes and sometimes even lower than that. And then I think we're also seeing customers look to their core business systems where they have a lot of value, like the SAP, like mainframe and thinking, okay, our core data is there, how can we get more value from this data? So that's key things we see all the time with customers. >> Yeah, we did a big editorial segment this year on, we called data as code. Data as code is kind of a riff on infrastructure as code and you start to see data becoming proliferating into all aspects, fresh data. It's not just where you store it, it's how you share it, it's how you turn it into an application intrinsically involved in all aspects. This is the big theme this year and that's driving all the conversations here at RE:Invent. And I'm guaranteeing you, it's going to happen for another five and 10 years. It's not stopping. So I got to get into the solution, you guys mentioned SAP and you've announced the solution by Qlik, Snowflake and AWS for your customers using SAP. Can you share more about this solution? What's unique about it? Why is it important and why now? Peter, Itamar, we'll start with you first. >> Let me jump in, this is really, I'll jump because I'm excited. We're very excited about this solution and it's also a solution by the way and again, we've seen proven customer success with it. So to your point, it's ready to scale, it's starting, I think we're going to see a lot of companies doing this over the next few years. But before we jump to the solution, let me maybe take a few minutes just to clarify the need, why we're seeing, why we're seeing customers jump to do this. So customers that use SAP, they use it to manage the core of their business. So think order processing, management, finance, inventory, supply chain, and so much more. So if you're running SAP in your company, that data creates a great opportunity for you to drive innovation and modernization. So what we see customers want to do, they want to do more with their data and more means they want to take SAP with non-SAP data and use it together to drive new insights. They want to use real-time data to drive real-time analytics, which they couldn't do to date. They want to bring together descriptive with predictive analytics. So adding machine learning in AI to drive more value from the data. And naturally they want to do it faster. So find ways to iterate faster on their solutions, have freedom with the data and agility. And I think this is really where cloud data platforms like Snowflake and AWS, you know, bring that value to be able to drive that. Now to do that you need to unlock the SAP data, which is a lot of also where Qlik comes in because typical challenges these customers run into is the complexity, inherent in SAP data. Tens of thousands of tables, proprietary formats, complex data models, licensing restrictions, and more than, you have performance issues, they usually run into how do we handle the throughput, the volumes while maintaining lower latency and impact. Where do we find knowledge to really understand how to get all this done? So these are the things we've looked at when we came together to create a solution and make it unique. So when you think about its uniqueness, because we put together a lot, and I'll go through three, four key things that come together to make this unique. First is about data delivery. How do you have the SAP data delivery? So how do you get it from ECC, from HANA from S/4HANA, how do you deliver the data and the metadata and how that integration well into Snowflake. And what we've done is we've focused a lot on optimizing that process and the continuous ingestion, so the real-time ingestion of the data in a way that works really well with the Snowflake system, data cloud. Second thing is we looked at SAP data transformation, so once the data arrives at Snowflake, how do we turn it into being analytics ready? So that's where data transformation and data worth automation come in. And these are all elements of this solution. So creating derivative datasets, creating data marts, and all of that is done by again, creating an optimized integration that pushes down SQL based transformations, so they can be processed inside Snowflake, leveraging its powerful engine. And then the third element is bringing together data visualization analytics that can also take all the data now that in organizing inside Snowflake, bring other data in, bring machine learning from SageMaker, and then you go to create a seamless integration to bring analytic applications to life. So these are all things we put together in the solution. And maybe the last point is we actually took the next step with this and we created something we refer to as solution accelerators, which we're really, really keen about. Think about this as prepackaged templates for common business analytic needs like order to cash, finance, inventory. And we can either dig into that a little more later, but this gets the next level of value to the customers all built into this joint solution. >> Yeah, I want to get to the accelerators, but real quick, Peter, your reaction to the solution, what's unique about it? And obviously Snowflake, we've been seeing the progression data applications, more developers developing on top of Snowflake, data as code kind of implies developer ecosystem. This is kind of interesting. I mean, you got partnering with Qlik and AWS, it's kind of a developer-like thinking real solution. What's unique about this SAP solution that's, that's different than what customers can get anywhere else or not? >> Yeah, well listen, I think first of all, you have to start with the idea of the solution. This are three companies coming together to build a holistic solution that is all about, you know, creating a great opportunity to turn SAP data into value this is Itamar was talking about, that's really what we're talking about here and there's a lot of technology underneath it. I'll talk more about the Snowflake technology, what's involved here, and then cover some of the AWS pieces as well. But you know, we're focusing on getting that value out and accelerating time to value for our joint customers. As Itamar was saying, you know, there's a lot of complexity with the SAP data and a lot of value there. How can we manage that in a prepackaged way, bringing together best of breed solutions with proven capabilities and bringing this to market quickly for our joint customers. You know, Snowflake and AWS have been strong partners for a number of years now, and that's not only on how Snowflake runs on top of AWS, but also how we integrate with their complementary analytics and then all products. And so, you know, we want to be able to leverage those in addition to what Qlik is bringing in terms of the data transformations, bringing data out of SAP in the visualization as well. All very critical. And then we want to bring in the predictive analytics, AWS brings and what Sage brings. We'll talk about that a little bit later on. Some of the technologies that we're leveraging are some of our latest cutting edge technologies that really make things easier for both our partners and our customers. For example, Qlik leverages Snowflakes recently released Snowpark for Python functionality to push down those data transformations from clicking the Snowflake that Itamar's mentioning. And while we also leverage Snowpark for integrations with Amazon SageMaker, but there's a lot of great new technology that just makes this easy and compelling for customers. >> I think that's the big word, easy button here for what may look like a complex kind of integration, kind of turnkey, really, really compelling example of the modern era we're living in, as we always say in theCUBE. You mentioned accelerators, SAP accelerators. Can you give an example of how that works with the technology from the third party providers to deliver this business value Itamar, 'cause that was an interesting comment. What's the example? Give an example of this acceleration. >> Yes, certainly. I think this is something that really makes this truly, truly unique in the industry and again, a great opportunity for customers. So we kind talked earlier about there's a lot of things that need to be done with SP data to turn it to value. And these accelerator, as the name suggests, are designed to do just that, to kind of jumpstart the process and reduce the time and the risk involved in such project. So again, these are pre-packaged templates. We basically took a lot of knowledge, and a lot of configurations, best practices about to get things done and we put 'em together. So think about all the steps, it includes things like data extraction, so already knowing which tables, all the relevant tables that you need to get data from in the contexts of the solution you're looking for, say like order to cash, we'll get back to that one. How do you continuously deliver that data into Snowflake in an in efficient manner, handling things like data type mappings, metadata naming conventions and transformations. The data models you build all the way to data mart definitions and all the transformations that the data needs to go through moving through steps until it's fully analytics ready. And then on top of that, even adding a library of comprehensive analytic dashboards and integrations through machine learning and AI and put all of that in a way that's in pre-integrated and tested to work with Snowflake and AWS. So this is where again, you get this entire recipe that's ready. So take for example, I think I mentioned order to cash. So again, all these things I just talked about, I mean, for those who are not familiar, I mean order to cash is a critical business process for every organization. So especially if you're in retail, manufacturing, enterprise, it's a big... This is where, you know, starting with booking a sales order, following by fulfilling the order, billing the customer, then managing the accounts receivable when the customer actually pays, right? So this all process, you got sales order fulfillment and the billing impacts customer satisfaction, you got receivable payments, you know, the impact's working capital, cash liquidity. So again, as a result this order to cash process is a lifeblood for many businesses and it's critical to optimize and understand. So the solution accelerator we created specifically for order to cash takes care of understanding all these aspects and the data that needs to come with it. So everything we outline before to make the data available in Snowflake in a way that's really useful for downstream analytics, along with dashboards that are already common for that, for that use case. So again, this enables customers to gain real-time visibility into their sales orders, fulfillment, accounts receivable performance. That's what the Excel's are all about. And very similarly, we have another one for example, for finance analytics, right? So this will optimize financial data reporting, helps customers get insights into P&L, financial risk of stability or inventory analytics that helps with, you know, improve planning and inventory management, utilization, increased efficiencies, you know, so in supply chain. So again, these accelerators really help customers get a jumpstart and move faster with their solutions. >> Peter, this is the easy button we just talked about, getting things going, you know, get the ball rolling, get some acceleration. Big part of this are the three companies coming together doing this. >> Yeah, and to build on what Itamar just said that the SAP data obviously has tremendous value. Those sales orders, distribution data, financial data, bringing that into Snowflake makes it easily accessible, but also it enables it to be combined with other data too, is one of the things that Snowflake does so well. So you can get a full view of the end-to-end process and the business overall. You know, for example, I'll just take one, you know, one example that, that may not come to mind right away, but you know, looking at the impact of weather conditions on supply chain logistics is relevant and material and have interest to our customers. How do you bring those different data sets together in an easy way, bringing the data out of SAP, bringing maybe other data out of other systems through Qlik or through Snowflake, directly bringing data in from our data marketplace and bring that all together to make it work. You know, fundamentally organizational silos and the data fragmentation exist otherwise make it really difficult to drive modern analytics projects. And that in turn limits the value that our customers are getting from SAP data and these other data sets. We want to enable that and unleash. >> Yeah, time for value. This is great stuff. Itamar final question, you know, what are customers using this? What do you have? I'm sure you have customers examples already using the solution. Can you share kind of what these examples look like in the use cases and the value? >> Oh yeah, absolutely. Thank you. Happy to. We have customers across different, different sectors. You see manufacturing, retail, energy, oil and gas, CPG. So again, customers in those segments, typically sectors typically have SAP. So we have customers in all of them. A great example is like Siemens Energy. Siemens Energy is a global provider of gas par services. You know, over what, 28 billion, 30 billion in revenue. 90,000 employees. They operate globally in over 90 countries. So they've used SAP HANA as a core system, so it's running on premises, multiple locations around the world. And what they were looking for is a way to bring all these data together so they can innovate with it. And the thing is, Peter mentioned earlier, not just the SAP data, but also bring other data from other systems to bring it together for more value. That includes finance data, these logistics data, these customer CRM data. So they bring data from over 20 different SAP systems. Okay, with Qlik data integration, feeding that into Snowflake in under 20 minutes, 24/7, 365, you know, days a year. Okay, they get data from over 20,000 tables, you know, over million, hundreds of millions of records daily going in. So it is a great example of the type of scale, scalability, agility and speed that they can get to drive these kind of innovation. So that's a great example with Siemens. You know, another one comes to mind is a global manufacturer. Very similar scenario, but you know, they're using it for real-time executive reporting. So it's more like feasibility to the production data as well as for financial analytics. So think, think, think about everything from audit to texts to innovate financial intelligence because all the data's coming from SAP. >> It's a great time to be in the data business again. It keeps getting better and better. There's more data coming. It's not stopping, you know, it's growing so fast, it keeps coming. Every year, it's the same story, Peter. It's like, doesn't stop coming. As we wrap up here, let's just get customers some information on how to get started. I mean, obviously you're starting to see the accelerators, it's a great program there. What a great partnership between the two companies and AWS. How can customers get started to learn about the solution and take advantage of it, getting more out of their SAP data, Peter? >> Yeah, I think the first place to go to is talk to Snowflake, talk to AWS, talk to our account executives that are assigned to your account. Reach out to them and they will be able to educate you on the solution. We have packages up very nicely and can be deployed very, very quickly. >> Well gentlemen, thank you so much for coming on. Appreciate the conversation. Great overview of the partnership between, you know, Snowflake and Qlik and AWS on a joint solution. You know, getting more out of the SAP data. It's really kind of a key, key solution, bringing SAP data to life. Thanks for coming on theCUBE. Appreciate it. >> Thank you. >> Thank you John. >> Okay, this is theCUBE coverage here at RE:Invent 2022. I'm John Furrier, your host of theCUBE. Thanks for watching. (upbeat music)

(upbeat music) >> Hello, welcome back to theCUBE's AWS RE:Invent 2022 Coverage. I'm John Furrier, host of theCUBE. Got a great lineup here, Itamar Ankorion SVP Technology Alliance at Qlik and Peter McDonald, vice President, cloud partnerships and business development Snowflake. We're going to talk about bringing SAP data to life, for joint Snowflake, Qlik and AWS Solution. Gentlemen, thanks for coming on theCUBE Really appreciate it. >> Thank you. >> Thank you, great meeting you John. >> Just to get started, introduce yourselves to the audience, then going to jump into what you guys are doing together, unique relationship here, really compelling solution in cloud. Big story about applications and scale this year. Let's introduce yourselves. Peter, we'll start with you. >> Great. I'm Peter MacDonald. I am vice president of Cloud Partners and business development here at Snowflake. On the Cloud Partner side, that means I manage AWS relationship along with Microsoft and Google Cloud. What we do together in terms of complimentary products, GTM, co-selling, things like that. Importantly, working with other third parties like Qlik for joint solutions. On business development, it's negotiating custom commercial partnerships, large companies like Salesforce and Dell, smaller companies at most for our venture portfolio. >> Thanks Peter and hi John. It's great to be back here. So I'm Itamar Ankorion and I'm the senior vice president responsible for technology alliances here at Qlik. With that, own strategic alliances, including our key partners in the cloud, including Snowflake and AWS. I've been in the data and analytics enterprise software market for 20 plus years, and my main focus is product management, marketing, alliances, and business development. I joined Qlik about three and a half years ago through the acquisition of Attunity, which is now the foundation for Qlik data integration. So again, we focus in my team on creating joint solution alignment with our key partners to provide more value to our customers. >> Great to have both you guys, senior executives in the industry on theCUBE here, talking about data, obviously bringing SAP data to life is the theme of this segment, but this reinvent, it's all about the data, big data end-to-end story, a lot about data being intrinsic as the CEO says on stage around in the organizations in all aspects. Take a minute to explain what you guys are doing as from a company standpoint. Snowflake and Qlik and the solutions, why here at AWS? Peter, we'll start with you at Snowflake, what you guys do as a company, your mission, your focus. >> That was great, John. Yeah, so here at Snowflake, we focus on the data platform and until recently, data platforms required expensive on-prem hardware appliances. And despite all that expense, customers had capacity constraints, inexpensive maintenance, and had limited functionality that all impeded these organizations from reaching their goals. Snowflake is a cloud native SaaS platform, and we've become so successful because we've addressed these pain points and have other new special features. For example, securely sharing data across both the organization and the value chain without copying the data, support for new data types such as JSON and structured data, and also advance in database data governance. Snowflake integrates with complimentary AWS services and other partner products. So we can enable holistic solutions that include, for example, here, both Qlik and AWS SageMaker, and comprehend and bring those to joint customers. Our customers want to convert data into insights along with advanced analytics platforms in AI. That is how they make holistic data-driven solutions that will give them competitive advantage. With Snowflake, our approach is to focus on customer solutions that leverage data from existing systems such as SAP, wherever they are in the cloud or on-premise. And to do this, we leverage partners like Qlik native US to help customers transform their businesses. We provide customers with a premier data analytics platform as a result. Itamar, why don't you talk about Qlik a little bit and then we can dive into the specific SAP solution here and some trends >> Sounds great, Peter. So Qlik provides modern data integration and analytics software used by over 38,000 customers worldwide. Our focus is to help our customers turn data into value and help them close the gap between data all the way through insight and action. We offer click data integration and click data analytics. Click data integration helps to automate the data pipelines to deliver data to where they want to use them in real-time and make the data ready for analytics and then Qlik data analytics is a robust platform for analytics and business intelligence has been a leader in the Gartner Magic Quadrant for over 11 years now in the market. And both of these come together into what we call Qlik Cloud, which is our SaaS based platform. So providing a more seamless way to consume all these services and accelerate time to value with customer solutions. In terms of partnerships, both Snowflake and AWS are very strategic to us here at Qlik, so we have very comprehensive investment to ensure strong joint value proposition to we can bring to our mutual customers, everything from aligning our roadmaps through optimizing and validating integrations, collaborating on best practices, packaging joint solutions like the one we'll talk about today. And with that investment, we are an elite level, top level partner with Snowflake. We fly that our technology is Snowflake-ready across the entire product set and we have hundreds of joint customers together and with AWS we've also partnered for a long time. We're here to reinvent. We've been here with the first reinvent since the inaugural one, so it kind of gives you an idea for how long we've been working with AWS. We provide very comprehensive integration with AWS data analytics services, and we have several competencies ranging from data analytics to migration and modernization. So that's our focus and again, we're excited about working with Snowflake and AWS to bring solutions together to market. >> Well, I'm looking forward to unpacking the solutions specifically, and congratulations on the continued success of both your companies. We've been following them obviously for a very long time and seeing the platform evolve beyond just SaaS and a lot more going on in cloud these days, kind of next generation emerging. You know, we're seeing a lot of macro trends that are going to be powering some of the things we're going to get into real quickly. But before we get into the solution, what are some of those power dynamics in the industry that you're seeing in trends specifically that are impacting your customers that are taking us down this road of getting more out of the data and specifically the SAP, but in general trends and dynamics. What are you hearing from your customers? Why do they care? Why are they going down this road? Peter, we'll start with you. >> Yeah, I'll go ahead and start. Thanks. Yeah, I'd say we continue to see customers being, being very eager to transform their businesses and they know they need to leverage technology and data to do so. They're also increasingly depending upon the cloud to bring that agility, that elasticity, new functionality necessary to react in real-time to every evolving customer needs. You look at what's happened over the last three years, and boy, the macro environment customers, it's all changing so fast. With our partnerships with AWS and Qlik, we've been able to bring to market innovative solutions like the one we're announcing today that spans all three companies. It provides a holistic solution and an integrated solution for our customer. >> Itamar let's get into it, you've been with theCUBE, you've seen the journey, you have your own journey, many, many years, you've seen the waves. What's going on now? I mean, what's the big wave? What's the dynamic powering this trend? >> Yeah, in a nutshell I'll call it, it's all about time. You know, it's time to value and it's about real-time data. I'll kind of talk about that a bit. So, I mean, you hear a lot about the data being the new oil, but it's definitely, we see more and more customers seeing data as their critical enabler for innovation and digital transformation. They look for ways to monetize data. They look as the data as the way in which they can innovate and bring different value to the customers. So we see customers want to use more data so to get more value from data. We definitely see them wanting to do it faster, right, than before. And we definitely see them looking for agility and automation as ways to accelerate time to value, and also reduce overall costs. I did mention real-time data, so we definitely see more and more customers, they want to be able to act and make decisions based on fresh data. So yesterday's data is just not good enough. >> John: Yeah. >> It's got to be down to the hour, down to the minutes and sometimes even lower than that. And then I think we're also seeing customers look to their core business systems where they have a lot of value, like the SAP, like mainframe and thinking, okay, our core data is there, how can we get more value from this data? So that's key things we see all the time with customers. >> Yeah, we did a big editorial segment this year on, we called data as code. Data as code is kind of a riff on infrastructure as code and you start to see data becoming proliferating into all aspects, fresh data. It's not just where you store it, it's how you share it, it's how you turn it into an application intrinsically involved in all aspects. This is the big theme this year and that's driving all the conversations here at RE:Invent. And I'm guaranteeing you, it's going to happen for another five and 10 years. It's not stopping. So I got to get into the solution, you guys mentioned SAP and you've announced the solution by Qlik, Snowflake and AWS for your customers using SAP. Can you share more about this solution? What's unique about it? Why is it important and why now? Peter, Itamar, we'll start with you first. >> Let me jump in, this is really, I'll jump because I'm excited. We're very excited about this solution and it's also a solution by the way and again, we've seen proven customer success with it. So to your point, it's ready to scale, it's starting, I think we're going to see a lot of companies doing this over the next few years. But before we jump to the solution, let me maybe take a few minutes just to clarify the need, why we're seeing, why we're seeing customers jump to do this. So customers that use SAP, they use it to manage the core of their business. So think order processing, management, finance, inventory, supply chain, and so much more. So if you're running SAP in your company, that data creates a great opportunity for you to drive innovation and modernization. So what we see customers want to do, they want to do more with their data and more means they want to take SAP with non-SAP data and use it together to drive new insights. They want to use real-time data to drive real-time analytics, which they couldn't do to date. They want to bring together descriptive with predictive analytics. So adding machine learning in AI to drive more value from the data. And naturally they want to do it faster. So find ways to iterate faster on their solutions, have freedom with the data and agility. And I think this is really where cloud data platforms like Snowflake and AWS, you know, bring that value to be able to drive that. Now to do that you need to unlock the SAP data, which is a lot of also where Qlik comes in because typical challenges these customers run into is the complexity, inherent in SAP data. Tens of thousands of tables, proprietary formats, complex data models, licensing restrictions, and more than, you have performance issues, they usually run into how do we handle the throughput, the volumes while maintaining lower latency and impact. Where do we find knowledge to really understand how to get all this done? So these are the things we've looked at when we came together to create a solution and make it unique. So when you think about its uniqueness, because we put together a lot, and I'll go through three, four key things that come together to make this unique. First is about data delivery. How do you have the SAP data delivery? So how do you get it from ECC, from HANA from S/4HANA, how do you deliver the data and the metadata and how that integration well into Snowflake. And what we've done is we've focused a lot on optimizing that process and the continuous ingestion, so the real-time ingestion of the data in a way that works really well with the Snowflake system, data cloud. Second thing is we looked at SAP data transformation, so once the data arrives at Snowflake, how do we turn it into being analytics ready? So that's where data transformation and data worth automation come in. And these are all elements of this solution. So creating derivative datasets, creating data marts, and all of that is done by again, creating an optimized integration that pushes down SQL based transformations, so they can be processed inside Snowflake, leveraging its powerful engine. And then the third element is bringing together data visualization analytics that can also take all the data now that in organizing inside Snowflake, bring other data in, bring machine learning from SageMaker, and then you go to create a seamless integration to bring analytic applications to life. So these are all things we put together in the solution. And maybe the last point is we actually took the next step with this and we created something we refer to as solution accelerators, which we're really, really keen about. Think about this as prepackaged templates for common business analytic needs like order to cash, finance, inventory. And we can either dig into that a little more later, but this gets the next level of value to the customers all built into this joint solution. >> Yeah, I want to get to the accelerators, but real quick, Peter, your reaction to the solution, what's unique about it? And obviously Snowflake, we've been seeing the progression data applications, more developers developing on top of Snowflake, data as code kind of implies developer ecosystem. This is kind of interesting. I mean, you got partnering with Qlik and AWS, it's kind of a developer-like thinking real solution. What's