>> From Orlando, Florida, it's theCUBE. Covering SAP SAPPHIRE NOW 2018. Brought to you by NetApp. >> Hey, welcome to theCUBE. I'm Lisa Martin, on the ground, at SAPPHIRE NOW 2018 in the NetApp booth with Keith Townsend for the day. Keith and I are joined by Scott Feldman, the Global Head of SAP HANA and Leonardo Communities. Scott, welcome to theCUBE. >> Thank you, great to be here. >> So, communities, plural. Why are... Tell us about the communities at SAP. Why is there specifically an SAP HANA community, before we get into Leonardo? >> Okay, well it's kinda fun because you saw one community and then they say, "Well, go do another community." So you do one, and it's like, okay do one. Do another one. So we have, at SAP, a global community that runs on the SAP.com platform. That's for everybody. That's for all customers, all partners, all analysts, everybody. That's normally called a SAP community. What we realized back in, around 2012 or 2013, is that we wanted to have a special place where our SAP HANA early adopter customers could go and join and network with each other on an online presence, right, and then have an opportunity to share their knowledge with each other and get more information from SAP. So we created a separate community on SAP HANA. It's actually a pretty easy URL, it's called SAPHANACommunity.com. It's pretty simple to remember. And now, we've doing this for about five, six years. >> So talk to us about what's unique about the HANA community outside of the technology. SAP Communities, in general's already pretty big, very active community. >> Correct. >> But what was the call out or what was the results of creating the HANA community? >> Great, and that's a great question. So what's really interesting about the SAP HANA community is that the topic and coverage of the content is specifically related to SAP HANA, data management, database tools and technologies, analytics, and other surrounding areas that are connected to that HANA platform as an anchor. So we have provided, over the past five years, almost 300, 300 webinars of content on SAP HANA technology. A lot of that content has come from SAP product managers, a lot of it's come from solution experts, partners as well, have provided content. And they're in the form of webinar frameworks as well as whitepapers and other content that's on there. Now, the people that join the community, which is all free by the way for the customers that join, are mainly our SAP customers. Now I'm proud to tell you, here and also SAPPHIRE 2018, we're here, we're over 6,100 or so members, globally, of the SAP HANA community. And what's really great about that is, you know, relative to some of the millions of numbers of people throughout for other communities, it seems like, you know, 6,000 plus is a small number. But you have to keep in mind that it's very targeted, right? So the people that are through the door, and our members of the community on the SAP HANA Jam, we have it on our SAP Jam site which is hosting the SAP cloud platform. These are people that really are interested in that topic. And they really wanna learn about SAP HANA and the technology surrounding SAP HANA. So they're very, very high-qualified, high-quality people. >> Very engaged, it sounds like. >> Absolutely. >> So, speaking of that, so this morning during Bill McDermott's keynote, he mentioned 23,000 HANA customers. >> Yes. >> You mentioned 6,000 actively engaging in your community. >> Yes. >> Collaboration was a big theme of this morning, talking about, this is not grandpa's CRM anymore, what SAP is doing to break that status quo. How influential are those customers engaging in the HANA community to its development and its evolution? >> That's a fantastic question. So what's happened is the community... Think of almost like a pyramid. So the community of the large, vast number of people who have joined the community for interest in topics have mostly consumed information, they are kinda the base line of the pyramid. Some of those customers have some great stories to tell. Okay, so what we did was we started a webinar series in 2013 called Spotlight. And I'll take credit for the name, actually, 'cause we call it the SAP HANA Spotlight. And essentially, what we're doing is, imagine the customer in a spotlight where they're sharing their journey. They're sharing their SAP HANA story and their journey. So we launched that a number of years ago and now we've done almost 80 separate HANA Spotlight webinars with customers that are sharing their stories. Well we even took it one step further beyond that. In 2013, some of the executives from our early adopting customers for SAP HANA, they came over to SAP and they said, "Gee, SAP, we're betting our career "and our company survival "on this new technology called SAP HANA," back in 2013. And they basically came to us and said, "I wanna have a council." So we wanna have a council of influence so that we have an opportunity to get together, share stories, share our journeys with each other, get to know who the other customers are that are also early adopters and are embarking on this journey with us together, and then, more importantly, to answer your question, feed that information back to SAP development so that we could, back at SAP, improve the product and come out with some additional features and functions and make it even better. Well that was 2013. Our very first meeting was up in Canada, in a suburb in Toronto, at one of our customer locations. We had 13 people in that meeting. Today, dial up six years, we're at over 750 members of an executive, so these are C-level VPS, senior IT, and chief architects that are in our community globally. We've done 24 meetings, I'm about to schedule the 25th meeting, and I've globalized that. And the customers, I thought they would've been tired of these kinds of meetings, they love it. They absolutely love it. So again, going back to that analogy, this is kind of the high peak point of the pyramid. We get the executives that are making these decisions and we talk about thought leadership. We don't talk about features and functionality. We do talk about road maps, we talk about investments that they need to make, and we