unique about this SAP solution that's, that's different than what customers can get anywhere else or not? >> Yeah, well listen, I think first of all, you have to start with the idea of the solution. This are three companies coming together to build a holistic solution that is all about, you know, creating a great opportunity to turn SAP data into value this is Itamar was talking about, that's really what we're talking about here and there's a lot of technology underneath it. I'll talk more about the Snowflake technology, what's involved here, and then cover some of the AWS pieces as well. But you know, we're focusing on getting that value out and accelerating time to value for our joint customers. As Itamar was saying, you know, there's a lot of complexity with the SAP data and a lot of value there. How can we manage that in a prepackaged way, bringing together best of breed solutions with proven capabilities and bringing this to market quickly for our joint customers. You know, Snowflake and AWS have been strong partners for a number of years now, and that's not only on how Snowflake runs on top of AWS, but also how we integrate with their complementary analytics and then all products. And so, you know, we want to be able to leverage those in addition to what Qlik is bringing in terms of the data transformations, bringing data out of SAP in the visualization as well. All very critical. And then we want to bring in the predictive analytics, AWS brings and what Sage brings. We'll talk about that a little bit later on. Some of the technologies that we're leveraging are some of our latest cutting edge technologies that really make things easier for both our partners and our customers. For example, Qlik leverages Snowflakes recently released Snowpark for Python functionality to push down those data transformations from clicking the Snowflake that Itamar's mentioning. And while we also leverage Snowpark for integrations with Amazon SageMaker, but there's a lot of great new technology that just makes this easy and compelling for customers. >> I think that's the big word, easy button here for what may look like a complex kind of integration, kind of turnkey, really, really compelling example of the modern era we're living in, as we always say in theCUBE. You mentioned accelerators, SAP accelerators. Can you give an example of how that works with the technology from the third party providers to deliver this business value Itamar, 'cause that was an interesting comment. What's the example? Give an example of this acceleration. >> Yes, certainly. I think this is something that really makes this truly, truly unique in the industry and again, a great opportunity for customers. So we kind talked earlier about there's a lot of things that need to be done with SP data to turn it to value. And these accelerator, as the name suggests, are designed to do just that, to kind of jumpstart the process and reduce the time and the risk involved in such project. So again, these are pre-packaged templates. We basically took a lot of knowledge, and a lot of configurations, best practices about to get things done and we put 'em together. So think about all the steps, it includes things like data extraction, so already knowing which tables, all the relevant tables that you need to get data from in the contexts of the solution you're looking for, say like order to cash, we'll get back to that one. How do you continuously deliver that data into Snowflake in an in efficient manner, handling things like data type mappings, metadata naming conventions and transformations. The data models you build all the way to data mart definitions and all the transformations that the data needs to go through moving through steps until it's fully analytics ready. And then on top of that, even adding a library of comprehensive analytic dashboards and integrations through machine learning and AI and put all of that in a way that's in pre-integrated and tested to work with Snowflake and AWS. So this is where again, you get this entire recipe that's ready. So take for example, I think I mentioned order to cash. So again, all these things I just talked about, I mean, for those who are not familiar, I mean order to cash is a critical business process for every organization. So especially if you're in retail, manufacturing, enterprise, it's a big... This is where, you know, starting with booking a sales order, following by fulfilling the order, billing the customer, then managing the accounts receivable when the customer actually pays, right? So this all process, you got sales order fulfillment and the billing impacts customer satisfaction, you got receivable payments, you know, the impact's working capital, cash liquidity. So again, as a result this order to cash process is a lifeblood for many businesses and it's critical to optimize and understand. So the solution accelerator we created specifically for order to cash takes care of understanding all these aspects and the data that needs to come with it. So everything we outline before to make the data available in Snowflake in a way that's really useful for downstream analytics, along with dashboards that are already common for that, for that use case. So again, this enables customers to gain real-time visibility into their sales orders, fulfillment, accounts receivable performance. That's what the Excel's are all about. And very similarly, we have another one for example, for finance analytics, right? So this will optimize financial data reporting, helps customers get insights into P&L, financial risk of stability or inventory analytics that helps with, you know, improve planning and inventory management, utilization, increased efficiencies, you know, so in supply chain. So again, these accelerators really help customers get a jumpstart and move faster with their solutions. >> Peter, this is the easy button we just talked about, getting things going, you know, get the ball rolling, get some acceleration. Big part of this are the three companies coming together doing this. >> Yeah, and to build on what Itamar just said that the SAP data obviously has tremendous value. Those sales orders, distribution data, financial data, bringing that into Snowflake makes it easily accessible, but also it enables it to be combined with other data too, is one of the things that Snowflake does so well. So you can get a full view of the end-to-end process and the business overall. You know, for example, I'll just take one, you know, one example that, that may not come to mind right away, but you know, looking at the impact of weather conditions on supply chain logistics is relevant and material and have interest to our customers. How do you bring those different data sets together in an easy way, bringing the data out of SAP, bringing maybe other data out of other systems through Qlik or through Snowflake, directly bringing data in from our data marketplace and bring that all together to make it work. You know, fundamentally organizational silos and the data fragmentation exist otherwise make it really difficult to drive modern analytics projects. And that in turn limits the value that our customers are getting from SAP data and these other data sets. We want to enable that and unleash. >> Yeah, time for value. This is great stuff. Itamar final question, you know, what are customers using this? What do you have? I'm sure you have customers examples already using the solution. Can you share kind of what these examples look like in the use cases and the value? >> Oh yeah, absolutely. Thank you. Happy to. We have customers across different, different sectors. You see manufacturing, retail, energy, oil and gas, CPG. So again, customers in those segments, typically sectors typically have SAP. So we have customers in all of them. A great example is like Siemens Energy. Siemens Energy is a global provider of gas par services. You know, over what, 28 billion, 30 billion in revenue. 90,000 employees. They operate globally in over 90 countries. So they've used SAP HANA as a core system, so it's running on premises, multiple locations around the world. And what they were looking for is a way to bring all these data together so they can innovate with it. And the thing is, Peter mentioned earlier, not just the SAP data, but also bring other data from other systems to bring it together for more value. That includes finance data, these logistics data, these customer CRM data. So they bring data from over 20 different SAP systems. Okay, with Qlik data integration, feeding that into Snowflake in under 20 minutes, 24/7, 365, you know, days a year. Okay, they get data from over 20,000 tables, you know, over million, hundreds of millions of records daily going in. So it is a great example of the type of scale, scalability, agility and speed that they can get to drive these kind of innovation. So that's a great example with Siemens. You know, another one comes to mind is a global manufacturer. Very similar scenario, but you know, they're using it for real-time executive reporting. So it's more like feasibility to the production data as well as for financial analytics. So think, think, think about everything from audit to texts to innovate financial intelligence because all the data's coming from SAP. >> It's a great time to be in the data business again. It keeps getting better and better. There's more data coming. It's not stopping, you know, it's growing so fast, it keeps coming. Every year, it's the same story, Peter. It's like, doesn't stop coming. As we wrap up here, let's just get customers some information on how to get started. I mean, obviously you're starting to see the accelerators, it's a great program there. What a great partnership between the two companies and AWS. How can customers get started to learn about the solution and take advantage of it, getting more out of their SAP data, Peter? >> Yeah, I think the first place to go to is talk to Snowflake, talk to AWS, talk to our account executives that are assigned to your account. Reach out to them and they will be able to educate you on the solution. We have packages up very nicely and can be deployed very, very quickly. >> Well gentlemen, thank you so much for coming on. Appreciate the conversation. Great overview of the partnership between, you know, Snowflake and Qlik and AWS on a joint solution. You know, getting more out of the SAP data. It's really kind of a key, key solution, bringing SAP data to life. Thanks for coming on theCUBE. Appreciate it. >> Thank you. >> Thank you John. >> Okay, this is theCUBE coverage here at RE:Invent 2022. I'm John Furrier, your host of theCUBE. Thanks for watching. (upbeat music)

(upbeat music) (logo swooshing) >> Good morning and welcome back to Dallas, ladies and gentlemen, we are here with theCUBE Live from Supercomputing 2022. David, my cohost, how are you doing? Exciting, day two, feeling good? >> Very exciting. Ready to start off the day. >> Very excited. We have two fascinating guests joining us to kick us off. Please welcome Pete and Armando. Gentlemen, thank you for being here with us. >> Thank you for having us. >> Thank you for having us. >> I'm excited that you're starting off the day because we've been hearing a lot of rumors about Ethernet as the fabric for HPC, but we really haven't done a deep dive yet during the show. You all seem all in on Ethernet. Tell us about that. Armando, why don't you start? >> Yeah, I mean, when you look at Ethernet, customers are asking for flexibility and choice. So when you look at HPC, InfiniBand's always been around, right? But when you look at where Ethernet's coming in, it's really our commercial in their enterprise customers. And not everybody wants to be in the top 500, what they want to do is improve their job time and improve their latency over the network. And when you look at Ethernet, you kind of look at the sweet spot between 8, 12, 16, 32 nodes, that's a perfect fit for Ethernet in that space and those types of jobs. >> I love that. Pete, you want to elaborate? >> Yeah, sure. I mean, I think one of the biggest things you find with Ethernet for HPC is that, if you look at where the different technologies have gone over time, you've had old technologies like, ATM, Sonic, Fifty, and pretty much everything is now kind of converged toward Ethernet. I mean, there's still some technologies such as InfiniBand, Omni-Path, that are out there. But basically, they're single source at this point. So what you see is that there is a huge ecosystem behind Ethernet. And you see that also the fact that Ethernet is used in the rest of the enterprise, is used in the cloud data centers, that is very easy to integrate HPC based systems into those systems. So as you move HPC out of academia into enterprise, into cloud service providers, it's much easier to integrate it with the same technology you're already using in those data centers, in those networks. >> So what's the state of the art for Ethernet right now? What's the leading edge? what's shipping now and what's in the near future? You're with Broadcom, you guys designed this stuff. >> Pete: Yeah. >> Savannah: Right. >> Yeah, so leading edge right now, got a couple things-- >> Savannah: We love good stage prop here on the theCUBE. >> Yeah, so this is Tomahawk 4. So this is what is in production, it's shipping in large data centers worldwide. We started sampling this in 2019, started going into data centers in 2020. And this is 25.6 terabytes per second. >> David: Okay. >> Which matches any other technology out there. Like if you look at say, InfinBand, highest they have right now that's just starting to get into production is 25.6 T. So state of the art right now is what we introduced, We announced this in August, This is Tomahawk 5, so this is 51.2 terabytes per second. So double the bandwidth, out of any other technology that's out there. And the important thing about networking technology is when you double the bandwidth, you don't just double the efficiency, actually, winds up being a factor of six efficiency. >> Savannah: Wow. >> 'Cause if you want, I can go into that, but... >> Why not? >> Well, what I want to know, please tell me that in your labs, you have a poster on the wall that says T five, with some like Terminator kind of character. (all laughs) 'Cause that would be cool. If it's not true, just don't say anything. I'll just... >> Pete: This can actually shift into a terminator. >> Well, so this is from a switching perspective. >> Yeah. >> When we talk about the end nodes, when we talk about creating a fabric, what's the latest in terms of, well, the nicks that are going in there, what speed are we talking about today? >> So as far as 30 speeds, it tends to be 50 gigabits per second. >> David: Okay. >> Moving to a hundred gig PAM-4. >> David: Okay. >> And we do see a lot of nicks in the 200 gig Ethernet port speed. So that would be four lanes, 50 gig. But we do see that advancing to 400 gig fairly soon, 800 gig in the future. But say state of the art right now, we're seeing for the end node tends to be 200 gig E based on 50 gig PAM-4. >> Wow. >> Yeah, that's crazy. >> Yeah, that is great. My mind is act actively blown. I want to circle back to something that you brought up a second ago, which I think is really astute. When you talked about HPC moving from academia into enterprise, you're both seeing this happen, where do you think we are on the adoption curve and sort of in that cycle? Armando, do you want to go? >> Yeah, well, if you look at the market research, they're actually telling you it's 50/50 now. So Ethernet is at the level of 50%, InfinBand's at 50%, right? >> Savannah: Interesting. >> Yeah, and so what's interesting to us, customers are coming to us and say, hey, we want to see flexibility and choice and, hey, let's look at Ethernet and let's look at InfiniBand. But what is interesting about this is that we're working with Broadcom, we have their chips in our lab, we their have switches in our lab. And really what we're trying to do is make it easy to simple and configure the network for essentially MPI. And so the goal here with our validated designs is really to simplify this. So if you have a customer that, hey, I've been InfiniBand but now I want to go Ethernet, there's going to be some learning curves there. And so what we want to do is really simplify that so that we can make it easy to install, get the cluster up and running and they can actually get some value out the cluster. >> Yeah, Pete, talk about that partnership. what does that look like? I mean, are you working with Dell before the T six comes out? Or you just say what would be cool is we'll put this in the T six? >> No, we've had a very long partnership both on the hardware and the software side. Dell's been an early adopter of our silicon. We've worked very closely on SI and Sonic on the operating system, and they provide very valuable feedback for us on our roadmap. So before we put out a new chip, and we have actually three different product lines within the switching group, within Broadcom, we've then gotten very valuable feedback on the hardware and on the APIs, on the operating system that goes on top of those chips. So that way when it comes to market, Dell can take it and deliver the exact features that they have in the current generation to their customers to have that continuity. And also they give us feedback on the next gen features they'd like to see again, in both the hardware and the software. >> So I'm fascinated by... I always like to know like what, yeah, exactly. Look, you start talking about the largest supercomputers, most powerful supercomputers that exist today, and you start looking at the specs and there might be two million CPUs, 2 million CPU cores. Exoflap of performance. What are the outward limits of T five in switches, building out a fabric, what does that look like? What are the increments in terms of how many... And I know it's a depends answer, but how many nodes can you support in a scale out cluster before you need another switch? Or what does that increment of scale look like today? >> Yeah, so this is 51.2 terabytes per second. Where we see the most common implementation based on this would be with 400 gig Ethernet ports. >> David: Okay. >> So that would be 128, 400 gig E ports connected to one chip. Now, if you went to 200 gig, which is kind of the state of the art for the nicks, you can have double that. So in a single hop, you can have 256 end nodes connected through one switch. >> Okay, so this T five, that thing right there, (all laughing) inside a sheet metal box, obviously you've got a bunch of ports coming out of that. So what's the form factor look like for where that T five sits? Is there just one in a chassis or you have.. What does that look like? >> It tends to be pizza boxes these days. What you've seen overall is that the industry's moved away from chassis for these high end systems more towardS pizza boxes. And you can have composable systems where, in the past you would have line cards, either the fabric cards that the line cards are plug into or interfaced to. These days what tends to happen is you'd have a pizza box and if you wanted to build up like a virtual chassis, what you would do is use one of those pizza boxes as the fabric card, one of them as the line card. >> David: Okay. >> So what we see, the most common form factor for this is they tend to be two, I'd say for North America, most common would be a 2RU, with 64 OSFP ports. And often each of those OSFP, which is an 800 gig E or 800 gig port, we've broken out into two 400 gig ports. >> So yeah, in 2RU, and this is all air cooled, in 2RU, you've got 51.2 T. We do see some cases where customers would like to have different optics and they'll actually deploy 4RU, just so that way they have the phase-space density. So they can plug in 128, say QSFP 112. But yeah, it really depends on which optics, if you want to have DAK connectivity combined with optics. But those are the two most common form factors. >> And Armando, Ethernet isn't necessarily Ethernet in the sense that many protocols can be run over it. >> Right. >> I think I have a projector at home that's actually using Ethernet physical connections. But, so what are we talking about here in terms of the actual protocol that's running over this? Is this exactly the same as what you think of as data center Ethernet, or is this RDMA over converged Ethernet? What Are we talking about? >> Yeah, so RDMA, right? So when you look at running, essentially HPC workloads, you have the NPI protocol, so message passing interface, right? And so what you need to do is you may need to make sure that that NPI message passing interface runs efficiently on Ethernet. And so this is why we want to test and validate all these different things to make sure that that protocol runs really, really fast on Ethernet. If you look at NPIs officially, built to, hey, it was designed to run on InfiniBand but now what you see with Broadcom, with the great work they're doing, now we can make that work on Ethernet and get same performance, so that's huge for customers. >> Both of you get to see a lot of different types of customers. I kind of feel like you're a little bit of a looking into the crystal ball type because you essentially get to see the future knowing what people are trying to achieve moving forward. Talk to us about the future of Ethernet in HPC in terms of AI and ML, where do you think we're going to be next year or 10 years from now? >> You want to go first or you want me to go first? >> I can start, yeah. >> Savannah: Pete feels ready. >> So I mean, what I see, I mean, Ethernet, what we've seen is that as far as on, starting off of the switch side, is that we've consistently doubled the bandwidth every 18 to 24 months. >> That's impressive. >> Pete: Yeah. >> Nicely done, casual, humble brag there. That was great, I love that. I'm here for you. >> I mean, I think that's one of the benefits of Ethernet, is the ecosystem, is the trajectory the roadmap we've had, I mean, you don't see that in any of the networking technology. >> David: More who? (all laughing) >> So I see that, that trajectory is going to continue as far as the switches doubling in bandwidth, I think that they're evolving protocols, especially again, as you're moving away from academia into the enterprise, into cloud data centers, you need to have a combination of protocols. So you'll probably focus still on RDMA, for the supercomputing, the AI/ML workloads. But we do see that as you have a mix of the applications running on these end nodes, maybe they're interfacing to the CPUs for some processing, you might use a different mix of protocols. So I'd say it's going to be doubling a bandwidth over time, evolution of the protocols. I mean, I expect that Rocky is probably going to evolve over time depending on the AI/ML and the HPC workloads. I think also there's a big change coming as far as the physical connectivity within the data center. Like one thing we've been focusing on is co-packed optics. So right now, this chip is, all the balls in the back here, there's electrical connections. >> How many are there, by the way? 9,000 plus on the back of that-- >> 9,352. >> I love how specific it is. It's brilliant. >> Yeah, so right now, all the SERDES, all the signals are coming out electrically based, but we've actually shown, we actually we have a version of Tomahawk 4 at 25.6 T that has co-packed optics. So instead of having electrical output, you actually have optics directly out of the package. And if you look at, we'll have a version of Tomahawk 5. >> Nice. >> Where it's actually even a smaller form factor than this, where instead of having the electrical output from the bottom, you actually have fibers that plug directly into the sides. >> Wow. Cool. >> So I see there's the bandwidth, there's radix's increasing, protocols, different physical connectivity. So I think there's a lot of things throughout, and the protocol stack's also evolving. So a lot of excitement, a lot of new technology coming to bear. >> Okay, You just threw a carrot down the rabbit hole. I'm only going to chase this one, okay? >> Peter: All right. >> So I think of individual discreet physical connections to the back of those balls. >> Yeah. >> So if there's 9,000, fill in the blank, that's how many connections there are. How do you do that many optical connections? What's the mapping there? What does that look like? >> So what we've announced for Tomahawk 5 is it would have FR4 optics coming out. So you'd actually have 512 fiber pairs coming out. So basically on all four sides, you'd have these fiber ribbons that come in and connect. There's actually fibers coming out of the sides there. We wind up having, actually, I think in this case, we would actually have 512 channels and it would wind up being on 128 actual fiber pairs because-- >> It's miraculous, essentially. >> Savannah: I know. >> Yeah. So a lot of people are going to be looking at this and thinking in terms of InfiniBand versus Ethernet, I think you've highlighted some of the benefits of specifically running Ethernet moving forward as HPC which sort of just trails slightly behind super computing as we define it, becomes more pervasive AI/ML. What are some of the other things that maybe people might not immediately think about when they think about the advantages of running Ethernet in that environment? Is it about connecting the HPC part of their business into the rest of it? What are the advantages? >> Yeah, I mean, that's a big thing. I think, and one of the biggest things that Ethernet has again, is that the data centers, the networks within enterprises, within clouds right now are run on Ethernet. So now, if you want to add services for your customers, the easiest thing for you to do is the drop in clusters that are connected with the same networking technology. So I think one of the biggest things there is that if you look at what's happening with some of the other proprietary technologies, I mean, in some cases they'll have two different types of networking technologies before they interface to Ethernet. So now you've got to train your technicians, you train your assist admins on two different network technologies. You need to have all the debug technology, all the interconnect for that. So here, the easiest thing is you can use Ethernet, it's going to give you the same performance and actually, in some cases, we've seen better performance than we've seen with Omni-Path, better than in InfiniBand. >> That's awesome. Armando, we didn't get to you, so I want to make sure we get your future hot take. Where do you see the future of Ethernet here in HPC? >> Well, Pete hit on a big thing is bandwidth, right? So when you look at, train a model, okay? So when you go and train a model in AI, you need to have a lot of data in order to train that model, right? So what you do is essentially, you build a model, you choose whatever neural network you want to utilize. But if you don't have a good data set that's trained over that model, you can't essentially train the model. So if you have bandwidth, you want big pipes because you have to move that data set from the storage to the CPU. And essentially, if you're going to do it maybe on CPU only, but if you do it on accelerators, well, guess what? You need a big pipe in order to get all that data through. And here's the deal, the bigger the pipe you have, the more data, the faster you can train that model. So the faster you can train that model, guess what? The faster you get to some new insight, maybe it's a new competitive advantage, maybe it's some new way you design a product, but that's a benefit of speed, you want faster, faster, faster. >> It's all about making it faster and easier-- for the users. >> Armando: It is. >> I love that. Last question for you, Pete, just because you've said Tomahawk seven times, and I'm thinking we're in Texas, stakes, there's a lot going on with that. >> Making me hungry. >> I know, exactly. I'm sitting out here thinking, man, I did not have big enough breakfast. How did you come up with the name Tomahawk? >> So Tomahawk, I think it just came from a list. So we have a tried end product line. >> Savannah: Ah, yes. >> Which is a missile product line. And Tomahawk is being kind of like the bigger and batter missile, so. >> Savannah: Love this. Yeah, I mean-- >> So do you like your engineers? You get to name it. >> Had to ask. >> It's collaborative. >> Okay. >> We want to make sure everyone's in sync with it. >> So just it's not the Aquaman tried. >> Right. >> It's the steak Tomahawk. I think we're good now. >> Now that we've cleared that-- >> Now we've cleared that up. >> Armando, Pete, it was really nice to have both you. Thank you for teaching us about the future of Ethernet and HCP. David Nicholson, always a pleasure to share the stage with you. And thank you all for tuning in to theCUBE live from Dallas. We're here talking all things HPC and supercomputing all day long. We hope you'll continue to tune in. My name's Savannah Peterson, thanks for joining us. (soft music)

>>You can put this in a conference. >>Good morning and welcome back to Dallas. Ladies and gentlemen, we are here with the cube Live from, from Supercomputing 2022. David, my cohost, how you doing? Exciting. Day two. Feeling good. >>Very exciting. Ready to start off the >>Day. Very excited. We have two fascinating guests joining us to kick us off. Please welcome Pete and Armando. Gentlemen, thank you for being here with us. >>Having us, >>For having us. I'm excited that you're starting off the day because we've been hearing a lot of rumors about ethernet as the fabric for hpc, but we really haven't done a deep dive yet during the show. Y'all seem all in on ethernet. Tell us about that. Armando, why don't you start? >>Yeah. I mean, when you look at ethernet, customers are asking for flexibility and choice. So when you look at HPC and you know, infinite band's always been around, right? But when you look at where Ethernet's coming in, it's really our commercial and their enterprise customers. And not everybody wants to be in the top 500. What they want to do is improve their job time and improve their latency over the network. And when you look at ethernet, you kinda look at the sweet spot between 8, 12, 16, 32 nodes. That's a perfect fit for ethernet and that space and, and those types of jobs. >>I love that. Pete, you wanna elaborate? Yeah, yeah, >>Yeah, sure. I mean, I think, you know, one of the biggest things you find with internet for HPC is that, you know, if you look at where the different technologies have gone over time, you know, you've had old technologies like, you know, atm, Sonic, fitty, you know, and pretty much everything is now kind of converged toward ethernet. I mean, there's still some technologies such as, you know, InfiniBand, omnipath that are out there. Yeah. But basically there's single source at this point. So, you know, what you see is that there is a huge ecosystem behind ethernet. And you see that also, the fact that ethernet is used in the rest of the enterprise is using the cloud data centers that is very easy to integrate HPC based systems into those systems. So as you move HPC out of academia, you know, into, you know, into enterprise, into cloud service providers is much easier to integrate it with the same technology you're already using in those data centers, in those networks. >>So, so what's this, what is, what's the state of the art for ethernet right now? What, you know, what's, what's the leading edge, what's shipping now and what and what's in the near future? You, you were with Broadcom, you guys design this stuff. >>Yeah, yeah. Right. Yeah. So leading edge right now, I got a couple, you know, Wes stage >>Trough here on the cube. Yeah. >>So this is Tomahawk four. So this is what is in production is shipping in large data centers worldwide. We started sampling this in 2019, started going into data centers in 2020. And this is 25.6 tets per second. Okay. Which matches any other technology out there. Like if you look at say, infin band, highest they have right now that's just starting to get into production is 25 point sixt. So state of the art right now is what we introduced. We announced this in August. This is Tomahawk five. So this is 51.2 terabytes per second. So double the bandwidth have, you know, any other technology that's out there. And the important thing about networking technology is when you double the bandwidth, you don't just double the efficiency, it's actually winds up being a factor of six efficiency. Wow. Cause if you want, I can go into that, but why >>Not? Well, I, what I wanna know, please tell me that in your labs you have a poster on the wall that says T five with, with some like Terminator kind of character. Cause that would be cool if it's not true. Don't just don't say anything. I just want, I can actually shift visual >>It into a terminator. So. >>Well, but so what, what are the, what are the, so this is, this is from a switching perspective. Yeah. When we talk about the end nodes, when we talk about creating a fabric, what, what's, what's the latest in terms of, well, the kns that are, that are going in there, what's, what speed are we talking about today? >>So as far as 30 speeds, it tends to be 50 gigabits per second. Okay. Moving to a hundred gig pan four. Okay. And we do see a lot of Knicks in the 200 gig ethernet port speed. So that would be, you know, four lanes, 50 gig. But we do see that advancing to 400 gig fairly soon. 800 gig in the future. But say state of the art right now, we're seeing for the end nodes tends to be 200 gig E based on 50 gig pan four. Wow. >>Yeah. That's crazy. Yeah, >>That is, that is great. My mind is act actively blown. I wanna circle back to something that you brought up a second ago, which I think is really astute. When you talked about HPC moving from academia into enterprise, you're both seeing this happen. Where do you think we are on the adoption curve and sort of in that cycle? Armand, do you wanna go? >>Yeah, yeah. Well, if you look at the market research, they're actually telling it's 50 50 now. So ethernet is at the level of 50%. InfiniBand is at 50%. Right. Interesting. Yeah. And so what's interesting to us, customers are coming to us and say, Hey, we want to see, you know, flexibility and choice and hey, let's look at ethernet and let's look at InfiniBand. But what is interesting about this is that we're working with Broadcom, we have their chips in our lab, we have our switches in our lab. And really what we're trying to do is make it easy to simple and configure the network for essentially mpi. And so the goal here with our validated designs is really to simplify this. So if you have a customer that, Hey, I've been in fbe, but now I want to go ethernet, you know, there's gonna be some learning curves there. And so what we wanna do is really simplify that so that we can make it easy to install, get the cluster up and running, and they can actually get some value out of the cluster. >>Yeah. Peter, what, talk about that partnership. What, what, what does that look like? Is it, is it, I mean, are you, you working with Dell before the, you know, before the T six comes out? Or you just say, you know, what would be cool, what would be cool is we'll put this in the T six? >>No, we've had a very long partnership both on the hardware and the software side. You know, Dell has been an early adopter of our silicon. We've worked very closely on SI and Sonic on the operating system, you know, and they provide very valuable feedback for us on our roadmap. So before we put out a new chip, and we have actually three different product lines within the switching group within Broadcom, we've then gotten, you know, very valuable feedback on the hardware and on the APIs, on the operating system that goes on top of those chips. So that way when it comes to market, you know, Dell can take it and, you know, deliver the exact features that they have in the current generation to their customers to have that continuity. And also they give us feedback on the next gen features they'd like to see again in both the hardware and the software. >>So, so I, I'm, I'm just, I'm fascinated by, I I, I always like to know kind like what Yeah, exactly. Exactly right. Look, you, you start talking about the largest super supercomputers, most powerful supercomputers that exist today, and you start looking at the specs and there might be 2 million CPUs, 2 million CPU cores, yeah. Ex alop of, of, of, of performance. What are the, what are the outward limits of T five in switches, building out a fabric, what does that look like? What are the, what are the increments in terms of how many, and I know it, I know it's a depends answer, but, but, but how many nodes can you support in a, in a, in a scale out cluster before you need another switch? What does that increment of scale look like today? >>Yeah, so I think, so this is 51.2 terras per second. What we see the most common implementation based on this would be with 400 gig ethernet ports. Okay. So that would be 128, you know, 400 giggi ports connected to, to one chip. Okay. Now, if you went to 200 gig, which is kind of the state of the art for the Nicks, you can have double that. Okay. So, you know, in a single hop you can have 256 end nodes connected through one switch. >>So, okay, so this T five, that thing right there inside a sheet metal box, obviously you've got a bunch of ports coming out of that. So what is, what does that, what's the form factor look like for that, for where that T five sits? Is there just one in a chassis or you have, what does that look >>Like? It tends to be pizza boxes these days. Okay. What you've seen overall is that the industry's moved away from chassis for these high end systems more towards pizza, pizza boxes. And you can have composable systems where, you know, in the past you would have line cards, either the fabric cards that the line cards are plugged into or interface to these days, what tends to happen is you'd have a pizza box, and if you wanted to build up like a virtual chassis, what you would do is use one of those pizza boxes as the fabric card, one of them as the, the line card. >>Okay. >>So what we see, the most common form factor for this is they tend to be two, I'd say for North America, most common would be a two R U with 64 OSF P ports. And often each of those OSF p, which is an 800 gig e or 800 gig port, we've broken out into two 400 gig quarts. Okay. So yeah, in two r u you've got, and this is all air cooled, you know, in two re you've got 51.2 T. We do see some cases where customers would like to have different optics, and they'll actually deploy a four U just so that way they have the face place density, so they can plug in 128, say qsf P one 12. But yeah, it really depends on which optics, if you wanna have DAK connectivity combined with, with optics. But those are the two most common form factors. >>And, and Armando ethernet isn't, ethernet isn't necessarily ethernet in the sense that many protocols can be run over it. Right. I think I have a projector at home that's actually using ethernet physical connections. But what, so what are we talking about here in terms of the actual protocol that's running over this? Is this exactly the same as what you think of as data center ethernet, or, or is this, you know, RDMA over converged ethernet? What, what are >>We talking about? Yeah, so our rdma, right? So when you look at, you know, running, you know, essentially HPC workloads, you have the NPI protocol, so message passing interface, right? And so what you need to do is you may need to make sure that that NPI message passing interface runs efficiently on ethernet. And so this is why we want to test and validate all these different things to make sure that that protocol runs really, really fast on ethernet, if you look at NPI is officially, you know, built to, Hey, it was designed to run on InfiniBand, but now what you see with Broadcom and the great work they're doing now, we can make that work on ethernet and get, you know, it's same performance. So that's huge for customers. >>Both of you get to see a lot of different types of customers. I kind of feel like you're a little bit of a, a looking into the crystal ball type because you essentially get to see the future knowing what people are trying to achieve moving forward. Talk to us about the future of ethernet in hpc in terms of AI and ml. Where, where do you think we're gonna be next year or 10 years from now? >>You wanna go first or you want me to go first? I can start. >>Yeah. Pete feels ready. >>So I mean, what I see, I mean, ethernet, I mean, is what we've seen is that as far as on the starting off of the switch side, is that we've consistently doubled the bandwidth every 18 to 24 months. That's >>Impressive. >>Yeah. So nicely >>Done, casual, humble brag there. That was great. That was great. I love that. >>I'm here for you. I mean, I think that's one of the benefits of, of Ethan is like, is the ecosystem, is the trajectory, the roadmap we've had, I mean, you don't see that in any other networking technology >>More who, >>So, you know, I see that, you know, that trajectory is gonna continue as far as the switches, you know, doubling in bandwidth. I think that, you know, they're evolving protocols. You know, especially again, as you're moving away from academia into the enterprise, into cloud data centers, you need to have a combination of protocols. So you'll probably focus still on rdma, you know, for the supercomputing, the a AIML workloads. But we do see that, you know, as you have, you know, a mix of the applications running on these end nodes, maybe they're interfacing to the, the CPUs for some processing, you might use a different mix of protocols. So I'd say it's gonna be doubling a bandwidth over time evolution of the protocols. I mean, I expect that Rocky is probably gonna evolve over time depending on the a AIML and the HPC workloads. I think also there's a big change coming as far as the physical connectivity within the data center. Like one thing we've been focusing on is co-pack optics. So, you know, right now this chip is all, all the balls in the back here, there's electrical connections. How >>Many are there, by the way? 9,000 plus on the back of that >>352. >>I love how specific it is. It's brilliant. >>Yeah. So we get, so right now, you know, all the thirties, all the signals are coming out electrically based, but we've actually shown, we have this, actually, we have a version of Hawk four at 25 point sixt that has co-pack optics. So instead of having electrical output, you actually have optics directly out of the package. And if you look at, we'll have a version of Tomahawk five Nice. Where it's actually even a smaller form factor than this, where instead of having the electrical output from the bottom, you actually have fibers that plug directly into the sides. Wow. Cool. So I see, you know, there's, you know, the bandwidth, there's radis increasing protocols, different physical connectivity. So I think there's, you know, a lot of things throughout, and the protocol stack's also evolving. So, you know, a lot of excitement, a lot of new technology coming to bear. >>Okay. You just threw a carrot down the rabbit hole. I'm only gonna chase this one. Okay. >>All right. >>So I think of, I think of individual discreet physical connections to the back of those balls. Yeah. So if there's 9,000, fill in the blank, that's how many connections there are. How do you do that in many optical connections? What's, what's, what's the mapping there? What does that, what does that look like? >>So what we've announced for TAMA five is it would have fr four optics coming out. So you'd actually have, you know, 512 fiber pairs coming out. So you'd have, you know, basically on all four sides, you'd have these fiber ribbons that come in and connect. There's actually fibers coming out of the, the sides there. We wind up having, actually, I think in this case, we would actually have 512 channels and it would wind up being on 128 actual fiber pairs because >>It's, it's miraculous, essentially. It's, I know. Yeah, yeah, yeah, yeah. Yeah. So, so, you know, a lot of people are gonna be looking at this and thinking in terms of InfiniBand versus versus ethernet. I think you've highlighted some of the benefits of specifically running ethernet moving forward as, as hpc, you know, which is sort of just trails slightly behind supercomputing as we define it, becomes more pervasive AI ml. What, what are some of the other things that maybe people might not immediately think about when they think about the advantages of running ethernet in that environment? Is it, is it connecting, is it about connecting the HPC part of their business into the rest of it? What, or what, what are the advantages? >>Yeah, I mean, that's a big thing. I think, and one of the biggest things that ethernet has again, is that, you know, the data centers, you know, the networks within enterprises within, you know, clouds right now are run on ethernet. So now if you want to add services for your customers, the easiest thing for you to do is, you know, the drop in clusters that are connected with the same networking technology, you know, so I think what, you know, one of the biggest things there is that if you look at what's happening with some of the other proprietary technologies, I mean, in some cases they'll have two different types of networking technologies before they interface to ethernet. So now you've got to train your technicians, you train your, your assist admins on two different network technologies. You need to have all the, the debug technology, all the interconnect for that. So here, the easiest thing is you can use ethernet, it's gonna give you the same performance. And actually in some cases we seen better performance than we've seen with omnipath than, you know, better than in InfiniBand. >>That's awesome. Armando, we didn't get to you, so I wanna make sure we get your future hot take. Where do you see the future of ethernet here in hpc? >>Well, Pete hit on a big thing is bandwidth, right? So when you look at train a model, okay, so when you go and train a model in ai, you need to have a lot of data in order to train that model, right? So what you do is essentially you build a model, you choose whatever neural network you wanna utilize, but if you don't have a good data set that's trained over that model, you can't essentially train the model. So if you have bandwidth, you want big pipes because you have to move that data set from the storage to the cpu. And essentially, if you're gonna do it maybe on CPU only, but if you do it on accelerators, well guess what? You need a big pipe in order to get all that data through. And here's the deal. The bigger the pipe you have, the more data, the faster you can train that model. So the faster you can train that model, guess what? The faster you get to some new insight, maybe it's a new competitive advantage. Maybe it's some new way you design a product, but that's a benefit of speed you want faster, faster, faster. >>It's all about making it faster and easier. It is for, for the users. I love that. Last question for you, Pete, just because you've said Tomahawk seven times, and I'm thinking we're in Texas Stakes, there's a lot going on with with that making >>Me hungry. >>I know exactly. I'm sitting up here thinking, man, I did not have a big enough breakfast. How do you come up with the name Tomahawk? >>So Tomahawk, I think you just came, came from a list. So we had, we have a tri end product line. Ah, a missile product line. And Tomahawk is being kinda like, you know, the bigger and batter missile, so, oh, okay. >>Love this. Yeah, I, well, I >>Mean, so you let your engineers, you get to name it >>Had to ask. It's >>Collaborative. Oh good. I wanna make sure everyone's in sync with it. >>So just so we, it's not the Aquaman tried. Right, >>Right. >>The steak Tomahawk. I >>Think we're, we're good now. Now that we've cleared that up. Now we've cleared >>That up. >>Armando P, it was really nice to have both you. Thank you for teaching us about the future of ethernet N hpc. David Nicholson, always a pleasure to share the stage with you. And thank you all for tuning in to the Cube Live from Dallas. We're here talking all things HPC and Supercomputing all day long. We hope you'll continue to tune in. My name's Savannah Peterson, thanks for joining us.

>>Okay. We're back in Boston covering AWS reinvent 2022. This is our second live reinvent. We've done the other ones, uh, in between as digital. Uh, my name is Dave Lanta and you're watching the cube. Peter McKay is here. He's the CEO of sneaking ad Shani is the chief technical officer guys. Great to see you again. Awesome. Being here in Boston >>In July. It is Peter. You can't be weather's good weather. Yeah, red SOS. Aren't good. But everything else >>Is SOS are ruin in our sub, you know, >>Hey, they're still in the playoff, the hunt, you >>Know, all you gotta do is make it in. Yes. >>Right. And there's a new season. Simple >>Kinda like hockey, but you know, I'm worried they're gonna be selling at the trading >>Deadline. Yeah. I think they should be. I think it's you think so it's not looking good. Oh, >>You usually have a good angle on this stuff, but uh, well, Hey, we'll see. We'll go. I got a lot of tickets. We'll go and see the Yankees at least we'll see a winning team. Anyway, we last talked, uh, after your fundraising. Yeah. You know, big, big round at your event last night, a lot of buzz, one of the largest, I think the largest event I saw around here, a lot of good customers there. >>It's great. Great time. >>So what's new. Give us the update. You guys have made some, an acquisition since then. Integration. We're gonna talk >>About that. Yeah. It's been, uh, a lot has happened. So, uh, the business itself has done extremely well. We've been growing at 170% year, over year, a hundred percent growth in our number of customers added. We've done six acquisitions. So now we have, uh, five products that we've added to the mix. We've tripled the size of the company. Now we're 1300 people, uh, in the organization. So quite a bit in a very short period of time. >>Well, and of course my, in my intro, I, I said, reinvent, I'm getting ahead of myself. Right. >>Of course we'll >>Reinforced. We'll be at reinve >>In November. Are that's the next one at >>Reinforced. We've done a lot of reinvents by the way, you know? >>So there's a lot, lot of reinvention >>Here. So of course, well, you're reinventing security, right? Yes. So, you know, I try to, I think about when I go to these events, like, what's the takeaway, what's the epiphany. And we're really seeing the, the developer security momentum, and it's a challenge. They gotta worry about containers. They gotta worry about run time. They gotta worry about platform. Yeah. You guys are attacking that problem. Maybe describe that a >>Little bit for us. Yeah. I mean, for years it was always, um, you know, after the fact production fixing security in run time and billions and billions of dollars spent in fixing after the fact. Right. And so the realization early on with the was, you know, you gotta fix these issues earlier and earlier, we started with open source was the first product at wait. Then six, six years ago, then we added container security and we added infrastructure's code. We added code security. We added, um, most recently cloud security with the F acquisition. So one platform, one view that a developer can look at to fix all the issues through the, be from the beginning, all the way through the software development life cycle. So we call it developer security. So allowing developers to develop fast, but stay secure at the same time. >>So I like the fact that you're using some of your capital to do acquisitions. Yeah. Now a lot of M and a is, okay, we're gonna buy this company. We're gonna leave them alone. You guys chose to integrate them. Maybe describe what that process was like. Yeah. Why you chose that. Yeah. How hard it was, how long it took. Take us through that. >>Yeah. Yeah. I'll give, uh, two examples, maybe one on sneak, which was an acquisition of, of the company that was focused on, uh, code analysis, actually not for security. And we have identified the merit of what we need in terms of the first security solution, not an ability to take a security product and put it in the end of developer, but rather build something that will build into the dev motion, which means very fast, very accurate things that it can rely on source and not just on the build code and so on. And we have built that into the platform and by that our customers can gain all of their code related issues together with all of their ISE related issues together with all of the container issues in one platform that they can prioritize accordingly. >>Yeah. Okay. So, so talk more about the, the, the call, the few, the sneak cloud, right? Yeah. So the few name goes away. I presume, right. Or yes, it does. Okay. So you retire that and bring it in the brand is sneak. Yeah. Right. So talk about the cloud, what it does, what problems >>It's solving. Yeah. Awesome. And, and this goes exactly the same. As we mentioned on, on the code, we have looked at the, the, the cloud security solutions for a while now. And what we loved about the few team is that they were building their product with their first approach. Okay. So the notion is as followed as you are, you know, you're a CSO, you have your pro you have your program, you're looking, you have different types of controls and capabilities. And your team is constantly looking for threats. When we are monitoring your cloud environment, we can detect problems like, you know, your FL bucket is not exposing the right permissions and is exposed to the world or things like that. But from a security perspective, it might be okay to stop there. But if you're looking at an operation perspective, you need to know who needs to fix, how do they need to fix it? >>Where do they need to fix it? What will the be the impact if they would fix it? So what do we actually doing is we are connecting all the dots of the platform. So on one end, you know, the actual resources that are running and what's the implication in the actual deployed environment. On the other end, we get correlation back to the actual code that generates that. And then I can give that context both to the security person, the context of how it affects the application. But more importantly, the context for the developer is required to fix the problem. What's the context of the cloud. Yeah. And a lot of things are being exposed this way. And we can talk about that. Uh, >>So this is really interesting because, and look, I love AWS to do an amazing job. One of the other things I really like about 'em is it seems like they're not trying to go hard and monetize their security products. Mm-hmm, they're leaving that to the ecosystem, which I like. Yeah. Microsoft taken a little different approach, right? Yeah, yeah, yeah. Ton a lot. But this, this, this example you're giving ad about the S3 bucket. So we heard in the keynotes yesterday about, you know, reasoning, AI reasoning, they said, we can say, is this S3 bucket exposed to the public? We can do that with math. Right. Yeah. But you're what I'm inferring is you don't stop there. Yeah. Yeah. There's a lot of other stuff that has to, >>And sometimes have to, not as simple, just as a configuration change, sometimes the correlation between what your application is doing affects what is the resulted experience of, you know, the remote user or in this case, the attacker, right. I mean, >>The application has access, who has access to the application, is this, this the chain. >>So propagates, you have to, you have to have a, a solution that looks both at have very good understanding of the application context. A very good understanding of what we refer to as the application graph, like understanding how it works, being able to analyze that and apply the same policies, both at development time, as well as run time. >>So there's, there's human to app. There's also a machine to machine. Can you guys help with that problem as well? Or is that sort of a futures thing or >>Could you, I'm not sure. I understand what >>Referring, so machines talking to machines, right. I mean, there's data flowing. Yep. You know, between those machines, right. It's not just the humans interacting with the application. Is that a trend that you see and is that something that you guys can solve? >>So at, at the end of the day, there is a lot of automation that happens both for, by humans for good reasons, as well as by humans for bads. Right. <laugh> and, and the notion is that we are really trying to focus on what matters to the developer as they're trying to improve their business around that. So both improves making sure they know, you know, quality problems or things of this kind. But as part of that, more importantly, when we're looking at security as a quality problem, making sure that we have a flow in the development life cycle that streamline what the developer is expecting to do as they're building the solution. And if every single point, whether it's the ID, whether it's the change management, whether it's the actual build, whether it's the deployed instance on the cloud, making sure that we identify with that and connect that back to the code. >>Okay. So if there's machine automation coming in, that shouldn't be there, you can sort of identify that and then notify remediate or whatever action should be >>Taken. Yeah. Identify, identify remediate. Yep. >>Yeah. We, we really focus on making sure that we help developers build better products. So our core focus is identify areas where the product is not built way in a good way, and then suggest the corrective action that is required to make that happen. >>And I think part of this is the, you know, just, uh, the speed of the software development today. I mean, you look at developers are constantly and not just look at sneak you're, you're trying to get so much more productivity outta the developers that you have. Every company is trying to get more productivity out of developers, incredible innovation, incredible pace, get those is a competitive advantage. And so what we're trying to do is we make it easier for developers to go fast innovate, but also do it securely and embed it without slowing them down, develop fast and secure. >>So again, I love, I love AWS love what they're doing. We heard, uh, yesterday from, from CJ, you know, a lot of talk about, you know, threat detection and, you know, some talk about DevOps, et cetera. But yeah, I, I, I didn't hear a lot about how to reduce the complexity for the CSO. And the reason I bring this up is it feels like the cloud is now the first level of defense and the CISO is, is becoming the next level, which is on the developer. So the developer is becoming responsible for security at a whole shift left, maybe shield. Right. But, but shift left is becoming critical. Seems like your role and maybe others in the ecosystem is to address my concern about simplifying the life of the CISO. Is that a reasonable way to think about it? I >>Think it's changing the role of the CISO. How so? You know, really it's, I, I think it's before it, in this, in the security organization and D you should chime in here is, you know, it used to be, I did, I owned all application security, I owned the whole thing and they couldn't keep up. Like, I think it's just every security organization is totally overwhelmed. And so they have to share the responsibility. They have to get that fix the issues earlier and earlier, because it's waiting too long. It's after the fact. And then you gotta throw this over the fence and developers have to fix it. So they've gotta find a new way because they're the bottleneck they're slowing down the company from, in innovating and bringing these applications to market. So we are the kind of this bridge between the security teams that wanna make sure the, that we're staying secure and the development organizations and engineering and CEOs go fast. We need you guys to go faster and faster. So we, we tend to be the bridge between the two of them. >>One of the things I really love happening these days is that we change the culture of the organization from a culture where the CSO is trying to, you know, push and enforce and dictate the policy, which, which they should, but they really wanna see the development team speak up like that. The whole motion of DevOps is that we are empowering them to make the decisions that are right for the business, right? And then there is a gap because on one hand, this is always like, you need to do this, you need to do this. You need to do that. And the dev teams don't understand how that impacts their business. Good enough. And they don't have the tools and, you know, the ability to add a source problem. So with the solution liken, we really empower the developers to bake security as part of their cycle, which is what was done in many other fields, quality, other things, everything, it, everything moves