anchor it again on the SAP HANA platform but we're bringing in other technologies and components like analytics or SAP Leonardo, right, or S/4 HANA, right. Now that it's announced, we'll bring in C/4 HANA. So we'll cover other topics as well, and of course the cloud platform. >> So you set it up, rinse and repeat, now we're at Leonardo. >> Rinse and repeat. Rinse and repeat. >> What is, first off, what is Leonardo? Great name, I love the name. But what is it? >> So SAP Leonardo is a methodology. It's an opportunity for our customers to co-design, co-invent, and get engaged in the design thinking process to understand how data, and we talked about this today, how we can, how data and how knowledge can enable an intelligent enterprise. And it's a process. So what people need to understand, and customers work with at SAP and they could go to the SAP Leonardo booth areas at the conferences and see as many testers as they wish. But essentially it's a foundation. It's an understanding of, how do I take where I am today from my own understanding of how I operate my business, and where do I need to go, what is my next gem process? Where do I need to be in five years to be that thought leader and how do I get there? So how do I take data that I know and data that I don't know? We have, I just ran into one of our customers... We run a program out of our team as well called the SAP Innovation Awards. It started off as the HANA Innovation Awards and now we cover all technologies and all topics for customer innovation. So SAP Leonardo, cloud platform solutions, SAP HANA solutions, data management solutions, these are all innovative offerings. We just announced all the winners, we have a actually ceremony tomorrow night where all the winners have been announced and they're gonna be receiving their trophies. We've been doing this for many years. What's interesting about that is all the innovative projects that are coming from the customer programs, projects, innovations. What are they doing? How are they co-innovating? Are they co-innovating with SAP? Are they doing smart farming? We have one winner that's actually doing smart farming, micro-crop planting to understand soil composition. And humidity and moisture composition is different even if you go one meter away on this, one meter, which is nothing. >> You're right. >> For the Americans listening, it's three feet. (everyone laughs) And that's pretty close. And they can actually combine different crop plantings based on soil conditions and compositions and this is all being monitored in the SAP HANA cloud. So this is really phenomenal. >> Yeah, that would be. >> And we love these kinds of stories. And what we're doing now, as you can imagine. You're probably gonna ask me, how do you connect the dots? Well it was pretty easy to connect the dots. We have the customers that are presented these great programs. They've created these great values that they're providing to their industry, right? And they're great wins and successes. And we're leveraging those customers in the community as thought leaders. And we're also doing sessions like that. I'd like to get them on theCUBE. Have them talk about some of the things >> That would be great. >> that they're doing. >> We would have fun. We love customer stories. >> I love it. I think it would be phenomenal. >> So, let's talk bout the dynamics of running a community program that featured around a product. And HANA, very straightforward, is about the tech, a lot of it was speeds and fees transitioned into solutions. >> Right. >> When you start out with something as ambitious as Leonardo framework, are the dynamics different, like what are, what is the community like? >> A little bit 'cause SAP HANA is the foundation. And we saw this today at the keynotes today. And Bill's keynote was phenomenal and we saw that how he was positioning this and it's all about the intelligent enterprise and SAP HANA as a foundation, it's fantastic. And we've been doing this for a lot of years. But what do we do to build upon that? When we established the foundational community for SAP HANA, people started coming in and wanting to understand everything about the HANA community. We did a couple fundamental things. Number one, we connected with the SAP HANA Academy. And I'll give a shout out to my friends at the academy, I love them to death, and we've been partnering with them for five plus years. The SAP HANA Academy is a YouTube site of thousands of videos on how to do anything. It could be data management, it could be data hub, it could be Vora which is the connected to Hadoop. It could be SAP HANA. It could be analytics. And there's thousands, literally thousands of videos on how to just about do anything that you want connected to the community. So the people and the SAP HANA Academy team has presented content, webinars on our community broadcasting at least for the last... This year they did one, they do like two or three every year for the last number of years. What we did with SAP Leonardo was, Leonardo can be thought of as a combination of the technologies. So we have, as you know, with machine learning, IoT, blockchain, right, analytics and a whole bunch of other things, design thinking methodologies that are in Leonardo, so what we did is we took a lot of that and created a series of webinars and content. We just finished something called the SAP Digital Transformation Series featuring SAP Leonardo in conjunction with ASUG, the America User Group, that's our co-conference sponsor here and we love them to death. And what we did was do the 14-part webinar series. We had thousands of people come onto these calls and each call covered, for example, Mala, who's our president, she did what is the overview of Leonardo? How do we do this? We covered analytics with Mike Flannagan. Maricel covered design thinking. And then we went from there. Then we covered the solutions themselves. What is IoT, what is blockchain, what is machine learning? How do you understand what these things do and how they impact your organization? Then we took it one step further. We went into the industry solutions. So the partners are developing industry solutions. The industry accelerates, we