into development already, right? So we're doing that. And the entire discussion now changes into an enablement discussion. >>So interesting. Cause you saw, this is the role of the CSOs changing. How so? I see that in a way like frees, sneak the CSO with the cloud is becoming a compliance officer. Like you do this, you do this, you do this, you do this, you third >>One would take a responsibility >>Trying. Yeah. Right, right. And so you're flipping that equation saying, Hey, we're gonna actually make this an accelerant to your business. >>So, so set the policy, determine compliance, but make sure that the teams, the developers are building applications in compliance with your policy. Right. So make sure and, and don't allow them to do something. If they're doing, if they're developing an application with a number of vulnerabilities, you can stop that from happening so you can oversee it, but you don't have to be the one who owns it all the way through from beginning to, >>Or, or get it before it's deployed. So you don't have to go back after the fact and, and remediate it with, you know, but, >>But think about deploy, they're deploying apps today. I mean, they're updating by the hour, right? Where, you know, six years ago, five years ago, two years ago was every six to nine months. Right? So the pace of this innovation from developers is so fast that the old way of doing security can't keep up. Like they're built for six month release cycles. This is six hour release cycles. And so we had to, it has to change security. Can't stay the way it is. So what we've been doing for se seven years for application security is exactly what we're doing for cloud security is moving all that earlier. All these products that we've been building over the years is really taking these afterthought security components and bringing 'em all earlier, you know, bringing everything like cloud security is done after the fact. Now we can take those issues and bring 'em right to the developers who created that and can fix the issues. So it's code to cloud back to code in a very automated fashion. So doesn't slow developers down. >>Okay. So what's the experience. We all know there's, everybody has more than one cloud. What's the experience across clouds. Can you create a consistent, continuous experience, cloud agnostic, >>Agnostic, cloud agnostic, uh, development environment, agnostic, you know, language agnostic. So that's kind of the beauty oft where you have maybe other certain tools for certain clouds, uh, or certain languages or certain development environments, but you have to learn different tools, you know, and, and they all roll up to security in a different way. And so what we have done is consolidated all that spend for open source security, container security infrastructure, now, cloud security, all that spend and all that fragmentation all under one platform. So it's one company that brings all those pieces >>Together. So it's a single continuous experience. Yeah. The developer experience you're saying is identical. Yes. >>Actually one product >>It's entitlement that we're getting. Yes. So you're hiding the underlying complexities of the respective clouds and those primitives developer doesn't have to worry about them. No, I call that a super cloud super >>Cloud. >>Okay. But no, but essentially that's what you're, you're building, building on the, on this ed Walsh would say on the shoulders of giants. Yeah, exactly. You know, you don't have to worry about the hyperscale infrastructure. Yep. Right. That you're building a layer of value on top of that. Yes. Is, is that essentially a PAs layer or is it, is it, can I think of it that way or is it not? Hmm. Is it platform? I >>Mean, yeah. I, I, I would say that at the end of the day, the, the way developers want to use a security tool is the same. Right. So we expose our functionality to them in those ways, if you're using, you know, uh, uh, one GI repository or another, if you're using one cloud or we, we are agnostic to data, don't, it's not, it doesn't really affect us in that manner. Um, I want to add another thing about the, the experience and associated with the consolidation that Peter referred to, uh, earlier, when you have a motion that automatically assess, you know, uh, problems that the developer is putting as part of the change management, as example, you do creating pool request. Now adding more capabilities into that motion is easy. So from enablement of the team, you can add another functionality, add cloud at ISC, add code and so on like that, because you already, you already made the decisions on how you are looking at that. And now you're integrated at, into your developer workflows, >>Right? So it's, it's already, it's already integrated for open source, adding container and ISD is real easy. It's all, you've already done all the integrations. And so for us going to five products and eventually 6, 7, 8, all, all based on the integrations that you already have in the same workflows that developers have become a use accustomed >>To. And that's what we, a lot of work from the company perspective. Right. >>I can ask you about another sort of trend we're seeing where you see Goldman Sachs last reinvent announced a cloud product, essentially bringing their data, their tools, their software. They're gonna run it on AWS at the snowflake summit, uh, capital one announced the service running on snowflake, Oracle by Cerner, right? Yeah. You know, they're gonna be, do something on OCI. Of course, make 'em do that. But it's, it's a spin on Andreessens every company's a software company. It's like every company's now becoming digital, a software company building their own SAS, essentially building their own clouds, or maybe, maybe something they'll be super clouds. Are you seeing industry come to sneak and say, Hey, help us build products that we can monetize >>There companies. So, first off, I think kind of the first iteration is, you know, all these industries of becoming software driven, like you said, and more software is more software risk. And so that kind of led us down this journey of now financial services, you know, tech, you know, media and entertainment, financial services, healthcare. Now it's this long tail of, of low tech. Yeah. Within those companies, they are offering services to the other parts of the organization. We have >>So far, mostly >>Internal, mostly internal, other than the global SI. And some of the companies who do that for a living, you know, they build the apps for companies and they are offering a sneak service. So before I give you these, I update these applications. I'm gonna make sure I'm running. I'm, I'm, I'm signifying those applications to make sure that they're secure before you get them. And so that now a company like a capital one coming to us saying, I wanna offer this to others. I think that's a, that's a leap because you know, companies are taking on security of someone else's and I think that's a, that's not there yet. It may be, >>Do you think it'll happen? >>We do have the, uh, uh, threat Intel that we, we have a very, a very strong security group that constantly monitors and analyzing the threat. And we create this vulnerability database. So in open sources, an example, we're the fact of standard, uh, in the field. So many of our partners are utilizing the threat Intel feed of snake as part of their offering. Okay. If you go to dock as an example, you can scan with, with snake intelligence immediately out of the gate over there, right? Yeah. >>And tenable, rapid seven trend micro. They all use the vulnerability database as well. Okay. So a lot of financial institutions use it because they had, they'd have seven, 10 people doing re security research on their own. And now they can say, well, I don't have to have those seven. I've got the industry standard for vulnerability database from Steve. >>And they don't have to throw out their existing tool sets where they have skills. >>Yes, exactly. >>Peter bring us homes, give us the bumper sticker, summarize, you know, reinforce and kind what we can expect going forward. >>Yeah, no, I mean, we're gonna continue the pace. We don't see anything slowing, slowing us down in terms of, um, just the number of customers that are, that are shifting left. Everybody's talking about, Hey, I need to embed this earlier and earlier. And I think what they're finding is this, this need to rein reinnovate like get innovation back into their business. And a lot of it had to slow down because, well, you know, you, we can't let developers develop an app without it going through security. And that takes time. It slows you down and allows you not to like slow the pace of innovation. And so for us, it's it help developers go fast, incredibly, you know, quickly, aggressively, creatively, but do it in a secure way. And I think that balance, you know, making sure that they're doing what they're doing, they're increasing developer productivity, increasing the amount of innovation that developers are trying to do, but you gotta do it securely. And that's where we compliment really what every CEO is pushing companies. I need more productivity. I need more aggressive creativity, innovation, but you better be secure at the same time. And that's what we bring together for our customers. >>And you better do that without slowing us down. That's >>Don't trade off, slow >>Us down. Always had to make. Yes, guys. Thanks so much for coming to the cube. Thanks, David. Always great to see you guys see ID. Appreciate it. All right. Keep it right there. This is the Cube's coverage of reinforced 2022 from Boston. We'll be right back right after the short break.

>>Hey everyone. Welcome back to the cube. Lisa Martin here with Dave ante, we're covering snowflake summit 22. This is Dave two of our wall to wall cube coverage of three days. We've been talking with a lot of customers partners, and we've got some more partners to talk with us. Next. Informatica two of our guests are back with us on the program. Rick TA Daniels joins us the G P global ecosystems and technology at Informatica and Peter COO vice president and chief strategist banking and financial services. Welcome guys. >>Thank you guys. Thanks for having us, Peter, >>Talk to us about what some of the trends are that you're seeing in the financial services space with respect to cloud and data and AI. >>Absolutely. You know, I'd say 10 years ago, the conversation around cloud was what is that? Right? How do we actually, or no way, because there was a lot of concerns about privacy and security and so forth. You know, now, as you see organizations modernizing their business capabilities, they're investing in cloud solutions for analytics applications, as well as data data being not only just a byproduct of transactions and interactions in financial services, it truly fuels business success. But we have a term here in Informatica where data really has no value unless it's fit for business. Use data has to be accessible in the systems and applications you use to run your business. It has to be clean. It has to be valid. It has to be transparent. People need to understand where it comes from, where it's going, how it's used and who's using it. It also has to be understood by the business. >>You can have all the data in the world and your business applications, but people don't know what they need it to use it for how they should use it. It has no value as well. And then lastly, it has to be protected when it matters most what we're seeing across financial services, that with the evolution of cloud now, really being the center of focus for many of the net new investments, data is scattered everywhere, not just in one cloud environment, but in multiple cloud environments, but they're still dealing with many of the on premise systems that have been running this industry for many, many years. So organizations need to have the ability to understand what they need to do with their data. More importantly, tie that to a measurable business outcome. So we're seeing the data conversation really at the board level, right? It's an asset of the business. It's no longer just owned by it. Data governance brings both business technology and data leaders together to really understand how do we use manage, govern and really leverage data for positive business outcomes. So we see that as an imperative that cuts across all sectors of financial services, both for large firms, as well as for the mid-market so >>Quick follow up. If I, may you say it's a board level. I totally agree. Is it also a line of business level? Are you seeing increasingly that line of businesses are leaning in owning the data, be building data products and the like >>Absolutely. Because at the end of the day business needs information in order to be successful. And data ownership now really belongs in the front office. Business executives understand that data again is not just a bunch of zeros and ones. These are critical elements for them make decisions and to run their business, whether it's to improve customer experience, whether it's to grow Wallace share, whether it's to comply with regulations, manage risks in today's environment. And of course being agile business knows that data's important. They have ownership of it and technology and data organizations help facilitate that solutions. And of course the investments to ensure that business can make the decisions and take the appropriate actions. >>A lot of asks and requirements on data. That's a big challenge for organizations. You mentioned. Well, one of the things that we've mentioned many times on this program recently is every company has to be a data company. There is no more, it's not an option anymore. If you wanna be successful, how does Informatica help customers navigate all of the requirements on data for them to be able to extract that business value and create new products and services in a timely fashion? >>So Informatica announced what we call the intelligent data management cloud platform. The platform has capabilities to help organizations access the data that they need, share it across to applications that run their business, be able to identify and deal with data, quality issues and requirements. Being able to provide that transparency, the lineage that people need across multiple environments. So we've been investing in this platform that really allows our customers to take advantage of these critical data management, data governance and data privacy requirements, all in one single solution. So we're no longer out there just selling piecemeal products. The platform is the offering that we provide across all industries. >>So how has that affected the way Informatica does business over the last several years? Snowflake is relatively new. You guys have been around a long time. How has your business evolved and specifically, how are you serving the snowflake yeah. Joint customers with >>Informatica? Yeah, I think then when I've been talking with folks here at the event, there are two big areas that keep coming up. So, so data governance, data governance, data governance, right? It's such a hot topic out there. And as Peter was mentioning, data governance is a critical enabler of access to data. In fact, there is an IDC study for last year that said that, you know, 80, 84% of executives, you know, no surprise, right? They wanna have data driven outcomes, data driven organizations, but only 30% of practitioners actually use data to make decisions. There's a huge gap there. And really that's where governance comes in and creating trust around data and not only creating trust, but delivering data to and users. So that's one big trend. The other one is departmental user adoption. We're seeing a, a huge push towards agility and rapid startup of new projects, new data driven transformations that are happening at the departmental level, you know, individual contributors, that sort of thing. So Informatica, we did a made announcement yesterday with snowflake of a whole host of innovations that are really targeting those two big trend areas. >>I wanna get into the announcements, but you know, the point about governance and, and users, business users being reluctant, it's kind of chicken and egg, isn't it. If, if I don't have the governance, I'm, I'm afraid to use it. But even if I do have it, there's the architecture of my, my, my company, my, my data organization, you know, may not facilitate that. And so I'm gonna change the architect, but then it's a wild west. So it has to be governed. Isn't that a challenge that company companies >>Absolutely, and, and governance is, is a lot more than just technology, right? It's of a people process problem. And there really is a community or an ecosystem inside every organization for governance. So it's really important that when you think about deploying governance and being successful, that every stakeholder have the ability to interact with this common framework, right. They get what they need out of it. It's tailored for how they wanna work. You've got your it folks, you got your chief data officer data stewards, you have your privacy folks and you have your business users. They're all different personas. So we really focus on creating a holistic, single pane of glass view with our cloud data governance and catalog offering that that really takes all the way from the raw technical data and actually delivers data in, in a shopping cart, like experience for actual enterprise users. Right? And, and so I think that's when data governance goes from historically data, governments was seen as an impediment. It was seen as a tax, I think, but now it's really an accelerator, an enabler and driving consumption of data, which in turn for our friends here at snowflake is exactly what they're looking for. >>Talk about the news. So data loader, what does that do? >>Well, it's all in the name. We say, no, the data loader it, it's a free utility that we announced here at, at snowflake summit that allows any user to sign up. It's completely free, no capacity limits. You just need an email address, three simple steps start rapidly loading data into snowflake. Right? So that first step is just get data in there. Start working with snowflake. Informatica is investing and making that easy for every single user out there. And especially those departmental users who wanna get started quickly. >>Yeah. So, I mean, that's a key part point of getting data into the snowflake data cloud, right? It's like any cloud, you gotta get data in. How does it work with, with customers? I mean, you guys are, are known, you have a long history of, you know, extract transform ETL. How does it work in the snowflake world? Is it, is it different? Is it, you remember the Hadoop days? It was, it was E LT, right? How are customers doing that today in this environment? >>Yeah, it's different. I mean, there, there are a lot of the, the same patterns are still in play. There's a lot more of a rapid data loading, right. Is a key theme. Just get it into snowflake and then work on the data, transform it inside of snowflake. So it's, it's a flavor of T right. But it's really pushing down to the snowflake data cloud as opposed to Hado with spark or something like that. Right. So that, that's definitely how customers are using it. And, you know, majority of our customers actually with snowflake are using our cloud technology, but we're also helping customers who are on premise customers, automate the migration from our on-premises technology to our cloud native platform as well. Yeah. >>And I'd say, you know, in addition to that, if you think about building a snowflake environment, Informatica helps with our data loader solution, but that's not enough. Then now you need to get value out of your data. So you can put raw data into the snowflake environment, but then you realize the data's not actually fit for business use, what do we need to do actually transform it to clean it, to govern it. And our customers that use Informatica with snowflake are managing the entire data management and data governance process so that they can allow the business to get value out of the snowflake investment. >>How quickly can you enable a business to get value from that data to be able to make business decisions that can transform right. Deliver competitive advantage? >>I think it really depends on an organization on a case by case basis. At the end of the day, you need to understand why are you doing this in the first place, right? What's the business outcome that you're trying to achieve next, identify what data elements do you actually need to capture, govern and manage in order to support the decisions and the actions that the business needs to take. If you don't have those things defined, that's where data governance comes into play. Then all you're doing is setting up a technical environment with a bunch of zeros in ones that no one knows what to do with. So we talk about data governance more holistically, say, you need to align it to your business outcomes, but ensure that you have people, processes, roles, and responsibilities, and the underlying technology to not just load data into snowflake, but to leverage it again for the business needs across the organization. >>Oh, good, please. >>I just wanted to add to that real quickly. Yeah. One of the things Informatica we're philosophically focused on is how do you accelerate the entire business of data management? So with our, our cloud platform, we have what's called our clear AI engine, right? So we use AI techniques, machine learning recommendations to accelerate with the, the knowledge of the metadata of what's gone on the organization. For example, that when we discover data assets figure out is this customer data, is it product data that dramatically shortens the time to find data assets deliver them? And so across our whole portfolio, we're taking things that were traditionally months to do. We're taking 'em down to weeks and days and even hours, right? So that's the whole goal is just accelerate that entire journey and life cycle through cloud native approaches and AI. Yeah, >>You kind of just answered my question. I think Rick, so you have this joint value statement together. We help customers. This is informatic and snowflake together. We help customers modernize their data. Architecture enable the most critical workloads, provide AI driven data governance and accelerate added value with advanced analytics. I mean, you definitely touched on some of those, but kind of unpack the rest of that. What do you mean by modernize? What is their data architecture? What is that? Let's start there. What does that look like? Modernizing a data. Yeah. >>So, so a lot with so many customers, right? They, they built data warehouses, core data and analytics systems on premises, right? They're using ETL technology using those, those either warehouse, appliances or databases. And what they're looking for is they wanna move to a cloud native model, right. And all the benefits of cloud in terms of TCO elasticity, instant scale up agility, all those benefits. So we're looking, we're looking to do with our, our modernization programs for our, for our current customer base that are on premises. We automate the process to get them to a fully cloud native, which means they can now do hybrid. They can do multi-cloud elastic processing. And it's all also in a consumption based model that we introduced about about a year and a half ago. So, so they're looking for all those elements of a cloud native platform and they're, but they're solving the same problems, right? We still have to connect data. We still have to transform data, prepare it, cleanse it, all those things exist, but in a, in a cloud native footprint, and that's what we're helping them get to. >>And the modern architecture these days, quite honestly, it's no longer about getting best breed tools and stitching them together and hoping that it will actually work. And Informatica is value proposition that our platform has all those capabilities as services. So our customers don't have to deal with the costs and the risks of trying to make everything work behind the scenes and what we've done with IDMC or intelligent data management cloud for financial services, retail, CPG, and healthcare and life sciences. In addition to our core capabilities and our clear AI machine learning engine, we also have industry accelerators, prebuilt data, quality rules for certain regulations in within banking. We've got master data management, customer models for healthcare insurance industry, all prebuilt. So these are accelerators that we've actually built over the years. And we're now making available to our customers who adopt informatic as intelligent data management cloud for their data management and governance needs. >>And then, and then the other part of this statement that that's interesting is provide AI driven data governance. You know, we are seeing a move toward, you know, decentralized data architectures and, and, and organizations. And we talk to snowflake about that. They go, yeah, we're globally distributed cloud. Okay, great. So that's decent place, but what we see a lot of customers doing to say, okay, we're gonna give lines of business responsibility for data. We're gonna argue about who owns what. And then once we settle that here's your own, here's your own data lake. Maybe they they'll try to cobble together a catalog or a super catalog. Right. And then they'll try to figure out, you know, some algorithms to, to determine data quality, you know, best, you know, okay. Don't use. Right, right. So that, so if I understand it, you automate all that. >>So what we're doing with AI machine learning is really helping the data professional, whether in the business, in technology or in between not only to get the job done faster, better, and cheaper, but actually do it intelligently. What do we mean by that? For example, our AI engine machine learning will look at data patterns and determine not only what's wrong with your data, but how should you fix it and recommend data quality rules to actually apply them and get those errors addressed. We also infer data relationships across a multi-cloud environment where those definitions were never there in the beginning. So we have the ability to scan the metadata and determine, Hey, this data set is actually related to that data set across multiple clouds. It makes the organization more productive, but more importantly, it increases the confidence level that these organizations have the right infrastructure in place in order to manage and govern their data for what they're trying to do from a business perspective. >>And I add that as well. I think you're talking a lot about data mesh architectures, right? That, that are really kind of popular right now. And I think those kind of, they live or die on, on data governance. Right? If you don't have data governance to share taxonomy, these things, it's very hard to, I think, scale those individual working groups. But if you have a platform where they, the data owners can publish out visibility to what their data means, how to use it, how to interpret it and get that insight, that context directly to the data consumers that's game changing. Right. And that's exactly what we're doing with our cloud data governance and catalog. >>Well, the data mesh, you talk about data mesh, there's four principles, right? It's like decentralized architecture data products. So if, once you figure out those two yep. You just created two more problems, which is the other two parts of the Princip four, two parts of the four principles, self service infrastructure, and computational governance. And that's like the hardest part of federated, federated, computational governance. That's the hardest part. That's the problem that you're solving. >>Yeah. Yeah, absolutely. I mean, think about the whole decentralization and self-service, well, I may be able to access my data in mesh architecture, but if I don't know what it means, how to use it for what purpose, when not to use it, you're creating more problems than what you originally expected to solve. So what we're doing is addressing the data management and the governance requirements, regardless of what the architecture is, whether it's a mesh architecture, a fabric architecture or a traditional data lake or a data store. >>Yeah. Mean, I say, I think data mesh is more of an organizational construct than it is. I, I'm not quite sure what data fabric is. I think Gartner confused the issue that data fabric was an old NetApp term. Yeah. You're probably working in NetApp at the time and it made sense in the NetApp context. And then I think Gartner didn't like the fact that Jamma Dani co-opted this cool term. So they created data fabric, but whatever. But my, my point being, I think when I talk to customers that are they're, they're trying to get more value outta data and they recognize that going through all these hyper specialized roles is time consuming and it's not working for them. And they're frustrated to your points and your joint statement. They want to accelerate that. And they're realizing, and the only way to do that is to distribute responsibility, get more people involved in the process. >>And, and that's, it kind of dovetails with some, the announcements we made on data governance for snowflake, right, is you're taking these, these operational controls of the snowflake layer that are typically managed by SQL and you, and that decentralized architecture data owner doesn't know how to set those patterns and things like that. Right. So we're saying, all right, we're, we're creating these deep integration so that again, we have a fit for persona type experience where they can publish data assets, they can set the rules and policies, and we're gonna push that down to snowflake. So when it actually comes to provisioning data and doing data sharing through snowflake, it's all a seamless experience for the end user and the data owner. Yeah. >>That's great. Beautiful, >>Seamless experience absolutely necessary these days for everybody above guys. Thanks so much for joining David me today, talking about Informatica what's new, what you're doing with snowflake and what you're enabling customers to do in terms of really extracting value from that data. We appreciate your insights. >>Thank you. Yep. >>Thank you for having us >>For our guests and Dave ante. I'm Lisa Martin. You're watching the cubes coverage of snowflake summit day two of the cubes coverage stick around Dave. And I will be right back with our next guest.