talked a little bit earlier, there's a press release that just came out on that, on some of the.. >> The Partner Medallion Initiative. >> The Premiere Medallion Initiative, right. My friend Mike is running, from the Leonardo team. And that is certifying partners for the specific solutions that they're building around the industry, the deliverables that they have around the SAP Leonardo, we feature that as well. So all of that content was in this series and we continue to build upon that. What we really want, though, now is we wanna do what we did this time last year which was, we want the customer stories. So we've done, I've told you, we've done a lot of webinars in the community. So a lot of content going to the members of the community from the experts that understand that content. Next step, second half of the year, is we want those customer stories out there. So those 80 or so webinars that I mentioned that we did with our customer Spotlights, we want those Spotlights now. So we'll focus those... Anybody watching, give me those Spotlights. We want those stories. We want the customers to really articulate their story, their challenges, their successes, their wins, what are they doing to the SAP technology that-- >> You're preaching to the choir about customer marketing persons so that there's no better value-- >> Isn't it great? >> Brand validation, than the voice of the customer. Speaking of brand validation, I heard this morning that Bill McDermott announced that you guys are now 17 on the top 100 global most valuable brands. >> Absolutely. >> He wants to be in the top 10. >> And we're proud of that. I'm part of that team. >> Up four. You're doing this with a tremendous amount of partners is what you mentioned, partners. We're in the NetApp booth. >> Correct. >> Talk to us about what SAP and NetApp are doing in the community to enable this amazing amount of education that you're doing. >> So that's a great find. I mean, SAP wouldn't be where it is today, and I've been with SAP for (chuckles) I don't wanna say the number of years but people watch me and they know I've been at SAP a long time. It's like you can't say Scott Feldman without SAP. So it's been kind of anchored in for a long time. It's sort of the blood, the blue blood runs in the DNA you know. It was just kind of fun. But some of the partners that we've worked with in the communities have taken it to another step. NetApp is one of those. And I love working with NetApp. They're a strategic technology provider and a fantastic global partner with SAP. I know you just heard from RJ who did an interview, we work a lot with him and his team as well, Roland and the rest of the team. And what NetApp has done is they've made another strategic investment with us in the communities, for the HANA community and the Leonardo community such that they're a name-sponsored partner. And what's really nice about that is we have a special spot and if you go to the SAPHANACommunity.com site, or if you're already a member, or the other one is, you can guess, SAPLeonardoCommunity.com, very similar, right? If you go to either one of those sites, you'll find that there's a spot for partners that are specific to that community, that have taken the next step to add additional value. NetApp is there, there's a page. And what we've done is we've created a page with all the NetApp content on, what is NetApp's contribution on SAP HANA and Leonardo? Where is the value proposition? Why NetApp? What are they doing with SAP? Where are the links that we can go for all the content that NetApp has provided to us to post in that community? And not only that, NetApp is also an outstanding member, upstanding member of the SAP HANA CL Council Community 'cause they also run SAP. And, in addition to that, NetApp is a strategic partner that provides webinar content for SAP, for the community. So, about once a quarter, there'll be a webinar that is sponsored by NetApp and now I'm bugging them a little bit to get the customers in front of the webinar so we can have these little-- >> There must be some NetApp-SAP Customer Spotlights just waiting to come into the surface, right? >> Oh, absolutely. And we're doing them in small snippets so what's really great about that, it's kinda like this discussion that we're having, these small chunks. 'Cause I think the new wave of doing things, >> Snackable content. >> And I could certainly tell you're from the generation that's just maybe a little bit younger, is that they don't have time to sit down and watch a webinar for one hour. But they'll take it in 20-minute doses. They'll just like, "Man, give me "all the 20-minute webinars you want." It's like, I'll just give me a chunk and I'll take it and boom. I really want that. So that's been a lot of fun. So NetApp's been a fantastic strategic partner and we'll continue to partner with them moving forward. >> So I'm hearing a lot of collaboration, a lot of participation, energy just radiating, I think off from the main stage-- >> Oh I don't like the community, just do the watch, uncles love it. >> From the main stage to what you're talking about, what with what you guys are doing and I love to hear that the customers are being recognized for their innovation. Not just-- >> They are, yeah. >> Transforming their businesses, new revenue streams, new business models, but leveraging their partners like SAP, like NetApp, to become the intelligent enterprise and change industries. >> Absolutely, Lisa. And they're becoming the thought leaders of their own industry. So if you want to become a leader or a thought leader in your own specific industry, join the SAP HANA Community, make the investments in SAP Leonardo, work with SAP, work with NetApp, and like Bill says, let's get it done. >> Let's get it done. Scott, thanks so much for stopping by and chatting with Keith and me this morning. >> Thank you for your time, it's been my pleasure. >> And enjoy the rest of the event. >> I look forward to it. >> All right. Lisa Martin with Keith Townsend on theCUBE from the NetApp booth at SAP SAPPHIRE NOW 2018. Thanks for watching. (funky 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 shimmers) >> Good afternoon everyone, and welcome back to AWS re Invent 2022. We are live here from the show floor in Las Vegas, Nevada, we're theCUBE, my name is Savannah Peterson, joined by John Furrier, John, are you excited for the next segment? >> I love the innovation story, this next segment's going to be really interesting, an example of ecosystem innovation in action, it'll be great. >> Yeah, our next guests are actually award-winning, I am very excited about that, please welcome Alan and Becky from IBM. Thank you both so much for being here, how's the show going for ya? Becky you got a, just a platinum smile, I'm going to go to you first, how's the show so far? >> No, it's going great. There's lots of buzz, lots of excitement this year, of course, three times the number of people, but it's fantastic. >> Three times the number of people- >> (indistinct) for last year. >> That is so exciting, so what is that... Do you know what the total is then? >> I think it's over 55,000. >> Ooh, loving that. >> John: A lot. >> It's a lot, you can tell by the hallways- >> Becky: It's a lot. >> John: It's crowded, right. >> Yeah, you can tell by just the energy and the, honestly the heat in here right now is pretty good. Alan, how are you feeling on the show floor this year? >> Awesome, awesome, we're meeting a lot of partners, talking to a lot of clients. We're really kind of showing them what the new IBM, AWS relationship is all about, so, beautiful time to be here. >> Well Alan, why don't you tell us what that partnership is about, to start us off? >> Sure, sure. So the partnership started with the relationship in our consulting services, and Becky's going to talk more about that, right? And it grew, this year it grew into the IBM software realm where we signed an agreement with AWS around May timeframe this year. >> I love it, so, like you said, you're just getting started- >> Just getting started. >> This is the beginning of something magic. >> We're just scratching the surface with this right? >> Savannah: Yeah. >> But it represents a huge move for IBM to meet our clients where they are, right? Meet 'em where they are with IBM technology, enterprise technology they're used to, but with the look and feel and usage model that they're used to with AWS. >> Absolutely and so to build on that, you know, we're really excited to be an AWS Premier Consulting Partner. We've had this relationship for a little over five years with AWS, I'd say it's really gone up a notch over the last year or two as we've been working more and more closely, doubling down on our investments, doubling down on our certifications, we've got over 15,000 people certified now, almost 16,000 actually- >> Savannah: Wow. >> 14 competencies, 16 service deliveries and counting. We cover a mass of information and services from Data Analytics, IoT, AI, all the way to Modernization, SAP, Security Services, right. So it's pretty comprehensive relationship, but in addition to the fantastic clients that we both share, we're doing some really great things around joint industry solutions, which I'll talk about in a few minutes and some of those are being launched at the conference this year, so that's even better. But the most exciting thing to me right now is that we just found out that we won the Global Innovator Partner of the Year award, and a LATAM Partner of the Year award. >> Savannah: Wow. >> John: That's (indistinct) >> So, super excited for IBM Consulting to win this, we're honored and it's just a great, exciting part to the conference. >> The news coming out of this event, we know tomorrow's going to be the big keynote for the new Head of the ecosystem, Ruba. We're hearing that it's going to be all about the ecosystem, enabling value creation, enabling new kinds of solutions. We heard from the CEO of AWS, this nextGen environment's upon us, it's very solution-oriented- >> Becky: Absolutely. >> A lot of technology, it's not an either or, it's an and equation, this is a huge new shift, I won't say shift, a continuation for AWS, and you guys, we've been covering, so you got the and situation going on... Innovation solutions and innovation technology and customers can choose, build a foundation or have it out of the box. What's your reaction to that? Do you think it's going to go well for AWS and IBM? >> I think it fits well into our partnership, right? The the thing you mentioned that I gravitate to the most is the customer gets to choose and the thing that's been most amazing about the partnership, both of these companies are maniacally focused on the customer, right? And so we've seen that come about as we work on ways the customer to access our technology, consume the technology, right? We've sold software on-prem to customers before, right, now we're going to be selling SaaS on AWS because we had customers that were on AWS, we're making it so that they can more easily purchase it by being in the marketplace, making it so they can draw down their committed spin with AWS, their customers like that a lot- [John] Yeah. >> Right. We've even gone further to enable our distributor network and our resellers, 'cause a lot of our customers have those relationships, so they can buy through them. And recently we've enabled the customer to leverage their EDP, their committed spend with AWS against IBM's ELA and structure, right, so you kind of get a double commit value from a customer point of view, so the amazing part is just been all about the customers. >> Well, that's interesting, you got the technology relationship with AWS, you mentioned how they're engaging with the software consumption in marketplace, licensed deals, there's all kinds of new business model innovations on top of the consumption and building. Then you got the consulting piece, which is again, a big part of, Adam calls it "Business transformation," which is the result of digital transformation. So digital transformation is the process, the outcome is the business transformation, that's kind of where it all kind of connects. Becky, what's your thoughts on the Amazon consulting relationships? Obviously the awards are great but- >> They are, no- >> What's the next step? Where does it go from here? >> I think the best way for me to describe it is to give you some