(bright upbeat music) >> Welcome, everyone, to theCUBE's, continuing coverage of AWS re:Invent 2021. I'm your host, Lisa Martin. And we are running one of the industry's most important and largest hybrid tech events of the year with AWS and its ecosystem partners. We have two live sets, two remote studios, and over 100 guests on the program talking about the next decade in cloud innovation. We're very excited to be welcoming back one of our CUBE alumni, Peter McKay, the CEO of Snyk. He's set to talk about reinventing application security with Snyk. Peter, welcome back to the program. >> It's great to be back, Lisa. Thanks for having me. >> Great to talk to you. So, my goodness, Snyk has had an incredible year, last year, this year, I was just looking at your Series F funding raised over 600 million in the month of September alone. Your valuation is, I think I saw over 9.6 billion, which is nearly doubled. This year-- >> Don't rush at 8.6, but yes, it was double the last time. Yeah, it's been been a crazy 2021, that's for sure. >> So, talk to me about some of that before we get into what you guys are doing with AWS. Let's talk about that, we talked about that funding. What are some of the strategic areas of investment? I know you've done a recent acquisition cloud skiff, but where are you really going to be focusing the Series F funding? >> Yeah, we've been very aggressive in building out our platform. We have a great vision for where we see developer security evolving and we want to get there fast. A lot of our customers and developers are kind of pushing us in that direction of really consolidating a platform. And so, to get there quickly, we do it organically building it ourselves, and we do it in inorganically where we can see other companies accelerate that roadmap. And so, it's this combination of very aggressive, organic expansion of both the breadth of our products, but also the depth, like adding more to our platform, but also the inorganic, because a lot of companies who have team and technologies that are very complimentary to what we're doing and allows us to continue to consolidate what is a very fragmented market in and around developers security. And so, we're going to continue to use the resources to accelerate that roadmap. The second part of it is, we are a little bit different than some companies where they kind of follow where the decision headquarters are of companies for us, we follow developers. And so, around the globe, Multinational Corporations have developers in the Philippines, in Argentina and all around the world and we needed to be there. And so, expanding our community, expanding our customer success organization around the world is critical for us. And so, that's something part of our kind of use of proceeds is the expansion of our go-to-market as well. >> Peter, modern development has changed. Next thing modern development has changed. So, traditional AppSec doesn't apply anymore. A new approach is needed. Talk to me about why Snyk believes that and what that new approach is. >> Yeah, you just go back to for 30 years, security was owned by application security teams and that's when it was kind of this waterfall application development model where they develop an app and every three, six, nine months, and then the security teams would audit that application and kind of send all the feedback, hear all the issues, go fix it, developers, and it was incredibly inefficient. And then you throw on top of this digital transformation and companies moving incredibly fast in building new applications. This agile development motion and all the incredible tools that allow developers to develop really fast. But then you get this very slow antiquated way of kind of testing it at the very end, right before you move the applications in production. So, it just didn't scale. And so, the concept is just way too late in the process. You really need to move security testing into that developer environment from the IDE, the CI/CD all the way through. So, when you're developing along the way, you're fixing the issues well ahead of time. And that's where modern development organizations are all this concept of shift left and building it in, into that's really the driver is moving security earlier and earlier in the software development life cycle. >> And that's key, especially you talked about the acceleration of digital transformation, but we've also seen the acceleration of the threat landscape in the last 20 months. There's been significant changes. The perimeter is so fragmented, it's expanding, the threat landscape goes all the way into outer space to low earth orbit these days. Talk to me about that as kind of a facilitator or an accelerator of what Snyk is doing to really focus on shifting security left with those developers. >> Yeah, I think people are kind of waking up to the fact that up to this point, they've spent billions and billions of dollars on endpoint securities and runtime security and all the things that are kind of in production. And they're realizing that, okay, well, why are we still vulnerable? Why are we still have these issues? And I think it's the realization that they're waiting too long to fix it. And a lot of the issues are happening. They're either new issues with moving to the cloud or they're issues that happen well before it got into production. And so, this realization that we've got to go earlier and earlier and fix these issues well before we go into production and don't wait till the very end. So, I think that's really driving the market to this shift lab. >> And you guys have actually kind of really pivoted your go-to-market model around that developers don't try and buy software the way that IT and security teams do. Talk to me about Snyk's GTM. >> Yeah, it's very unique in that it's really marrying this model developer security approach with the way developers want to buy. So, we start with our community and we do free content and tools all around building awareness for the developer community. We have, all of our products are free, so developers can try before they buy. And if you're truly a developer solution, you offer it free and let them use it. And then when they want to collaborate and they want to integrate and automate that moves from free to paid. So, it's very much of this bottoms up motion that really allowed developers to try MI. That's a big, big driver for our business, inbound motion drives 70% of our pipeline from them coming to us from this community. And then we come in kind of top down once they kind of get into different places. And we go in through those security organizations, which are trying to shift labs, trying to move security earlier, earlier and we work together with the security organizations to help move that to the developer world. So, you've got this bottoms up, developer adoption, viral adoption of Snyk within those organizations. Now, with the top-down kind of, and we become this bridge between the developer teams in engineering, and the security teams that are all trying to move in the same direction. And so, that's kind of how this market is evolved. And we're kind of that bridge for both those organizations. >> I was going to ask you about that, that bridge is critical, but also that bridge is a cultural change. I'm curious, how do you see organizations? It sounds like obviously you're, what over, I think, six, 700 customers now, a couple of million developers using the technology, so-- >> 1300 customers today >> 1300, okay. Wow! You have had a big year. 1300 customers, millions of developers using the technology. Talk to me a little bit about how you guys have figured out how to facilitate that cultural shift and shift security left, but also bridge between the IT and the security folks which have tended to be on sort of opposite sides of the spectrum. >> Yeah, I think the realization, I think a lot of people are very early on and I was... We'd been in the software industry for 25 years. Even nobody ever thought developers would care about security. Like there's no way developers really care about security. And really, if you think about, if you asked the developer, would you rather develop a secure app or an insecure app? If all things were equal, of course, they'd want it to be secure, but it needs to be easy. It needs to be like, don't slow me down, whatever you do, don't slow me down. And so, we have this, "Hey, it's all about speed of development, speeds, speed, speed." So, for us, we need to make it embedded, like integrated completely into that software development life cycle. So, developers don't have to be security experts, developers don't have to get out of their flow to do it, learn a different piece of software to figure out it's all embedded into that process. So, you can be fast and you can be agile, but you can also be secure at the same time. And so, part of that is embedding education and other things in there to learn that expansion of getting in the door and kind of building that momentum within these development communities all around the world. And so, I think we help all our customers with that kind of developer adoption and working together with the security teams and engineering teams on how we roll that out around best practices. And in some of the things we've learned over the six and a half years of doing this. >> It sounds very strategic and methodical and a great approach that is obviously quite successful. We talked about the growth trajectory now, 1300 customers. Let's talk about what you guys are doing with AWS. Here we are at reinvent this year. Talk to me about this Snyk, AWS partnership. >> Yeah, it's been really gaining momentum over the past year and a half, almost two years now. AWS, a lot of the workloads, one of the reasons, a lot of the applications don't go to the cloud is because of security issues and moving workloads to the cloud. Also developing applications in the cloud, security is a critical part of it. So, AWS is obviously infrastructure, but they also need solutions that allow them to make sure that those companies that are developing on AWS are secure. And so, we've integrated our Intel database into AWS inspector. We have a lot of offerings, very specific AWS offerings that our mutual customers can leverage. And we work very collaboratively with AWS in not only our technical roadmap with them, but also our go-to-market side, which is very much aligned. And it's continuing, we kind of, I say, we're in the second inning of that game. We got a lot more coming. >> Okay, but well aligned. Give me a customer example, if you will, have joined AWS Snyk customer that you've really helped with this transition, shifting security left they're building apps in the AWS cloud very successfully and securely. >> Yeah, I'd well, almost every company has some relationship with size with AWS. And so, for us, it's one of the first questions we ask anybody coming in is what's your relationship with one of the cloud vendors? And that inevitably it'll be, yeah, we have a relationship with AWS. And so, we talk about our roadmap that we have with AWS. They can buy our software through the AWS marketplace. You could leverage kind of your EDPs that you have with AWS to kind of build that scale. So, we're very technically aligned with the AWS platform. And so, you look at financial services, we've done a fair amount of financial services, insurance companies that are all kind of moving more workloads to AWS. Some of them have been our customers before, some of them separate from AWS, and now they're kind of, "Hey, can I move all my apps over and leveraged, Snyk in that process?" So, it's now, a good part of our go-to-market motion is coming through AWS marketplace as well. So, it's been a very successful partnership on both parties. >> A lot of momentum there, speaking of momentum, we talked about the funding raise this year alone, tremendous momentum going on for the company. What are some of the things that we can expect to see from Snyk in calendar year 22? >> Yeah, well, aggressive roadmap. I mean, that's still, we see, we have four modules today. We started with one and we added to, that was open to a security. We added a container security, infrastructure as code security. Then we added code security or a stats solution. We see modules five, six, seven coming out. we made an acquisition of drift technology, adding into kind of adding some more depth. So, you're going to see just a lot more continued aggressiveness on our side, as we scale both our engineering, organically and inorganically, but also, the go-to-market, now we're almost in all the major countries around the world and we're going to continue to invest in building that out and going where the developers are, the 28 million developers around the world. Our goal is to reach every one of them as fast as we possibly can with our free or paid, or whatever way is to get to 28 million developers as fast as we can. >> So, for those developers watching, where do you want to point them to go to, to start their free trial. >> Just go right to our website, snyk.io and you can get all of our products free, you can chat, schedule demos, you can do everything very easily if not. And it's very self-service so, if you don't want to talk to anybody, you don't have to talk to anybody, but if you do, we have plenty of people you can talk to. That's our world, frictionless motion. >> Frictionless and contactless at the same time, Peter, congratulations on the growth and momentum of the company. What you're doing, the evolution of the partnership with AWS and that lofty goal to reach 28 million developers. Am looking forward to our next conversation to see where you are on that progress. >> Same thing, same here, Lisa, thank you for your time. >> Oh, likewise. For Peter McKay, I'm Lisa Martin and you're watching theCUBE's continuous coverage of AWS re:Invent 2021. Stick around, more great content coming up next. (soft upbeat music)

(bright upbeat music) >> Welcome, everyone, to theCUBE's, continuing coverage of AWS re:Invent 2021. I'm your host, Lisa Martin. And we are running one of the industry's most important and largest hybrid tech events of the year with AWS and its ecosystem partners. We have two live sets, two remote studios, and over 100 guests on the program talking about the next decade in cloud innovation. We're very excited to be welcoming back one of our CUBE alumni, Peter McKay, the CEO of Snyk. He's set to talk about reinventing application security with Snyk. Peter, welcome back to the program. >> It's great to be back, Lisa. Thanks for having me. >> Great to talk to you. So, my goodness, Snyk has had an incredible year, last year, this year, I was just looking at your Series F funding raised over 600 million in the month of September alone. Your valuation is, I think I saw over 9.6 billion, which is nearly doubled. This year-- >> Don't rush at 8.6, but yes, it was double the last time. Yeah, it's been been a crazy 2021, that's for sure. >> So, talk to me about some of that before we get into what you guys are doing with AWS. Let's talk about that, we talked about that funding. What are some of the strategic areas of investment? I know you've done a recent acquisition cloud skiff, but where are you really going to be focusing the Series F funding? >> Yeah, we've been very aggressive in building out our platform. We have a great vision for where we see developer security evolving and we want to get there fast. A lot of our customers and developers are kind of pushing us in that direction of really consolidating a platform. And so, to get there quickly, we do it organically building it ourselves, and we do it in inorganically where we can see other companies accelerate that roadmap. And so, it's this combination of very aggressive, organic expansion of both the breadth of our products, but also the depth, like adding more to our platform, but also the inorganic, because a lot of companies who have team and technologies that are very complimentary to what we're doing and allows us to continue to consolidate what is a very fragmented market in and around developers security. And so, we're going to continue to use the resources to accelerate that roadmap. The second part of it is, we are a little bit different than some companies where they kind of follow where the decision headquarters are of companies for us, we follow developers. And so, around the globe, Multinational Corporations have developers in the Philippines, in Argentina and all around the world and we needed to be there. And so, expanding our community, expanding our customer success organization around the world is critical for us. And so, that's something part of our kind of use of proceeds is the expansion of our go-to-market as well. >> Peter, modern development has changed. Next thing modern development has changed. So, traditional AppSec doesn't apply anymore. A new approach is needed. Talk to me about why Snyk believes that and what that new approach is. >> Yeah, you just go back to for 30 years, security was owned by application security teams and that's when it was kind of this waterfall application development model where they develop an app and every three, six, nine months, and then the security teams would audit that application and kind of send all the feedback, hear all the issues, go fix it, developers, and it was incredibly inefficient. And then you throw on top of this digital transformation and companies moving incredibly fast in building new applications. This agile development motion and all the incredible tools that allow developers to develop really fast. But then you get this very slow antiquated way of kind of testing it at the very end, right before you move the applications in production. So, it just didn't scale. And so, the concept is just way too late in the process. You really need to move security testing into that developer environment from the IDE, the CI/CD all the way through. So, when you're developing along the way, you're fixing the issues well ahead of time. And that's where modern development organizations are all this concept of shift left and building it in, into that's really the driver is moving security earlier and earlier in the software development life cycle. >> And that's key, especially you talked about the acceleration of digital transformation, but we've also seen the acceleration of the threat landscape in the last 20 months. There's been significant changes. The perimeter is so fragmented, it's expanding, the threat landscape goes all the way into outer space to low earth orbit these days. Talk to me about that as kind of a facilitator or an accelerator of what Snyk is doing to really focus on shifting security left with those developers. >> Yeah, I think people are kind of waking up to the fact that up to this point, they've spent billions and billions of dollars on endpoint securities and runtime security and all the things that are kind of in production. And they're realizing that, okay, well, why are we still vulnerable? Why are we still have these issues? And I think it's the realization that they're waiting too long to fix it. And a lot of the issues are happening. They're either new issues with moving to the cloud or they're issues that happen well before it got into production. And so, this realization that we've got to go earlier and earlier and fix these issues well before we go into production and don't wait till the very end. So, I think that's really driving the market to this shift lab. >> And you guys have actually kind of really pivoted your go-to-market model around that developers don't try and buy software the way that IT and security teams do. Talk to me about Snyk's GTM. >> Yeah, it's very unique in that it's really marrying this model developer security approach with the way developers want to buy. So, we start with our community and we do free content and tools all around building awareness for the developer community. We have, all of our products are free, so developers can try before they buy. And if you're truly a developer solution, you offer it free and let them use it. And then when they want to collaborate and they want to integrate and automate that moves from free to paid. So, it's very much of this bottoms up motion that really allowed developers to try MI. That's a big, big driver for our business, inbound motion drives 70% of our pipeline from them coming to us from this community. And then we come in kind of top down once they kind of get into different places. And we go in through those security organizations, which are trying to shift labs, trying to move security earlier, earlier and we work together with the security organizations to help move that to the developer world. So, you've got this bottoms up, developer adoption, viral adoption of Snyk within those organizations. Now, with the top-down kind of, and we become this bridge between the developer teams in engineering, and the security teams that are all trying to move in the same direction. And so, that's kind of how this market is evolved. And we're kind of that bridge for both those organizations. >> I was going to ask you about that, that bridge is critical, but also that bridge is a cultural change. I'm curious, how do you see organizations? It sounds like obviously you're, what over, I think, six, 700 customers now, a couple of million developers using the technology, so-- >> 1300 customers today >> 1300, okay. Wow! You have had a big year. 1300 customers, millions of developers using the technology. Talk to me a little bit about how you guys have figured out how to facilitate that cultural shift and shift security left, but also bridge between the IT and the security folks which have tended to be on sort of opposite sides of the spectrum. >> Yeah, I think the realization, I think a lot of people are very early on and I was... We'd been in the software industry for 25 years. Even nobody ever thought developers would care about security. Like there's no way developers really care about security. And really, if you think about, if you asked the developer, would you rather develop a secure app or an insecure app? If all things were equal, of course, they'd want it to be secure, but it needs to be easy. It needs to be like, don't slow me down, whatever you do, don't slow me down. And so, we have this, "Hey, it's all about speed of development, speeds, speed, speed." So, for us, we need to make it embedded, like integrated completely into that software development life cycle. So, developers don't have to be security experts, developers don't have to get out of their flow to do it, learn a different piece of software to figure out it's all embedded into that process. So, you can be fast and you can be agile, but you can also be secure at the same time. And so, part of that is embedding education and other things in there to learn that expansion of getting in the door and kind of building that momentum within these development communities all around the world. And so, I think we help all our customers with that kind of developer adoption and working together with the security teams and engineering teams on how we roll that out around best practices. And in some of the things we've learned over the six and a half years of doing this. >> It sounds very strategic and methodical and a great approach that is obviously quite successful. We talked about the growth trajectory now, 1300 customers. Let's talk about what you guys are doing with AWS. Here we are at reinvent this year. Talk to me about this Snyk, AWS partnership. >> Yeah, it's been really gaining momentum over the past year and a half, almost two years now. AWS, a lot of the workloads, one of the reasons, a lot of the applications don't go to the cloud is because of security issues and moving workloads to the cloud. Also developing applications in the cloud, security is a critical part of it. So, AWS is obviously infrastructure, but they also need solutions that allow them to make sure that those companies that are developing on AWS are secure. And so, we've integrated our Intel database into AWS inspector. We have a lot of offerings, very specific AWS offerings that our mutual customers can leverage. And we work very collaboratively with AWS in not only our technical roadmap with them, but also our go-to-market side, which is very much aligned. And it's continuing, we kind of, I say, we're in the second inning of that game. We got a lot more coming. >> Okay, but well aligned. Give me a customer example, if you will, have joined AWS Snyk customer that you've really helped with this transition, shifting security left they're building apps in the AWS cloud very successfully and securely. >> Yeah, I'd well, almost every company has some relationship with size with AWS. And so, for us, it's one of the first questions we ask anybody coming in is what's your relationship with one of the cloud vendors? And that inevitably it'll be, yeah, we have a relationship with AWS. And so, we talk about our roadmap that we have with AWS. They can buy our software through the AWS marketplace. You could leverage kind of your EDPs that you have with AWS to kind of build that scale. So, we're very technically aligned with the AWS platform. And so, you look at financial services, we've done a fair amount of financial services, insurance companies that are all kind of moving more workloads to AWS. Some of them have been our customers before, some of them separate from AWS, and now they're kind of, "Hey, can I move all my apps over and leveraged, Snyk in that process?" So, it's now, a good part of our go-to-market motion is coming through AWS marketplace as well. So, it's been a very successful partnership on both parties. >> A lot of momentum there, speaking of momentum, we talked about the funding raise this year alone, tremendous momentum going on for the company. What are some of the things that we can expect to see from Snyk in calendar year 22? >> Yeah, well, aggressive roadmap. I mean, that's still, we see, we have four modules today. We started with one and we added to, that was open to a security. We added a container security, infrastructure as code security. Then we added code security or a stats solution. We see modules five, six, seven coming out. we made an acquisition of drift technology, adding into kind of adding some more depth. So, you're going to see just a lot more continued aggressiveness on our side, as we scale both our engineering, organically and inorganically, but also, the go-to-market, now we're almost in all the major countries around the world and we're going to continue to invest in building that out and going where the developers are, the 28 million developers around the world. Our goal is to reach every one of them as fast as we possibly can with our free or paid, or whatever way is to get to 28 million developers as fast as we can. >> So, for those developers watching, where do you want to point them to go to, to start their free trial. >> Just go right to our website, snyk.io and you can get all of our products free, you can chat, schedule demos, you can do everything very easily if not. And it's very self-service so, if you don't want to talk to anybody, you don't have to talk to anybody, but if you do, we have plenty of people you can talk to. That's our world, frictionless motion. >> Frictionless and contactless at the same time, Peter, congratulations on the growth and momentum of the company. What you're doing, the evolution of the partnership with AWS and that lofty goal to reach 28 million developers. Am looking forward to our next conversation to see where you are on that progress. >> Same thing, same here, Lisa, thank you for your time. >> Oh, likewise. For Peter McKay, I'm Lisa Martin and you're watching theCUBE's continuous coverage of AWS re:Invent 2021. Stick around, more great content coming up next. (soft upbeat music)