rapid flyer client examples, you know, real customer stories and I think that's where it really, rubber meets the road, right? So one of the most recent examples are IBM CEO Arvind Krishna, in his three key results actually mentioned one of our big clients with AWS which is the Department of Veterans Affairs in the US and is an AI solution that's helped automate claims processing. So the veterans are trying to get their benefits, they submit the claims, snail mail, phone calls, you know, some in person, some over email- >> Savannah: Oh, it gives me all the feels hearing you talk about this- >> It's a process that used to take 25 to 30 days depending on the complexity of the claims, we've gotten it down with AWS down to within 24 hours we can get the veterans what they need really quickly so, I mean, that's just huge. And it's an exciting story that includes data analytics, AI and automation, so that's just one example. You know, we've got examples around SAP where we've developed a next generation SAP for HANA Platform for Phillips Carbon Black hosted on AWS, right? For them, it created an integrated, scalable, digital business, that cut out a hundred percent the capital cost from on-prem solutions. We've got security solutions around architectures for telecommunications advisors and of course we have lots of examples of migration and modernization and moving workloads using Red Hat to do that. So there's a lot of great client examples, so to me, this is the heart of what we do, like you said, both companies are really focused on clients, Amazon's customer-obsessed, and doing what we can for our clients together is where we get the impact. >> Yeah, that's one of the things that, it sounds kind of cliche, "Oh we're going to work backwards from the customer," I know Amazon says that, they do, you guys are also very customer-focused but the customers are changing. So I'd love to get your reaction because we're now in that cloud 2.0, I call that 2.0 or you got the Amazon Classic, my word, and then Next Gen Cloud coming, the customers are different, they're transforming because IT's not a department anymore, it's in the DevOps pipeline. The developers are driving a lot of IT but security and on DataOps, it's the structural change happening at the customer, how do you guys see that at IBM? I know we cover a lot of Red Hat and Arvind talks to us all the time, meeting the customer where they are, where are they? Where are the customers? Can you share your perspective on where they are? >> It's an astute observation, right, the customer is changing. We have both of those sets of customers, right, we still have the traditional customer, our relationship with Central IT, right, and driving governance and all of those things. But the folks that are innovating many times they're in the line of business, they're discovering solutions, they're building new things. And so we need our offerings to be available to them. We need them to understand how to use them and be convenient for these guys and take them through that process. So that change in the customer is one that we are embracing by making our offerings easy to consume, easy to use, and easy to build into solutions and then easy to parlay into what central IT needs to do for governance, compliance, and these types of things, it's becoming our new bread and butter. >> And what's really cool is- >> Is that easy button- >> We've been talking about- >> It's the easy button. >> The easy button a lot on the show this week and if you just, you just described it it's exactly what people want, go on Becky. >> Sorry about that, I was going to say, the cool part is that we're co-creating these things with our clients. So we're using things like the Amazon Working Backward that you just mentioned.` We're using the IBM garage methodology to get innovative to do design working, design thinking workshops, and think about where is that end user?, Where is that stakeholder? Where are they, they thinking, feeling, doing, saying how do we make the easier? How do we get the easy button for them so that they can have the right solutions for their businesses. We work mostly with lines of business in my part of the organization, and they're hungry for that. >> You know, we had a quote on theCUBE yesterday, Savannah remember one of our guests said, you know, back in the, you know, 1990s or two 2000s, if you had four production apps, it was considered complex >> Savannah: Yeah. >> You know, now you got hundreds of workloads, thousands of workloads, so, you know, this end-to-end vision that we heard that's playing out is getting more complex, but the easy button is where these abstraction layers and technology could come in. So it's getting more complex because there's more stuff but it's getting easier because- >> Savannah: What is the magnitude? >> You can make it easier. This is a dynamic, share your thoughts on that. >> It's getting more complex because our clients need to move faster, right, they need to be more agile, right, so not only are there thousands of applications there are hundreds of thousands microservices that are composing those applications. So they need capabilities that help them not just build but govern that structure and put the right compliance over that structure. So this relationship- >> Savannah: Lines of governance, yeah- >> This relationship we built with AWS is in our key areas, it's a strategic move, not a small thing for us, it covers things like automation and integration where you need to build that way. It covers things like data and AI where you need to do the analytics, even things like sustainability where we're totally aligned with what AWS is talking about and trying to do, right, so it's really a good match made there. >> John: It really sounds awesome. >> Yeah, it's clear. I want to dig in a little bit, I love the term, and I saw it in my, it stuck out to me in the notes right away, getting ready for you all, "maniacal", maniacal about the customer, maniacal about the community, I think that's really clear when we're talking about 24 days to 24 hours, like the veteran example that you gave right there, which I genuinely felt in my heart. These are the types of collaborations that really impact people's lives, tell me about some of the other trends or maybe a couple other examples you might have because I think sometimes when our head's in the clouds, we talk a lot about the tech and the functionality, we forget it's touching every single person walking around us, probably in a different way right now than we may even be aware- >> I think one of the things that's been, and our clients have been asking us for, is to help coming into this new era, right, so we've come out of a pandemic where a lot of them had to do some really, really basic quick decisions. Okay, "Contact Center, everyone work from home now." Okay, how do we do that? Okay, so we cobbled something together, now we're back, so what do we do? How do we create digital transformation around that so that we are going forward in a really positive way that works for our clients or for our contact center reps who are maybe used to working from home now versus what our clients need, the response times they need, and AWS has all the technology that we're working with like Amazon Connect to be able to pull those things together with some of our software like Watson Assistant. So those types of solutions are coming together out of that need and now we're moving into the trend where economy's getting tougher, right? More cost cutting potentially is coming, right, better efficiencies, how do we leverage our solutions and help our clients and customers do that? So I think that's what the customer obsession's about, is making sure we really understand where their pain points are, and not just solve them but maybe get rid of 'em. >> John: Yeah, great one. >> Yeah. And not developing in a silo, I mean, it's a classic subway problem, you got to be communicating with your community if you want to continue to serve them. And IBM's been serving their community for a very long time, which is super impressive, do you think they're ready for the challenge? >> Let's do it. >> So we have a new thing on theCUBE. >> Becky: Oh boy. >> We didn't warn you about this, but here we go. Although you told, Alan, you've mentioned you're feeling very cool with the microphone on, so I feel like, I'm going to put you in the hot seat first on this one. Not that I don't think Becky's going to smash it, but I feel like you're channeling the power of the microphone. New challenges, treat it like a 32nd Instagram reel-style story, a hot take, your thought leadership, money clip, you know, this is your moment. What is the biggest takeaway, most important thing happening at the show this year? >> Most important thing happening at the show? Well, I'm glad you mentioned it that way, because earlier you said we may have to sing (presenters and guests all laughing) >> So this is much better than- >> That's actually part of the close. >> John: Hey, hey. >> Don't worry, don't worry, I haven't forgotten that, it's your Instagram reel, go. (Savannah laughs) >> Original audio happening here on theCUBE, courtesy of Alan and IBM, I am so here for it. >> So what my takeaway and what I would like for the audience to take away, out of this conversation especially, but even broadly, the IBM AWS relationship is really like a landmark type of relationship, right? It's one of the biggest that we've established on both sides, right- >> Savannah: It seems huge, okay you are too monolith in the world of companies, like, yeah- >> Becky: Totally. >> It's huge. And it represents a strategic change on both sides, right? With that customer- >> Savannah: Fundamentally- >> In the middle right? >> Savannah: Yeah. >> So we're seeing things like, you know, AWS is working with us to make sure we're building products the way that a AWS client likes to consume them, right, so that we have the right integration, so they get that right look and feel, but they still get the enterprise level capabilities they're used to from IBM, right? So the big takeaway I like for people to take, is this is a new IBM, it's a new AWS and IBM relationship, and so expect more of that goodness, more of those new things coming out of it. [John] Excellent, wow. >> That was great, well done, you nailed it. and you're going to finish with some acapella, right? (Alan laughs) >> You got a pitch pipe ready? (everyone laughs) >> All right Becky, what about you? Give us your hot take. >> Well, so for me, the biggest takeaway is just the way this relationship has grown so much, so, like you said, it's the new IBM it's the new AWS, we were here last year, we had some good things, this year we're back at the show with joint solutions, have been jointly funded and co-created by AWS and IBM. This is huge, this is a really big opportunity and a really big deal that these two companies have come together, identified joint customer needs and we're going after 'em together and we're putting 'em in the booth. >> Savannah: So cool. And there's things like smart edge for welding solutions that are out there. >> Savannah: Yes. >> You know, I talked about, and it's, you know you wouldn't think, "Okay, well what's that?" There's a lot to that, a lot of saving when you look at how you do welding and if you apply things like visual AI and auditory AI to make sure a weld is good. I mean, I think these are, these things are cool, I geek out on these things- >> John: Every vertical. >> I'm geeking out with you right now, just geeking- >> Yeah, yeah, yeah, so- >> Every vertical is infected. >> They are and it's so impactful to have AWS just in lockstep with us, doing these solutions, it's so different from, you know, you kind of create something that you think your customers like and then you put it out there. >> Yeah, versus this moment. >> Yeah, they're better together. >> It's strategic partnership- >> It's truly a strategic partnership. and we're really bringing that this year to reinvent and so I'm super excited about that. >> Congratulations. >> Wow, well, congratulations again on your awards, on your new partnership, I can't wait to hear, I mean, we're seven months in, eight months in to this this SaaS side of the partnership, can't wait to see what we're going to be talking about next year when we have you back on theCUBE. >> I know. >> and maybe again in