(soft techno music) >> Good evening. Welcome back to the Kube. Live in Los Angeles. We are at KubeCon Cloud Native Con 2021. Lisa Martin with Dave Nicholson, rounding out our day. We're going to introduce you to a new company, a new company that's new to us. I should say, log DNA. Peter Choi joins us the VP of product. Peter, welcome to the program. >> Thanks for having me. >> (Lisa) Talk to us about log DNA. Who are you guys? What do you do? >> So, you know, log DNA is a log medicine platform. Traditionally, we've been focused on, you know, offering log analysis, log management capabilities to dev ops teams. So your classic kind of troubleshooting, debugging, getting into your systems. More recently, maybe in like the last year or so we've been focused on a lot of control functionality around log medicine. So what I mean by that is a lot of people typically think of kind of the analysis or the dashboards, but with the pandemic, we noticed that you see this kind of surge of data because all of the services are being used, but you also see a downward pressure on cost, right? Because all of a sudden you don't want to be spending two X on those digital experiences. So we've been focused really on kind of tamping down kind of controls on the volume of log data coming in and making sure that they have a higher kind of signal and noise ratio. And then, you know, I'll talk about it a little bit, but we've really been honing in on how can we take those capabilities and kind of form them more in a pipeline. So log management, dev ops, you know, focusing on log data, but moving forward really focused on that flow of data. >> (Dave) So, when you talk about the flow of data and logs that are being read, make this a little more real, bring it up, bring it up just to level in terms of data, from what? >> Yeah. >> What kind of logs? What things are generating logs? What's the relevant information that's being. Kept track of? >> Yeah, I mean, so from our perspective, we're actually agnostic to data source. So we have an assist log integration. We have kind of basic API's. We have, you know, agents for any sort of operating system. Funny enough people actually use those agents to install, log DNA on robots, right? And so we have a customer they're, you know, one of the largest E-commerce platforms on, in the, in the world and they have a warehouse robots division and they installed the agent on every single one of those robots. They're, you know, they're running like arm 64 processors and they will send the log data directly to us. Right? So to us, it's no different. A robot is no different from a server is no different from an application is no different from a router. We take in all that data. Traditionally though, to answer your question, I guess, in the simplest way, mostly applications, servers, firewalls, all the traditional stuff you'd expect kind of going into a log platform. >> So you mentioned a big name customer. I've got a guess as to who that is. I won't, I won't say, but talk to us about the observability pipeline. What is that? What are the benefits in it for customers? >> (Peter) Sure. So, like if we zoom out again, you know, you think about logs traditionally. I think a lot of folks say, okay, we'll ingest the logs. We'll analyze them. What we noticed is that there's a lot of value in the step before that. So I think in the earlier days it was really novel to say, Hey, we're going to get logs and we're going to put it into a system. We're going to analyze it. We're going to centralize. Right. And that had its merits. But I think over time it got a little chaotic. And so you saw a lot of the vendors over the last three years consolidating and doing more of a single pane of glass, all the pillars of observability and whatnot. But then the downside of that is you're seeing a lot of the teams that are using that then saying being constrained by single vendor for all the ways that you can access that data. So we decided that the control point being on the analysis side on, on the very far right side was constricting. So we said, okay, let's move the control point up into a pipeline where the logs are coming to a single point of ingress. And then what we'll do is we will offer views, but also allow you to stream into other systems. So we'll allow you to stream into like a SIM or a data warehouse or something, something like that. Right? So, and you know, we're still trying to like nail down the messaging. I'm sure our marketing person's going to roast me after this. But the simplest way to think of observability pipeline is it's the step before the analysis part, that kind of ingest processes and routes the data. >> (Dave) Yeah. This is the Kube, by the way, neither one of us is a weather reporter. (laughing) So, so the technical stuff is good with us. >> Yes. It is. What are, and talk to us about some of the key features and capabilities and maybe anything that's newly announced are going to be announced. >> Yeah. For sure. So what we recently announced early access on is our streaming capabilities. So it's something that we built in conjunction with IBM and with a couple of, you know, large major institutions that we were working with on the IBM cloud. And basically we realized as we were ingesting a log data, some of those consumers wanted to access subsets of that data and other systems such as Q radar or, you know, a security product. So we ended up taking, we filtered down a subset of that data and we stream it out into those systems. And so we're taking those capabilities and then bringing it into our direct product, you know, whatever you access via logging.com. That is what's essentially going to be the seed for the kind of observability pipeline moving forward. So when you start thinking about it, all of this stuff that I mentioned, where we say, we're focusing on control, like allowing you to exclude logs, allowing you to transform logs, you take those processing capabilities, you take the streaming capabilities, you put them together and all of a sudden that's the pipeline, right? So that's the biggest focus for us now. And then we also have supporting features such as, you know, control API's. We have index rate alerting so that you can get notified if you see aberrations in the amount of flow of data. We have things like variable retention. So when a certain subset of logs come in, if you want it store it for seven days or 30 days, you can go ahead and do that because we know that a large block of logs is going to have many different use cases and many different associated values, right? >> So let's pretend for a moment that a user, somebody who has spent their money on log DNA is putting together a Yelp review and they've given you five stars. >> Yup. >> What do they say about log DNA? Why did they give you that five star rating? >> Yeah. Absolutely. I think, you know, the most common one and it's funny it's Yelp because we actually religiously mine, our G2 crowd reviews. (all laughing) And so the thing that we hear most often is, it's ease of use, right? A lot of these tools. I mean, I'm sure, you know, you're talking to founders and product leaders every day with developers. Like the, the bar, the baseline is so low, you know, a lot of, a lot of organizations where like, we'll give them the, you know, their coders, they'll figure it out. We'll just give them docs and they'll figure it out. But we, we went a little bit extra in terms of like, how can we smooth that experience so that when you go to your computer and you type in QTPL, blah, blah, blah, two lines, and all of a sudden all your logs are shipping from your cluster to log DNA. So that's the constant theme for us in all of our views is, Hey, I showed up, I signed up and within 30 minutes I had everything going that I needed to get. >> (Lisa) So fast time to value. >> Yes. >> Which is critical these days. >> Absolutely. >> Talk to me. So here we are at, at KubeCon, the CNCF community is huge. I think I, the number I saw yesterday was 138,000 contributors. Lots of activity, because we're in person, which is great. We can have those hallway networking conversations that we haven't been able to have in a year and a half. What are some of the things that you guys have heard at the booth in terms of being able to engage with the community again? >> You know, the thing that we've heard most often is just like having a finger on the pulse. It's so hard to do that because you know, when we're all at our computers, we just go from zoom to zoom. And so it, it like, unless it punches you in the face, you're not aware of it. Right. But when you come here, you look around, you go, you can start to identify trends, you hear the conversations in the hallway, you see the sessions. It's just that, that sense of, it's almost like a Phantom limb that, that sense of community and being kind of connected. I think that's the thing that we've heard most often that people are excited. And, you know, I think a lot of us are just kind of treating this like a dry run. Like we're kind of easing our way back in. And so it, you know, it felt good to be back. >> Well, they've done a great job here, right? I mean, you have to show your proof of vaccination. They're doing temperature checks, or you can show your clear health pass. So they're making it. We were talking to the executive director of CNCF earlier today and you're making it, it's not rocket science. We have enough data to know that this can be done carefully and safely. >> (David) Don't forget the wristbands. >> That's right. And, and did you see the wristbands? >> (Peter) Oh yeah. >> Yeah, yeah that's great. >> Yep, it is great. >> I was, I was on the fence by the way. I was like, I was a green or yellow, depending on the person. >> (both) Yeah. >> Yeah. But giving, giving everybody the opportunity to socialize again and to have those, those conversations that you just can't have by zoom, because you have somebody you've seen someone and it jogs your memory and also the control of do I want to shake someone's hand or do I not. They've done a great job. And I think hopefully this is a good test in the water for others, other organizations to learn. This can be done safely because of the community. You can't replicate that on video. >> (Peter) Absolutely. And I'll tell you this one for us, this is our, this is our event. This is the event for us every single year. We, we it's the only event we care about at the end of the day. So. >> What are some of the things that you've seen in the last year, in terms of where, we were talking a lot about the, the adoption of Kubernetes, kind of, where is it in its maturation state, but we've seen so much acceleration and digital transformation in the last 18 months for every industry businesses rapidly pivoting multiple times to try to, to survive one and then figure out a new way to thrive in this, this new I'll call it the new. Now I'll borrow that from a friend at Citrix, the new now, not the new normal, the new now, what are some of the things that you've seen in the last year and a half from, from your customer base in terms of what have they been coming to you saying help? >> (Peter) You know, I think going back to the earlier point about time to value, that's the thing that a lot. So a lot of our customers are, you know, very big Kubernetes, you know, they're, they're big consumers of Kubernetes. I would say, you know, for me, when I do the, we do our, our QBRs with our top customers, I would say 80% of them are huge Kubernetes shops. Right. And the biggest bottleneck for them actually is onboarding new engineers because a lot of the, and you know, we have a customer, we have better mortgage. We have, IBM, we have Rappi is a customer of ours. They're like Latin American version of Instacart. They double their engineering base and you, you know, like 18 in 18 months. And so that's, you know, I think it was maybe from 1500 to 3000 developers or so, so their thing is like, we need to get people on board as soon as possible. We need to get them in these tools, getting access to, to, to their longs, to whatever they need. And so that's been the biggest thing that we've heard over and over again is A, how can we hire? And then B when we hire them, how do we onboard them as quickly as possible, so that they're ramped up and they're adding value. >> How do you help with that onboarding, making it faster, seamless so that they can get value faster? >> So for us, you know, we really lean in on our, our customer success teams. So they do, you know, they do trainings, they do best practices. Basically. We kind of think of ourselves given how much Kubernetes contradiction we have, we think of ourselves as cross pollinators. So a lot of the times we'll go into those decks and we'll try to learn just as much as we're trying to try to teach. And then we'll go and repeat that process through every single set of our customers. So a lot of the patterns that we'll see are, well, you know, what kinds of tools are you using for orchestration? What kind of tools are you using for deployment? How are you thinking about X, Y, and Z? And then, you know, even our own SRE teams will kind of get into the mix and, you know, provide tips and feedback. >> (Lisa) Customer centricity is key. We've heard that a lot today. We hear that from a lot of companies. It's one thing to hear it. It's another thing to see it. And it sounds like the Yelp review that you would have given, or, or what you're hearing through G2 crowd. I mean, that voice of the customer is valid. That's, that's the only validation. I think that really matters because analysts are paid. >> Yeah. >> But hearing that validation through the voice of the customer consistently lets you know, we're going in the right direction here. >> Absolutely. >> I think it's, it's interesting that ease of use comes up. You wonder if those are only anonymous reviews, you don't necessarily associate open source community with cutting edge, you know, we're the people on the pirate ship. >> (Peter) Yeah. And so when, when, when people start to finally admit, you know, some ease of use would be nice. I think that's an indication of maturity at a certain point. It's saying, okay, not everyone is going to come in and sit behind a keyboard and program things in machine language. Every time we want to do some simple tasks, let's automate, let's get some ease of use into this. >> And I'll tell you in the early days it drove me and our, our CEO talker. It drove us nuts that people would say easiest to be like, that's so shallow. It doesn't mean anything. Well, you know, all of that. However, but to your point, if we don't meet the use case, if we don't have the power behind it, the ease of use is abstracting away. It's like an iceberg, right. It's abstracting away a lot. So we can't even have the ease of use conversation unless we're able to meet the use case. So, so what we've been doing is digging into that more, be like, okay, ease of use, but what were you trying to do? What, what is it that we enabled? Because ease of use, if it's a very shallow set of use cases is not as valid as ease of use for petabytes of data for an organization like IBM. Right? >> That's a great, I'm glad that you dug into that because ease of use is one of those things that you'll see it in marketing materials, but to your point, you want to know what does this actually mean? What are we delivering? >> Right. >> And now, you know what you're delivering with Peter, thank you for sharing with us about logged in and what you guys are doing, how you're helping your community of customers and hearing the voice of the customer through G2 and others. Good work. >> Thank you. And by the way, I'll be remiss if I, if I don't say this, if you're interested in learning more about some of the stuff that we're working on, just go to logging in dot com. We've got, I think we've got a banner for the early access programs that I mentioned earlier. So, you know, at the end of the day, to your point about customer centricity, everything we prioritize is based on our customers, what they need, what they tell us about. And so, you know, whatever engagement that we get from the people at the show and prospects, like that's how we drive a roadmap. >> (Lisa) Yup. That's why we're all here. Log dna.com. Peter, thank you for joining Dave and me today. We appreciate it. >> Thanks for having me. >> Our pleasure for Dave Nicholson. I'm Lisa Martin signing off from Los Angeles today. The Kubes coverage of KubeCon clouding of con 21 continues tomorrow. We'll see then. (soft techno music)

>>from the bellagio hotel in Las Vegas >>it's the >>cube >>covering Ui >>Path Forward four brought to you >>by Ui Path. >>Welcome back to las Vegas. The cube is live with you. I Path forward four at the bellagio lisa martin with Dave Volonte. We're gonna be talking about you I Path integration suite, we have a couple of guests joining us here. Mark Jeannie is here the GM of Ui Path, formerly the co founder and Ceo of cloud elements and Peter Villeroy also joins us Director of Global I. T. Automation practice at UI Path guys welcome to the program. >>Thanks lisa. Great to hear. >>So Mark, let's go ahead and start with you. The Cloud elements acquisition was done in about the last six months. Talk to us about why you chose to be acquired by Ui Path and where things are today. Some big announcements yesterday. >>Yeah absolutely. So yeah if you go back six months ago um you know we have been in conversations with you I Path for for quite a while and um you know as we were looking at our opportunities as an api integration platform. So cloud elements just to step back a little bit um was a leader in helping companies take a P. I. S integrate applications together and bed that into their into their apps and um you know I Path approached us about the combination of what's happening in the automation world and you know these these have been a society as the marine Fleming from I. D. C. Mentioned this morning integration and DARPA have been separate swim lanes and what we saw and what you I. Path approaches with was ability to combine these together and really be the first company to take and take ui automation and seamlessly connected together with A. P. I. Automation or api integration >>Peter What's been some of the feedback? We know you guys are more than 9000 customers strong now we've had a whole bunch of amount yesterday and today. What's been the feedback so far on the cloud elements acquisition? So >>there's a huge amount of interest. We've had very positive feedback on that lisa the combination of Ui driven automation and A. P. I. Uh Native Integrations is is key especially to the I. T. Leadership that I work with. Um some of whom have traditionally compartmentalized you ipads platform in the Ui space and legitimately think about their own internal processes as being having very little to do with the user interface right. And so combining Ui driven automation together with uh api integration really helps too pick them up where they are and show them the power of that kind of a hyper automation platform that can deliver value in a number of spaces. And you guys ever >>see the movie Blindside? All right. You know what I'm talking about with joe. Theismann gets hit from the blind side and then his career is over and and that's when people realized oh my gosh the left tackle for right handed quarterback is so important and it's subsequent drafts when somebody would pick a left tackle like a good left all the rest went and that's what's happening in in the automation business today. You guys took the lead, you you set the trend. People said wow this is actually going to be a huge market. And then now we're seeing all this gonna occur. And a lot of it from these big software companies who believe every dollar of software should go to them saying hey we can actually profit from this within our own vertical stacks. So what do you make of all the M. And A. That's going on in particular? There was one recently where private equity firm is mashing together a long time R. P. A vendor with a long time integration firm. So it looks like you guys, you know on the right >>side of history in this regard. Your thoughts. Yeah. Absolutely. I mean if you think about automation right you've got to obviously help people do their jobs better. But if you're going to automate a process and a department you needed connect the applications that they use that those people use otherwise you can't accomplish it. And where ap is fit in as is automation and ui automation has become more and more mission critical and it's become bigger and bigger part of enterprise I. T. Wants to get involved. And so enterprise gets involved and what's their stack. It's api based their technology stack is how you connect back is through api so more and more companies are seeing what you I path saw is that if you're gonna automate every process and every department for every person you need to connect to every application that they're using and that's why this is now becoming right. Three companies now just recently have done these types of acquisitions of bringing an integration platform in and combining them together are trying to combine them together. >>All mps are not created equally as we know. Some are sort of half baked lot of them. Many of them don't have decent documentation so there's sort of a spectrum there. How do you, how do you think about prioritizing? How do you think about the landscape? Do you just kind of ignore the stuff that's not well documented and eventually that will take care of itself. How should we think about there have always >>been layers of integration right. Especially working with the ICTy organizations. So you've got our native integrations would make it easy to drag and drop activities and then you've got the A. P. I. Is that we can consume with various activities. That area has really grown through the acquisition of cloud elements and then you've got that third layer where when all else fails, you go on to the user interface and interact with the application like a human does and what you see is that our our interaction with college elements really enables a great enhancement of that lower base level um which is mildly interesting to the lines of business very important. I Yeah, for sure. >>So the reason I asked that question is I was talking to one of your customers this big ASAP customers said I love you ipad. The problem I have is I got so many custom mods and so it's just you know orally documented and I can't I wanna put automation in there but I can't. So to those parts of the tech stack become like the main frame of you know what I mean? And just sort of they live there and they just keep doing their thing but there's so much innovation that pops up around it. How do you how do you see that? >>Well that's part of the agility that comes with the platform like you ipads is that you can interact with the very clean uh swagger documented restful aPI s and you can interact with SCP on their proprietary ages old A. P. I. S. Um Those are things that we've traditionally done decently well, but again through this acquisition we could do that on a grander scale um with bidirectional triggering and all the goodness that you >>solve that problem today that your customer and this is a couple of years ago, you can solve that problem with cloud elements. Is that right? >>Yeah, absolutely. The the ability to integrate too these enterprise platforms like ASAP you need multiple tools to do the job. Right. So ui automation is great but if you've customized ui significantly or other things like that then the A. P. I can be a great structure for it and other cases where um that api provides a resiliency in a in a scale to it that um opens up new processes as well to those corporate systems. Right? So the balance of being able to bring these two worlds together is where you can unlock more because you got >>east west automation >>that's very good overhead and now >>you're going north south with cloud elements is deeper. Right, >>bottom line from the VP of its point of view, the more that can be done from a machine to machine communication the better. So sure. >>What's the opportunity for the existing cloud elements customers to take advantage of here? >>Yeah, absolutely. Um We've continued to support, brought our customers over with us. Uh Part of our customer base has actually been a significant number of software customers. Uh cos S. A. P. S. One of them doc you sign gain site, you know, so household names in the world of software as well as large financial services institutions like US Bank and Capital One and american Express, all of them had that common need where um they wanted to have an api centric approach to being able to connect to customers and partners and leverage our platform to do that. So we will continue to support that extend that. But we see opportunities where again we couldn't automate everything for our customers just threw a PS And uh you know for example one of our major financial services institutions were working with wants to take um and provide a robot for their uh customers and commercial payments to be able to automatically kick off in A. P. I. And so that seamless integration where we can combine that automation with robots leveraging and kicking off a P. I. S automatically takes us further into automating those processes for those >>customers. So you guys six months right. Uh talk about how that integration api integration company better gone smoothly. But what was that like you guys are getting the knack of M and a talk about that, what you learn maybe what you would do differently to even accelerate further, How'd it go? Uh >>That's the best answer from you having been on the >>acquisition side. Um Well we how well it went is six months later, which I think is really unheard of in the technology world, we're introducing our combined offering you I Path integration service that essentially takes what cloud elements built embeds it right into automation. Cloud studio in the Ui Path products. We and uh it's been a global effort. Right? So we had the Ui Path team was based in Hyderabad Denver and Dallas and then we've got um Ui Path engineers working with that cloud elements team that are in Bucharest Bellevue and bangalore and with the miracles of zoom and uh that type of thing, never meeting anyone in person, we were able to integrate the product together and launch it here today >>six months is a fast turnaround time frame was how much of that was accelerated by the, by the fact of the global situation that we're in. >>Yeah, well you know in some respects that that helped right? Because we um um we didn't have to waste time traveling and we could hop on zoom calls instantly. We spent a lot of time even over zoom making sure there was a cultural fit. You I path has a, you know, not only the humble, bold and type of values but it's a very collaborative environment, very open and collaborative environment as Brent can attest to. And that collaboration, I think in that spirit of collaboration really helped us feel welcome and move quickly to pull this together. And also >>the necessity is the mother of innovation right. Uh you ipad traditionally being popular in the CFOs organization were becoming the C I O s best friend and the timing was right to introduce this kind of capability to combine with what we traditionally do well and really move into their picking up like I said the customer where they are and leading them into that fully end to end automation capability and this was integral. So it wasn't time to kick the tires but to get moving >>and my right, there's a governance play here as well because I. T. Is kind of generally responsible for governance if you make it easier for them to whatever governance systems they're using >>governance privacy >>security that now you can just connect. They don't have to rip and replace. Is there an angle there? >>Sure, yeah. So nothing is more important than I. T. Than than control and governments and change management and half of the uh conversations we're having out there on the floor are around that right um uh ensuring that all of the good governance is in place um and we have a lot of the uh integrations and frameworks necessary to help that through your devops pipeline and doing proper ci cd and test automation um and you know introducing that integration layer in addition to what we already have just helps all of that to uh move more smoothly and bring more value to our customers. >>Mark talk to me about some of the feedback from customers that you mentioned, doc Watson. S A P probably I imagine joint customers with you. I path now there you're working together, what's the what's in it for them? >>Yeah, no the feedback has been tremendous. Right, so um api automation is not new to you. I path but customers have been asking for more capability. So one of them is in that governance area that we were just talking about, right, the ability to create connections centrally enable them disable them. Right? You got mission critical corporate applications. You want to be able to make sure that those applications are being controlled and monitored. Right? So that was one aspect. And by bringing this as a cloud based service, we can accomplish that. Um the other area is that this eventing capability, the ability to kick off workflows and processes based on changes to corporate applications, a new employees added in workday. I want to kick off a process to onboard that new employee and that triggered eventing service has been really well received and then um yeah, so that I'd say with the ability to also create new connections more simply was the third big factor. Uh we created a standardized authentication service. So no matter where you are in the UI Path product line, you get a consistent way to create a new connection, whether it's a personal connection by a business user too, you know, google docs or Microsoft office or your C O E R I T. Creating a connection to uh an important corporate system. >>How about the partner? I know you guys had partner day here leading into forward for they must be stoked about this gives you a lever to even add new partners. What was those >>conversations like? Yeah, yeah, no, absolutely. The partners are excited about those same features but um they're also excited about something in our roadmap which we expect to be previewing early next year and that's a connector builder. So the ability for partners to uh more quickly than ever create their own connectors. That'll work just like first party connectors that we ui Path build and add them into catalogs, share them in the market place. So there's new revenue opportunities, new opportunities for partners to create reusable assets that they can leverage and yeah so um lots of things, lots of work to continue to do, right? It's only been six months and uh but that's that's gonna be a big initiative going forward. >>So integration service as you mentioned, announced at this conference, we know that that's the first step obviously accomplished as we also talked about very quickly in a six month time period. But what does the future hold for api automation and integration service? >>So um one of the key areas just continue to expose the integration service um more broadly in the Ui Path product portfolio. Now that we have this service, more Ui Path products will be able to leverage it. Right? We're starting off with studio and orchestrator but that we can all use and share that common common capability. Um The other is to make access to complex business systems easier. So you think about it right. A uh to get a purchase order from net suite might take five or six api calls to do. Well, a citizen developer doesn't know what those five or six things you have to do. So we'll be creating these business activities or just get me open purchase orders that will work seamlessly in the studio product. And behind the scenes. Well, chain together those 56 aPI calls to make that a simple process. Right? So taking the integration service and making it even more powerful tool for that citizen developer than nontechnical user as well. So that's >>development work you're going to do. >>That's what we're gonna do as well as enable partners to do as well. So it's a key part of our road map over time. Because >>yeah I mean the partner pieces key because when net suite changes how it you're creating that abstraction layer. So but that's value add for the partners. >>Absolutely. And they have that domain expertise, right. They can create assets, leveraging the UI path automation capabilities but also bring their knowledge about A. S. A. P. Or workday and those oracle ebs and those core business systems and then combine that together into assets that enhance integration service that they build and I can I can share with their customers and share with our market >>because the work workday developer is going to know about that well ahead of time. No, >>it's coming and they know better than we do. Right. That's their business. That's what they know really well. >>Nice nice value at opportunity, peter >>One of the things that you iPad has been known for is its being very and I've said this on the program the last two days, that's being a good use case for land and expand. You guys have 70% of revenue that comes from existing customers. Talk to me about the cloud elements acquisition as a facilitator of because you kind of mentioned, you know, we're used to be really in bed with the cfos now we're going to see us and we've heard from a number of your customers where they started in finance and it's now Enterprise White, how is this going to help facilitate that? Even more? >>It really helps, you know, touching on what Mark just mentioned about the citizen developer, right, just as one of many examples, the empowerment of end users to automate things for themselves um is critical to that land and expand um successes that we've been seeing and where from an I. T standpoint, the frustration with the citizen developer is, you know, maybe what they're building isn't so top notch right? It works for themselves. What we can't replicate that, but put making it easy to make api integration part of what they do in studio X is so key to enhancing also the reusability of what's coming out of there. So that c uh C O E S can replicate that across teams are globally within their organization and that's part of land and expand because you may find something that's valuable in one line of business replicates easily into another line of business if the tool set is in place >>pretty powerful model lisa >>it is guys. Thanks so much for joining us today, talking about the club elements acquisition, what you're uh, doing with integration service, What's to come the opportunities in it for both sides and your partners? We appreciate your time. >>Great. Thank you. Thank you very much. I >>appreciate it. Thank you for >>David Want I'm lisa martin. You're watching the cube live in las Vegas at the bellagio Ui Path forward for stick around. We'll be right back. Yeah. Mhm. Mhm mm.