between now and then. Alan, Becky, thank you both so much for being here, this was truly a joy and I'm sure you gave folks a taste of the new IBM, practicing what you preach. >> John: Great momentum. >> And I'm just, I'm so impressed with the two companies collaborating, for those of us OGs in tech, the big companies never collaborated before- >> Yeah. >> John: Yeah. Joint, co-created solutions. >> And you have friction between products and everything else. I mean's it's really, co-collaboration is, it's a big theme for us at all the shows we've been doing this year but it's just nice to see it in practice too, it's an entirely different thing, so well done. >> Well it's what gets me out of the bed in the morning. >> All right, congratulations. >> Very clearly, your energy is contagious and I love it and yeah, this has been great. Thank all of you at home or at work or on the International Space Station or wherever you might be tuning in from today for joining us, here in Las Vegas at AWS re Invent where we are live from the show floor, wall-to-wall coverage for three days with John Furrier. My name is Savannah Peterson, we're theCUBE, the source for high tech coverage. (cheerful 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)

from the cube studios in Palo Alto in Boston bringing you data-driven insights from the cube and ETR this is breaking analysis with Dave vellante over the past decade cloudflare has built a Global Network that has the potential to become the fourth us-based hyperscale class cloud in our view the company is building a durable Revenue model with hooks into many important markets these include the more mature DDOS protection space to other growth sectors such as zero trust a serverless platform for application development and an increasing number of services such as database and object storage and other network services in essence cloudflare could be thought of as a giant distributed supercomputer that can connect multiple clouds and act as a highly efficient scheduling engine at scale its disruptive DNA is increasingly attracting novel startups and established Global firms alike looking for Reliable secure high performance low latency and more cost-effective alternatives to AWS and Legacy infrastructure Solutions hello and welcome to this week's wikibon Cube insights powered by ETR in this breaking analysis we initiate our deeper coverage of cloudflare we'll briefly explain our take on the company and its unique business model we'll then share some peer comparisons with both the financial snapshot and some fresh ETR survey data finally we'll share some examples of how we think cloudflare could be a disruptive force with a super cloud-like offering that in many respects is what multi-cloud should have been cloudflare has been on our peripheral radar Ben Thompson and many others have written about their disruptive business model and recently a breaking analysis follower who will remain anonymous emailed with some excellent insights on cloudflare that prompted us to initiate more detailed coverage let's first take a look at how cloudflare seize the world in terms of its view of a modern stack this is a graphic from cloudflare that shows a simple three-layer Stack comprising Storage and compute the lower level and application layer and the network and their key message is basically that the big four hyperscalers have replaced the on-prem leaders apps have been satisfied and that mess of network that you see and Security in the upper left can now be handled all by cloudflare and the stack can be rented via Opex versus requiring heavy capex investment so okay somewhat of a simplified view is those companies on the the left are you know not standing still and we're going to come back to that but cloudflare has done something quite amazing I mean it's been a while since we've invoked Russ hanneman of Silicon Valley Fame on breaking analysis but remember when he was in a meeting one of his first meetings if not the first with Richard Hendricks it was the whiz kid on the show Silicon Valley and hanneman said something like if you had a blank check and you could build anything in the world what would it be and Richard's answer was basically a new internet and that led to Pied Piper this peer-to-peer Network powered by decentralized devices and and iPhones and this amazing compression algorithm that enabled high-speed data movement and low latency uh up to no low latency access across the network well in a way that's what cloudflare has built its founding premise reimagined how the internet should be built with a consistent set of server infrastructure where each server had lots of cores lots of dram lots of cash fast ssds and plenty of network connectivity and bandwidth and well this picture makes it look like a bunch of dots and points of presence on a map which of course it is there's a software layer that enables cloudflare to efficiently allocate resources across this Global Network the company claims that it's Network utilization is in the 70 percent range and it has used its build out to enter the technology space from the bottoms up offering for example free tiers of services to users with multiple entry points on different services and selling then more services over time to a customer which of course drives up its average contract value and its lifetime value at the same time the company continues to innovate and add new services at a very rapid cloud-like Pace you can think of cloudflare's initial Market entry as like a lightweight Cisco as a service the company's CFO actually he uses that term he calls it that which really must tick off Cisco who of course has a massive portfolio and a dominant Market position now because it owns the network cloudflare is a marginal cost of adding new Services is very small and goes towards zero so it's able to get software like economics at scale despite all this infrastructure that's building out so it doesn't have to constantly face the increasing infrastructure tax snowflake for example doesn't own its own network infrastructure as it grows it relies on AWS or Azure gcp and and while it gives the company obvious advantages it doesn't have to build out its own