>> Okay. We're back here. theCube and all the action here in Mobile World Congress, cloud city, I'm John ferry, host of the cube. We've got a great remote interviews. Of course, it's a hybrid event here in the cube. And of course, cloud city's bringing all the physical face-to-face and we're going to get the remote interviews. Peter Adderton, founder, chairman, CEO of Mobile X Global. Nicholas Gerrard, founder and CEO of OxyGo. Gentlemen, thank you for coming in remotely onto the cube here in the middle of cloud city. You missed Bon Jovi last night, he was awesome. The little acoustic unplugged and all the action. Thanks for coming on. >> Yeah, thanks for having us. >> All right, Peter and Nicholas, if you don't mind, just take a quick 30 seconds to set the table on what you guys do, your business and your focus here at Mobile World Congress. >> So I'll jump in quickly. Being the Australian, I'll go first, but just quick by way of background, I founded a company called Boost Mobile, which is one of the, is now the fourth largest mobile brand in, in America. And I spent a lot of time managing effort in that, in that space and now launching Mobile X, which is kind of the first cloud AI platform that we're going to build for mobile. >> Awesome. Nicholas. >> So I'm a founder of a company called, Ox Fuel where we do is basically a telecommunity service platform for brands to basically incorporate telecom as part of their services and learn from their customers through what we call a telecom business intelligence. So basically making sense of the telecom data to improve their business across retail, financial services or in-demand economy. >> Awesome. Well, thanks for the setup. Peter, I want to ask you first, if you don't mind, the business models in the telecom area is really becoming, not just operate, but build and build new software enabled software defined just cloud-based software. And this has been a change in mindset, not so much a change so much in the actual topologies per se, or the actual investments, but as a change in personnel. What's your take on this whole cloud powering the change in the future of telco? >> Well, I think you've got to look at where the telcos have come from in order to understand where they're going in the future. And where they've come from is basically using other people's technology to try to create a differentiation. And I think that that's the struggle that they're going to have. They talk about wanting to convert themselves from telcos into techcos. I just think it's a leap too far for the carriers to do that. So I think we're going to see, you know, them pushing 5G, which you see they're doing out there right now. Then they start talking about open rand and cloud and, and at the end of the day, all they want to do is basically sell you a plan, give you a phone attached to that and try to make as much money out of you as they possibly can. And they disguise that basically in the whole technology 5G open rand discussion, but they really, I don't think care. And at the end of the day, I don't think the consumers care, their model isn't built around technology. The model is built around selling your data and, and that's their fundamental principle and how they do that. And I've seen them go through from 2G, 3G, 4G, 5G. Every G we see come out has a promise of something new and incredible. But what we basically get is a data plan with the minutes. Right? >> Yeah, yeah I totally right on. And I think we're going to get into the whole edge piece of what that's going to open up when you start thinking about what, what the capabilities are and this new stakeholders who are going to have an interest in the trillions of dollars on the table right now, up for grabs. But Nicholas wanted to get to you on this whole digital-first thing, because one of the things we've been saying on theCube and interviewing folks and riffing on is: If digital drives more value and there's new use cases that are going to bring on, that's going to enabled by software. There's now new stakeholders coming and saying, Hey, you know what? I need more than just a pipe. I need more than just the network. I need to actually run healthcare. I need to run education on the edge. These are now industrial and consumer related use cases. I mean, this is software. This is where software and apps shine. So cloud native can enable that. So what's your take on the industry as they start to wake up and say, holy shit, this is going to be pretty massive when you look at what's coming. Not so much what's going to be replatformed, but what's coming. >> Yeah, no, I think it's a, it's where I kind join Peter on this. There's been pretty significant, heavy innovation on the carrier side for, you know, if you think about it 30 years or so of like just reselling plans effectively, which is a virtual slice of the network that built. And all of a sudden they started competing against, you know, the heavyweights on the internet. We had, putting the bar really high in terms of, you know, latency in terms of expectation, in terms of APIs, right? We've we've heard about telecom APIs for 15 years, right? It's- nothing comes close to what you could get if you start building on top of a Stripe or a Google. So I think, it's going to be hard for a lot of those companies. What we do with our show is we try to bridge that gap. Right, we try to build on top of their infrastructure to be able to expose modern APIs, to be able to open up a programmatic interface so that innovators like Peter's are able to actually really take the user experience forward and start, building those specialized businesses across healthcare, financial services, and whatnot. >> Yeah, David Blanca and I were on the, on theCube yesterday talking about how Snowflake, a company that basically sits on top of Amazon built almost nothing on the infrastructure. Built on top of it and was successful. Peter, this is a growth thing. One of the things I want to get your thoughts on is you've had experiences in growing companies. How do you look at the growth coming into this market, Peter, because you know, you got to have new opportunities coming in. It's a growth play too. It's not just take share from someone. It's net new capabilities. >> Yeah. Here's the issue you've got with the wireless industry is that there's only a very few amount of them that actually have that last mile covered. So if you're going to build something on top of it, you're going to have to deal with the carrier, and the carrier as out of like a duopoly slash monopoly, because without their access to their network, you're not going to be able to do these incredible things. So I think we've got a real challenge there where you're going to have to get the carriers to innovate. Now you've got the CEO of Deutsche Telekom coming out yesterday saying that the OTT players aren't paying their fair share. Right, and I sit back and go, well, hang on. You're selling data to customers who basically are using that data to use apps and OTT. And now he's saying, well, they should pay as well. So not only the consumer pay, but now the OTT players should pay. It's a mixed message. So what you're going to have to do, and what we're going to have to do as a, as a growth industry is we're going to have to allow it to grow. And the only way to do that is that the carriers are going to have to have better access, allow more access to their networks, as Nico said, let the APIs has become more available. I just think that that's a leap too far. So I think we're going to be handicapped in our growth based on these carriers. And it's going to take regulators and it's going to take innovation and consumers demanding carriers, do it, otherwise, you know, you're still going to deal with the three carriers in your world. >> Yeah, That's interesting about- I was just talking to Danielle Royce, the DR here at TelcoDR. And she said, I was talking about ORAN and there's more infrastructure than needed. She said, oh, it's more software. I don't disagree with her. I do agree with it. But I also think that the ORAN points to, Nicholas, kind of this idea that there's more surface area to be had on the scale side. So standardizing hardware creates a lower fixed cost, so you can get some cost reduction. And then with standardized software, you get more enablement for hardened openness. I mean, open source is already proven. You can still be secure. And obviously Cloud was once said, could never be secure and most, is probably more secure than anything. What's your take on this whole ORAN commodity standardization mission- efforts? >> I think it's a, I mean, it goes along to the second phase, right? Of what the differentiation in telecom was, you know. Early on, specialized boxes that are very expensive. You know, that you, you, you, you get from a few vendors, then you have the transition over to a software. We lower the price, as you were mentioning. It can run on off the shelf hardware. And then we're in the transition, which is what Danielle is, is evangelizing, right. Transition towards the cloud and specifically the public cloud, because there's no such thing as a private cloud really. And, and so up and running is just another, another piece where you can make the Legos connect better effectively and just have more flexibility. And generally the, the, the game here is to also break the agenda when you- from, from the vendors, right? Because now you have a standard, so you don't necessarily need to buy the entire stack from, from the same vendors. You have a lot more flexibility. You know, you've probably followed the same debate that we've all seen, right. With a push against Huawei, for instance. Th-this is extremely hard for an operator, to start ripping out an entire vendor, because most of the time, they, they own the entire stack. But something like ORAN, now you can start mixing and matching with different vendors, but generally this is also a trend that's going to accelerate the move towards the public cloud. >> That's awesome. Peter, I want to get your thoughts because you're basically building on the cloud. And if you don't mind chime it in to kind of end the segment on this one point. People are trying to really get their minds around what refactoring means. And we've been saying, and talking about, you know, the three phases of, of waking up to the world. Reset your business, or reboot. Replatform to the cloud, and then refactor, which means take advantage of cloud enabled things, whether it's AI and other things. But first get on the platform, understand the economics, and then replatform. So the question, Peter, we'll start with you. What does refactoring actually mean and look like in a successful future execution or playbook? Can you share your thoughts, because this is what people want to get to because that's where the value will come from. That's where the iteration gets you. What's your take on this refactoring? >> Yeah, yeah. So I always, I mean, we're in the consumer business, so I'm always about what is the difference going to make for the consumer? So, whether you're, and when you look at refactoring and you look at what's happening in the space. Is what is the difference that's going to, what are the consumers going to see that's different and are they willing to pay for that? And so we can strip away the technical layers and we all get caught up in the industry with these buzzwords and terms, and we get, and at the end of the day, when it moves to the consumer, the consumer just sits there and says, so what's the value? How much am I paying? And so what we're trying to do at MobileX is, we're trying to use the cloud and we're trying to use kind of innovation into create a better experience for the consumer. One way to do that is to basically help the customer, understand their usage patents. You know, right now today, they don't understand that. Right if I asked you how much you paid for your mobile bill, you will tell me my cell phone bill is $150, but I'm going to ask you the next question How much data do you use? You go, I don't know, right? >> John: unlimited. >> And then I'd say why am I started- well you'd say limited, right. I will go. I'd go, I don't know. So I sit back and go, most customers are like you. You're basically paying for a service that you have no clear, no idea what you're getting. And it's designed by the carriers to scare you into thinking you need it. So I think we've got to get away from the buzzwords that we use as an industry and just dumb that down to what, what does that mean for a consumer? And I think that the cloud is going to allow us to create some very unique ways for consumers to interact with their device and their usage of that device. And I think that that's the holy grail for me. >> Yeah. That's a great point. And it's worth calling out because I think if the cloud can get you a 10X value at, at a reduction in costs compared to the competition, that's one benefit that people will pay for. And the other one is just, Hey, that's really cool. I want I'll, I value that, that's a valuable thing. I'll pay for it. So it's interesting that the cloud scale there, it's just a good mindset. >> Yeah. So it's always, I always like say to people, you know, I've spoken a lot to the Dish guys about what open rand is going to do and I keep saying to them, so what's the value that I'm going to get from a consumer. And they'll say, oh it's flexible pricing plans. They're now starting to talk about, okay, what the end product is of this technology. You look at ECM, right? ECM has been around for a long time. It's only now that we're to see ECM technology, get enabled. The carriers fought that for a long, long time. So there's a monumental shift that needs to take place. And it's in the four or five carriers in our counties. >> Awesome. Nicholas, what's your take on refactoring? Obviously, you know, you've got APIs, you've got all this cool software enabled. How do you get to refactoring and how do you execute through that? >> I mean, it's a little bit of a, what Peter was saying as well, right? There's the, the advantage of that point is to be, you know, all our stuff basically lives in the cloud, right. So it's opportunity to, to get that closer, you know, just having better latency, making sure that, you know, you're not losing your, your photos and your data as you lose your phone and yep. Just bet- better access in general. I, I think ultimately like the, the push to the cloud right now is it's mostly just a cost reduction. The back tick, as far as the carriers are concerned, right. They don't necessarily see how they can build that break. And then from there start interacting with the rest of the OTT world and, and, you know, Netflix is built on Amazon and companies like that, right? Like, so as you're able to get closer as a carrier to that cloud where the data lives, this is also just empowering better digital experience. >> Yeah I think that's where the that's, the proof point will be there, as they say, that's where the rubber will meet the road or proof is in the pudding, whatever expression. Once they get to that cost reduction, if they can wake up to that, whoa we can actually do something better here and make m- or if they don't someone else will. Right. That's the whole point. So, final question as we wrap up, ecosystem changeover. Lot more ecosystem action. I mean, there's a lot of vendors here at Mobile Congress, but real quick, Peter, Nicholas, your take on the future of ecosystem around this new telco. Peter, we'll start with you. >> Yeah, I look, I mean, it, it, again, it keeps coming back to, to, to where I say that consumers have driven all the ecosystems that have ever existed. And when I say consumers also to IOT as well, right? So it's not just the B to C it's also B to B. So look to the consumer and look to the business to see what pain points you can solve. And that will create the ecosystems. None of us bet on Uber, none of us bet on Airbnb. Otherwise we'd all be a lot richer than we are today. So none of us took that platform- and by the way, we've been in mobile and wireless and any kind of that space smartphone space for a long time. And we will miss those applications. And if you ask a CEO today of a telco, what's the 5G killer application, that's going to send 5G into the next atmosphere, they can't answer the question. They'll talk about drones and robotic surgeries and all things that basically will never have any value to a consumer at the end of the day. So I think we've got to go back to the consumer and that's where my focus is and say, how do we make their lives better? And that will create the ecosystem. >> Yeah, I mean, they go for the low hanging fruit. Low latency and, and whatnot. But yeah, let's, it's going to be, it's going to be, we'll see what happens. Nicolas your take on ecosystems as they develop. A lot more integrations and not customization. What's your thoughts? >> Yeah, I think so too. I mean, I think going back to, you know, again like 20- 20 years ago, the network was the product conductivity to the product. Today it's a, it's a building block, right? Something that you integrate that's part of your experience. So the same way we're seeing like conversions between telecom and financial services. Right? You see a lot of telcos trying to be banks. Banks and fintechs trying to be telcos. It's, it's a blending of that, right? So it, at the end of the day, it's like, why, what is the experience? What is the above and beyond the conductivity? Because customers, at this point, it's just not differentiated based on conductivity, kind of become just a busy commodity. So even as you look at what Peter is building, right, this, what is the experience above and beyond just buying a plan that I get out of it, or if you are a media company, you know, how do I pair my content or resolve real problems? Like for instance, we work a lot to the NBA and TikTok. They get into markets where, you know, having a video product at the end and people not being well-connected, that's a problem, right? So it's an opportunity for them to bring the building block into their ecosystem and start offering solutions that are a different shape. >> Awesome. Gentlemen, thank you so much. Both of you, both experienced entrepreneurs and executives riding the wave on the right side of history, I believe. Thanks for coming on theCube, I appreciate it. >> Thanks for having us. >> If you're not riding the wave the right way, you're driftwood. And we're going to toss it back to the studio. Adam and the team, take it from here.

>>from the cube studios in Palo alto in boston connecting with thought leaders all around the world. >>This is a cute conversation. Welcome to the cubes coverage of HP discover 2021 I'm lisa martin. I've got three guests with me here. They're going to be talking about the partnership between HP and AMG. Please welcome George hope worldwide Head of partner sales at HP terry, Richardson north american channel chief for AMG and Peter chan, the director of media channel sales at AMG Gentlemen, it's great to have you on the cube. >>Well, thanks for having us lisa. >>All right, >>we're excited to talk to you. We want to start by talking about this partnership terry. Let's go ahead and start with you. H P E and M D have been partners for a very long time, very long history of collaboration. Talk to us about the partnership >>HB named, He do have a rich history of collaboration spinning back to the days of chapter on and then when A M. D brought the first generation AMG equity process department back in 2017, HP was a foundational partner providing valuable engineering and customer insights from day one AmY has a long history of innovation that created a high performance CP roadmap for value partners like HP to leverage in their workload optimized product portfolios, maximizing the synergies between the two companies. We've kicked off initiatives to grow the chain of business together with workload focused solutions and together we define the future. >>Thanks terry George, let's get your perspective as worldwide had a partner sales at HP. Talked to me about H P S perspective of that AMG partnership. >>Yeah, they say it's uh the introduction of the third generation AMG Epic processors, we've we've doubled our A. M. D. Based Pro Lion portfolio. We've even extended it to our follow systems. And with this we have achieved a number of world records across a variety of workloads and are seeing real world results. The third generation am the epic processor delivers strong performance, expand ability and the security our customers need as they continue their digital transformation, We can deliver better outcomes and lay a strong foundation for profitable apartment growth. And we're incorporating unmatched workload optimization and intelligent automation with 360° security. And of course, uh with that as a service experience. >>But as a service experience becoming even more critical as is the security as we've seen some of the groundbreaking numbers and data breaches in 2020 alone. Peter I want to jump over to you now. One of the things that we see H P E and M. D. Talking about our solutions and workloads that are key areas of focus for both companies. Can you explain some of those key solutions and the value that they deliver for your customers? >>Absolutely. It's from computing to HPC to the cloud and everything in between and the young HB have been focused on delivering not just servers but meaningful solutions that can solve customer challenges. For example, we've seen here in India, the DL- 325 has been really powerful for customers that want to deploy video. Hp nmD have worked together with icy partners in the industry to tune the performance and ensure that the user experience is exceptional. Um This just one example of many of course, for instance, the 3 45 with database 3 65 for dense deployments, it's key the 35 That has led the way in big data analytics. Um the Apollo 60 500 breaking new path in terms of AI and Machine learning, quite a trending topic and m D H p are always in the news when it comes to groundbreaking HPC solutions and oh by the way, we're able to do this due to an unyielding commitment to the data center and long term laser focused execution on the M the road map. >>Excellent. Thanks. Peter. Let's talk about the channel expansion a little bit more terry with you. You know, you and the team here. Channel Chief focused on the channel. What is A. M. D. Doing specifically to expand your channel capabilities and support all of the Channel partners that work with Andy >>great question lisa Campbell is investing in so many areas around the channel. Let's start with digital transformation. Our Channel partners consistently provided feedback that customers need to do more with less between A and B and H P. E. We have solutions that increase capabilities and deliver faster time to value for the customer looking to do more with less. We have a tool on our website called the and metrics server virtualization, Tco estimation tool and those who have visually see the savings. We also have lots of other resources such as technical documentation, A and E arena for training and general CPU's departments can take advantage of aside from solution examples, AMG is investing in headcount internally and at our channel part race. I'm actually an example of the investment MD is making to build out the channel. One more thing that I'll mention is the investment that are, you know, lisa su and Andy are making to build out the ecosystem from head Count to code development and is investing to have a more powerful user experience with our software partners in the ecosystem. From my discussions with our channel partners, they're glad to see A and d expanding our our channel through the many initiatives and really bringing that ecosystem. >>Here's another question for you as channel chief. I'm just curious in the last year, speaking and you talked about digital transformation. We've seen so much acceleration of the adoption of that since the last 15 months has presented such challenges. Talk to me a little bit about some of the feedback from your channel partners about what you am, D N H B are doing together to help those customers needed to deliver that fast time to value, >>you know, so really it's all about close collaboration. Um we we work very closely with our counterparts at H P. E just to make sure we understand partner and customer requirements and then we work to craft solutions together from engaging, technically to collaborating on on, you know, when products will be shipped and delivered and also just what are we doing to uh to identify the next key workloads and projects that are going to be engaged in together? So it's it's really brought the companies I think even closer together, >>that's excellent as a covid catalyst. As I say, there's a lot of silver linings that we've seen and it sounds like the collaboration terry that you mentioned has become even stronger George. I want to go to you. Let's HP has been around for a long time. My first job in tech was Hewlett Packard by the way, many years ago. I won't mention how long but talk to me about the partnership with AMG from H P s perspective, is this part of H P S D N A? >>Absolutely. Partnering is our D N A. We've had 80 years of collaboration with an ever expanding ecosystem of partners that that all play a key role in our go to market strategy. We actually design and test our strategic initiatives in close collaboration with our partners so that we can meet their most pressing needs. We do that through like farmer advisory boards and things of that nature. Um but we have we have one of the most profitable partner programs in the industry, 2-3 times higher rebates than most of our competitors. And we continue to invest in the partner experience in creating that expertise so partners can stand out in a highly competitive market. Uh And Andy is in direct alignment with that strategy. We have strong synergies and a common focus between the two companies. >>And I also imagine George one question and one question to that there's tremendous value in it for your end user customers, especially those that have had to everyone pivot so many times in the last year and have talked to me a little bit about George What you're saying from the customer's perspective. >>Well as Antonio Neri said a couple of years back, the world is going to be hybrid and uh, he was right. We continue uh we continue to see that evolution and we continue to deliver solutions around a hybrid digital world with, with Green Lake and the new wave of digital transformation that we refer to now as the age of insight customers want a cloud experience everywhere. And 70% of today's workloads can easily be re factored for the public cloud or they need to stay physically close to the data and other apps at the emerging edge or in polos are in the data centers. So as a result, most organizations are forced to deal with the complexity of having two divergent operating models and they're paying higher cost to maintain them both with Green Lake, we provide one consistent operating model with visibility and control across public clouds and on prem environments. And that applies to all workloads, you know, whether it's cloud native or non cloud native applications. Um we also have other benefits like no cloud block in or no data. Egress charges, so you have to pay a steep price just to move workloads out of the public cloud. And then we're expanding collaboration opportunities within for our partner ecosystem so that we can bring that cloud experience to a faster growing number of customers worldwide. So we've launched new initiatives uh in support of the core strategy as we accelerate our as a service vision and then work with partners to unlock better customer outcomes with Green Lake and of course, hb compute of which I am d is part of is, is the underlying value added technology. >>Can you expand on some of those customer outcomes as we look at, as I mentioned before, this very dynamic market in which we live. It's all about customer outcomes. What are some of those that from a hybrid cloud environment perspective with Green like that you're helping customers achieve? >>Well, at least Greenland has come out with with about 30 different different offerings that package up some solutions. So you're not just buying infrastructure as a service. We have offerings like HPC as a service. We have offerings like uh, V D I as a service, ml, ops as a service. So we're packaging in technology, some are are some are not ours, but into completing some solutions. So that creates the outcome that the customers are looking for. >>Excellent. Thanks, George and Peter, last question to you again with the hybrid cloud environment being something that we're seeing more and more of the benefits that Green Lake is delivering through the channel. What's your perspective from a. M decide? >>Absolutely lisa. So, so I mean I think it's clear with a MD based systems, customers get the benefit of performance, security and fast time to value whether deployed on prem and cloud on a hybrid model. So please come try out our HP system based on name the processors and see how we can accelerate and protect your applications. Thank you lisa. >>Excellent, Peter George terry, thank you for joining me today. I'm sure there's a lot more that folks are going to be able to learn about what AM D and H. P. Are doing together on the virtual show floor. We appreciate your time. Thank you. Yeah, for my guests, I'm lisa martin. You're watching the cubes coverage of HP discover 2021 Yeah.

(upbeat music) >> Welcome back to the Quantcast Industry Summit on the demise of third-party cookies, The Cookie Conundrum, A Recipe for Success. We're here with Peter Day, the CTO, Quantcast and Shruti Koparkar, Head of Product Marketing Quancast. Thanks for coming on. Talk about the changing advertising landscape. >> Thanks for having us. >> Thank you for having us. >> So we've been hearing the story out to the big players, want to keep the data, make that centralized, control all the leverage, and then you've got the other end. You've got the open internet that still wants to be free and valuable for everyone. What's what are you guys doing to solve this problem? Because if cookies go away, what's going to happen there? How do people track things? You guys are in this business? First question, what is Quancast strategy to adapt to third-party cookies going away? What's going to be the answer? >> Yeah, so very rightly said, John. The mission, the Quancast mission is to champion of free and open internet. And with that in mind, our approach to this a world without third party cookies is really grounded in three fundamental things. First is industry standards. We think it's really important to participate and to work with organizations who are defining the standards that will guide the future of advertising. So with that in mind we've been participating with IAB Tech Lab, We've been part of their project, we are same thing with Prebid, who's kind of trying to figure out the pipes of identity the ID pipes of the future. And then also is W3C which is the World Wide Web Consortium. And our engineers and our engineering team are participating in their weekly meetings, trying to figure out what's happening with the browsers and keeping up with the progress there on things such as Google's FLoC. The second sort of thing is interoperability. As you've mentioned that a lots of different ID solutions that are emerging. You have UID 2.0, you have LiveRamp, you have Google's FLoC, and there will be more, there are more, and they will continue to be more. We really think it is important to build a platform that can ingest all of these signals. And so that's what we've done. The reason really is to meet our customers where they are at. Today our customers use multiple Data Management Platforms, DMPs. And that's why we support multiple of those. This is not going to be much different than that. We have to meet our customers where we are, or where they are at. And then finally, of course, which is at the very heart of who Quancast is, is innovation. As you can imagine being able to take all of these multiple signals in, including the IDs and the cohorts, but also others like contextual first party consent is becoming more and more important. And then there are many other signals like time, language, geolocation. So all of these signals can help us understand user behavior, intent and interests. In absence of third party cookies. However there's something to note about these. They're very raw, they're complex, they're messy, all of these different signals. They are changing all the time, their real time. And those incomplete in information isolation, just one of these signals can not help you build up true and complete picture. So what you really need is a technology like AI and Machine Learning, to really bring all of these signals together, combine them statistically, and get an understanding of user behavior intent and interest, and then act on it. Be it in terms of providing audience insights, or responding to bid requests and so on and so forth. So those are sort of the three fundamentals that our approach is grounded in which is industry standards, interoperability, and innovation. And you know, you have Peter here >> Yeah. who is the expert so you can dive much deeper into it. >> So Peter is CTO. You've got to tell us, how is this going to actually work? What are you guys doing from a technology standpoint to help with data-driven advertising and a third-party cookieless world? >> Well, we've been this is not a shock. You know, I think anyone who's been close to this space has known that the third party cookie has been reducing in quality in terms of its pervasiveness and its longevity for many years now. And the kind of death knell is really Google Chrome, making the changes that, they're going to be making. So we've been embarrassing in this space for many years and we've had to make a number of hugely diverse investments. So one of them is in how to, as a marketer how do I tell it my marketing still working in a world without (indistinct). The majority of marketers, completely relying on third party cookies today. It's tell them if their marketing is working or not. And so we've had to invest heavily and statistical techniques, which are closer to kind of echo metric models that marketers are used to have things like out of home advertising. It's going to be establishing whether their advertising is working or not in a digital environment. And actually this as with often the case in these kind of times of massive disruption, there's always opportunity to make things better. And we really think that's true. And you know, digital measurement is often mistaken precision for accuracy and there's a real opportunity to kind of see the wood for the trees if you'd like. And start to come up with better methods of measuring the effectiveness of advertising without third party cookies. And we've had to make countless other investments in areas like contextual modeling, and targeting that third-party cookies and connecting directly to publishers rather than going through this kind of loom escape that's going to tied together third party cookies. So I could, if I was to enumerate all the investments we've made I think it would be here till midnight, but we've had to make a number of investments over a number years. And that level investments only increasing at the moment. >> Peter, on that contextual, can you just double click on that and tell us more? >> Yeah, I mean, contextual it is, unfortunately when I think this is really poorly defined. It can mean everything from a publisher saying, Hey trust us this page is about SUV's, it's a what's possible now. And it's only really been possible the last couple of years which is to build statistical models of the entire internet based on the content that people are actually consuming. And this type of technology requires massive data processing capabilities, it's able to take advantage of the latest innovations in areas like natural language processing. And really gives computers, that kind of much deeper and richer understanding of the internet, which ultimately makes it possible to kind of organize the internet, in terms of the types of content of pages. So this type of technology has only been possible for the last few years. And, but we've been using contextual signals since our inception. Had always been massively predictive in terms of audience behaviors, in terms of where advertising is likely to work. And so we've been very fortunate to keep that investment going and take advantage of many of these innovations that are happening in academia and in kind of an adjacent areas >> On the AI and Machine Learning aspect. That seems to be a great differentiator in this day and age for getting the most out of the data. How is machine learning and AI factoring into your platform? >> I think it's how we've always operated, right from our inception. When we started as a measurement company. The way that we were giving our customers at the time we were just publishers, just the publisher side of our business. Insights into who their audience was, which was using Machine Learning techniques. And that's never really changed. The foundation of our platform has always been Machine Learning from before it was cool. A lot of our, kind of a lot of our co-teams have backgrounds in Machine Learning, and the PhDs in statistics and Machine Learning. And that really drives our decision-making. I mean, data is only useful if you can make sense of it and if you can organize it, and if you can take action on it, and to do that at this kind of scale it's absolutely necessary to use Machine Learning technology. >> So you mentioned contextual also, you know, in advertising we have everyone knows and that world that you got the contextual and behavioral dynamics. The behavior that's kind of generally can everyone's believing is happening. The consensus is undeniable is that, people are wanting to expect an environment where there's trust, there's truth, but also they want to be locked in. They don't want to get walled into a walled garden. Nobody wants to be in a wall garden. They want to be free to pop around and visit sites. It's more horizontal scalability than ever before yet. The bigger players are becoming walled garden vertical platforms. So with future of AI, the experience is going to come from this data. So the behaviors out there. How do you get >> Yeah. that contextual relevance and provide the horizontal scale that users expect? >> Yeah, I think it's a really good point and we're definitely at this kind of tipping point, we think in the broader industry. I think, you know, every publisher, right? We're really blessed to work with the biggest publishers in the world. All the way through to my mom's blog, right? So we get to hear the perspectives of the publishers at every scale. And they consistently tell us the same thing. Which is they want some more directly connect to consumers. They don't want to be tied into these walled gardens, which dictate how they must present their content. And in some cases what content they're allowed to present. And so, you know, our job as a company is to really provide level the playing field a little bit. Provide them the same capabilities they're only used to in the walled gardens, but let, give them more choice. In terms of how they structure their content, how they organize their content, how they organize their audiences, but make sure that they can fund that effectively. By making their audiences and their environments discoverable by marketers, measurable by marketers, and connect them as directly as possible to make that kind of ad funded economic model, as effective in the open internet as it is in social. And so a lot of the investments we've made over recent years have been really to kind of realize that vision, which is, it should be as easy for a marketer to be able to understand people on the open internet, as it is in social media. It should be as effective for them to reach people in that environment, is really high quality content as it is on Facebook. And so we've invested a lot of our R&D dollars in making that true. And we're now live with the Quantcast Platform which does exactly that. And as third party cookies go away, it only kind of exaggerate all kind of further emphasizes the need for direct connections between brands and publishers. And so we just want to build a technology that helps make that true, and gives the kind of technology to these marketers and publishers to connect, and to deliver great experiences without relying on these kind of walled gardens. >> Yeah. The direct to consumer, direct to audience is a new trend. You're seeing it everywhere. How do you guys support this new kind of signaling from for that's happening in these new world? How do you ingest the content, ingest this consent signaling? >> We were really fortunate to have an amazing an amazing R&D team. And, you know, we've had to do all sorts to make this, you know, to realize our vision. This has meant things like we, you know we have crawlers which stand the entire internet at this point, extract the content of the pages, and kind of make sense of it, and organize it. And organize it for publishers so that they can understand how their audiences overlap with potentially their competitors or collaborators, but more importantly, organize it for marketers. So they can understand what kind of high-impact opportunities are there for them there. So, you know, we've had to build a lot of technology. We've had to build analytics engines which can get answers back in seconds, so that, you know marketers and publishers can kind of interact with it with their own data and make sense of it and present it in a way that is compelling and then help them drive their strategy as well as their execution. We've had to invest in areas like consent management. Because we believe that a free and open internet is absolutely reliant on trust. And therefore we spend a lot of our time thinking about how do we make it easy for end-users to understand who has access to that data and easy friendly and users to be able to opt out. And as a result of that, we've now got the world's most widely adopted consent management platform. So it's hard to tackle one of these problems without tackling all of them. And we're fortunate enough to have had a large enough R&D budget over the last four or five years, make a number of investments, everything from consent and identity, through to contextual signals, through to measurement technologies, which really bring advertisers and publishers closer together. >> Great insight there. Shruti last word for you. What's the customer view here as you bring these new capabilities of the platform. What's what are you guys seeing as the highlight from a platform perspective? >> So the initial response that we've seen from our customers has been very encouraging. Both on the publisher side, as well as the marketer side. I think, you know, one of the things we hear quite a lot is you guys are at least putting forth a solution and action solution for us to test. Peter mentioned measurement. That really is where we started because you cannot optimize what you cannot measure. So that is where his team has started. And we have some measurement, very very initial capabilities still in alpha, but they are available in the platform for marketers to test out today. So the initial response has been very encouraging. People want to engage with us. Of course, our, you know, our fundamental value proposition which is that the Quantcast platform was never built to be reliant on third party data, these stale segments. Like we operate we've always operated on real time live data. The second thing is our premium publisher relationships. We have had the privilege of working like Peter served with some of the biggest publishers but we also have a very wide footprint. We have first party tags across over a hundred million plus web and mobile destinations. And, you know, as you must've heard like that sort of first party footprint, is going to come in really handy in a world without third party cookies. We are encouraging all of our customers, publishers and marketers to grow their first party data. And so that's something that's a strong point that customers love about us and lean into it quite a bit. So, yeah, the initial response has been great. Of course it doesn't hurt that we've made all these R&D investments. We can talk about consent, and, you know, I often say that consent it sounds simple, but it isn't, there's a lot of technology involved. But there's lots of legal work involved as it as well. We have a very strong legal team who has expertise built in. So yeah, a very good response initially. >> Democratization, everyone's a publisher, everyone's a media company. They have to think about being a platform. You guys provide that. So congratulations Peter, thanks for dropping the gems there. Shruti thanks for sharing the product highlights. Thanks for your time. >> Thank you. >> Okay, this is the Quancast Industry Summit on the demise of third-party cookies and what's next The Cookie Conundrum, the Recipe for success with Quancast I'm John Berger with theCUBE. Thanks for watching. (upbeat music)

>> Announcer: From around the globe. It's theCUBE with digital coverage of IBM Think 2021, brought to you by IBM. >> Welcome to theCUBEs coverage of IBM Think 2021. I'm Lisa Martin, joined next by Peter Morrow the VP of sales and marketing at IBM partner, TRM. Peter, welcome to the program. >> Hi, thank you. Happy to be here. >> Tell me a little bit about yourself and TRM before we dig in. >> Well, TRM is a long time business partner for IBM. We for about 30 years, specialize in helping IBM customers implement Maximo and have a lot of deep technology expertise and in Maximo and related software in the enterprise asset management industry. I'm the VP of sales and marketing, I've been at TRM for about 10 years and I'm proud to lead our talented sales teams and our sole mission is to help our customers get value out of their EAM solutions. And we're really excited about recent developments in AI and bringing value to a lot of our customers and their organization, and finally get ROI out of their long time investments in the EAM. >> Let's dig in a bit more to the IBM relationship. I know TRM is a gold partner, but talk to me about that and how TRM has leveraged that partnership with IBM to help your customers be successful. >> Sure. Now, we're a little bit of a unique partner with IBM for a long time. We've been pure resell and implementation services. And recently we've transitioned into an OEM relationship with IBM where we actually embed IBM products into broader TRM offerings. And this relationship that we have with IBM is really important as IBM is the dominant player in EAM and AI and hybrid cloud it's really a natural fit for us to leverage those really mature solutions and build on top of them TRMs deep expertise and the technology and the reliability side to offer more of an end to end solution to our customers. >> Got it. So the last year or so we've seen a lot of market dynamics. Talk to me about the EAM market what's going on there. What are some of the changes? >> Well, there's a couple of key changes that we see, one of the biggest changes I think that impacts our business and IBM is that customers really don't have an appetite for long expensive implementations of custom solutions. They're really looking for more turnkey solutions that have proven value already and very mature. They've already spent tens of millions of dollars implementing Maximo or related EAM solution. They really don't want to embark on this really expensive long journey to get to that next level. And so to meet this requirement we've been focused for the past couple of years on developing much more turnkey solutions. One of which is one that we call TRMs Maximo AAM, solution and that's built on Maximo, but it's also layered with IBM's new AI solution for Maximo customers. And we marry that with our deep reliability expertise and we're really excited about being able to roll it out in literally weeks instead of months or years for a lot of new customers. And that's a really short time to value and ROI is something that's pretty much unheard of until now in this industry. >> Talk to me about some of the advantages that your customers are getting like on a general level from AI, from hybrid cloud, from data. >> I mean, it's this really groundbreaking. What we're finding is that there's, until very recently AI was really not embraced as a practical solution to a lot of maintenance problems. You're looking at a community of pretty old school mindsets and maintenance and reliability where, it's a very, RCM is a very structured methodology for breaking down equipment and failure types and solutions, ways to predict those failures. And for a long time RCM specialists didn't really feel like AI was a solution that was the answer. And what we're finding is that, with the maturity level of IBM's products, it is now at a point where AI is a great fit and you take a experienced reliability specialist and you've armed them with AI tools like IBM's asset monitor and Maximo health and predict and you give them those tools and they can roll out predictive solutions that scale like really they've never had the chance to before. >> And talk to me about some of the adaptations that TRM has made in the last year or so as the market has been so much influx and so many dynamics going on, how have you adapted to that to really help those customers take advantage of the latest technologies? And for example, use AI. >> The big thing for us is recognizing that customers really aren't interested in a long expensive, drawn out solution. They recognize they have problems, but until you can come to table with something that they can digest in small bites. And that is at a price point that isn't over the top they're really happy staying with the status quo, at least until the solutions can be delivered and like that very bite-sized implementation programs. So we've spent a lot of time trying to make our solutions more turnkey, packaging up offerings in a way that you can start small, but all that effort you put in on a small scale, you can ramp up and scale enterprise wide without making a huge investment. And it doesn't take years to roll it out. You can really do something and make an impact within a couple of weeks or months, rather than you know, many months and years down the road. >> That time to value is key. Especially I think we've learned in the last year that real time is so essential for so many things. I'm just curious if any industries in particular that TRM and IBM are really helping transform like energy, for example, give me some examples of industries that are really moving forward with your technologies. >> It's really the classic asset intensive industries. Utilities are really big maximum users in there. They're the ones that, they've embraced Maximo for many, many years. They're hungry for innovative technology, but still cautious about moving forward on a large scale but we're able to get them excited with the programs that we're offering. And the same goes with oil and gas. That's another big user of Maximo, asset intensive organization and manufacturing definitely big Maximo users, all three have been very interested in moving forward with the AI for maintenance solutions that TRM and IBM are together bringing to the market. >> We summed up across the oil and gas, energy utilities, as you mentioned what are some of the biggest things that you hear in terms of demands from customers when you're in sales meetings? What are they looking for problems they need you to help solve? >> You know, it's honestly, it's the classic problems that we've been working with them for 20 years and really have they haven't been able to solve effectively where they're talking about critical assets that break down on expectedly, maintenance teams, running around doing a lot of maintenance on assets. That's in perfect health, making big promises on transforming maintenance, massively reducing maintenance budgets. And it really hasn't happened. And there's really been until now no real solution that solves those problems directly. And we believe the combination of AI and reliability engineering and in the key EAM fundamental principles is what's going to help our customer base really get value and really solve the problems that they really suffered from all these years. >> It's interesting that you say that it really they haven't been able to solve those problems but from a technological perspective the technology is there now to help them do that. What's the time window when you're talking with customers especially given the market dynamics that we're still living in, are they coming to you saying help us within a week, two weeks, we got to turn this around? >> I mean, the ones that are approaching this with an open mind, we can communicate to them that a huge undertaking is not required. They can get started on a small project, select one critical asset and then begin to plug in some data, around that asset that they know is related to equipment failures. We can get that data connected with the maximum asset monitor and within weeks they begin monitoring that asset health. They do some anomaly detection and it does not require of big long-term investment. And so for somebody who is willing to keep an open mind about AI and really wants to give it a try, that sales cycle is very short. They're willing to get going relatively quickly. We do find that many organizations want to step back take it slow, assess other options. And for them that's that aligns more with the classic, big bang type of implementation project, where that takes months of planning, budget planning approvals. And that goes into that 12, 18 month sales cycle or project planning phase, that's fine. And at the end of that, it's a big project but we really do recommend starting small. It is definitely possible to see some early quick wins and then roll out on a larger scale. And frankly, you could have something deployed at scale within that entire period of planning that they would otherwise naturally do on their own. >> Take us out of here Peter, with some predictions, some thoughts, maybe a crystal ball on where you see the EAM market going, the rest of this year and what TRM is planning to do to help customers really leverage opportunities and growth. >> You know I really do believe we're at a tipping point where there's been a lot of anticipation leading up to the release of Maximo and the Maximo eight and the Maximo application suite. There's the AI apps that are in the suite like asset monitor and health and predict that they really are mature products. There's not, I think until now there's the customer base has viewed AI as more of a like a fantasy or science fiction as it relates to maintenance, but these products are real. And I think with a lot of spending having been on hold over the past year, there's a lot of interest in learning more trying to test the waters. I really think that we're going to see a lot of interest in predictive solutions, a lot of interest in IOT projects. And, we're in a position where we're ready to begin rolling these out and it's really exciting. >> Yeah, the maturation is there, the technology is the customer interest is there certainly the opportunities are there. Peter takes out with where can customers go to learn more information about your solutions? >> I mean the best places to check us out on our website, www.trmnet.com. We're also on LinkedIn. We do a lot of blogs. We do a lot of webinars, we're out in front and trying to make the market aware of our thought leadership and deep expertise in Maximo and EAM and in predictive solutions we've got a YouTube channel where we post demos and all of our webinars. So we're trying to push information out there happy to, we look forward to interacting with prospects and customers about how our solutions can impact them. >> Excellent, Peter, thanks for stopping by and sharing with us more about the TRM IBM relationship, the opportunities in the EAM market and the appetite for AI that your customers and very big industries are having. We appreciate your time. >> Thank you very much. I enjoyed it. >> Me too, for Peter Morrow, I'm Lisa Martin. You're watching theCUBEs coverage of IBM Think 2021. (upbeat music)