network it also requires them to constantly pay the tax and negotiate with hyperscalers for better rental rates now as previously mentioned Cloud Fair cloudflare claims that its utilization is very high probably higher than the hyperscalers who can spin up servers that they can charge for underutilized customer capacity cloudflare also has excellent Network traffic data that it can use to its Advantage with its Analytics the company has been rapidly innovating Beyond its original Core Business adding as I said before serverless zero trust offerings it has announced a database it calls its database D1 that's pretty creative and it's announced an object store called R2 that is S3 minus one both from the alphabet and the numeric I.E minus the egress cost saying no egress cost that's their big claim to fame and they've made a lot of marketing noise around about that and of course they've promised in our a D2 database which of course is R2D2 RR they've launched a developer platform cloudflare can be thought of kind of like first of all a modern CDN they've got a simpler security model that's how they compete for example with z-scaler that brings uh they also bring VPN sd-wan and DDOS protection services that are that are part of the network and they're less expensive than AWS that's kind of their sort of go to market and messaging and value proposition and they're positioning themselves as a neutral Network that can connect across multiple clouds now to be clear unlike AWS in particular cloudflare is not well suited to lift and shift your traditional apps like for instance sap Hana you're not going to run that in on cloudflare's platform rather the company started by making websites more secure and faster and it flew under the radar and much in the same way that clay Christensen described the disruption in the steel industry if you've seen that where new entrants picked off the low margin rebar business then moved up the stack we've used that analogy in the semiconductor business with arm and and even China cloudflare is running a similar playbook in the cloud and in the network so in the early part of the last decade as aws's ascendancy was becoming more clear many of us started thinking about how and where firms could compete and add value as AWS is becoming so dominant so for instance take an industry Focus you could do things like data sharing with snowflake eventually you know uh popularized you could build on top of clouds again snowflake is doing that as are others you could build private clouds and of course connect to hybrid clouds but not many had the wherewithal and or the hutzpah to build out a Global Network that could serve as a connecting platform for cloud services cloudflare has traction in the market as it adds new services like zero trust and object store or database its Tam continues to grow here's a quick snapshot of cloudflare's financials relative to Z scalar which is both a competitor and a customer fastly which is a smaller CDN and Akamai a more mature CDN slash Edge platform cloudflare and fastly both reported earnings this past week Cloud Fair Cloud flare surpassed a billion dollar Revenue run rate but they gave tepid guidance and the stock got absolutely crushed today which is Friday but the company's business model is sound it's growing close to 50 annually it has sas-like gross margins in the mid to high 70s and it's it it's got a very strong balance sheet and a 13x revenue run rate multiple in fact it's Financial snapshot is quite close to that of z-scaler which is kind of interesting which zinc sailor of course doesn't own its own network that's a pure play software company fastly is much smaller and growing more slowly than cloudflare hence its lower multiple well Akamai as you can see is a more mature company but it's got a nice business now on its earnings call this week cloudflare announced that its head of sales was stepping down and the company has brought in a new leader to take the firm to five billion dollars in sales I think actually its current sales leader felt like hey you know my work is done here bring on somebody else to take it to the next level the company is promising to be free cash flow positive by the end of the year and is working hard toward its long-term financial model or so working towards sorry it's a long-term financial model with gross margin Targets in the mid 70s it's targeting 20 non-gaap operating margins so so solid you know very solid not like completely off the charts but you know very good and to our knowledge it has not committed to a long-term growth rate but at that sort of operating profit level you would like to see growth be consistently at least in the 20 range so they could at least be a rule of 40 company or perhaps even even five even higher if they're going to continue to command a premium valuation okay let's take a look at the ETR data ETR is very positive on cloudflare and has recently published a report on the company like many companies cloudflare is seeing an across the board slowdown in spending velocity we've reported on this quite extensively using the ETR data to quantify the degree to that Slowdown and on the data set with ETR we see that many customers they're shifting their spend to Flat spend you know plus or minus let's say you know single digits you know two three percent or even zero or in the market we're seeing a shift from paid to free tiers remember cloudflare offers a lot of free services as you're seeing customers maybe turn off the pay for a while and going with the freebie but we're also seeing some larger customers in the data and the fortune 1000 specifically they're actually spending more which was confirmed on cloudflare's earnings call they did say everything across the board was softer but they did also indicate that some of their larger customers are actually growing faster than their smaller customers and their churn is very very low here's a two-dimensional graphic we'd like to share this view a lot it's got Net score or spending momentum on the vertical axis and overlap or pervasiveness in the survey on the horizontal axis and this cut isolates three segments in the etrs taxonomy that cloudflare plays in Cloud security and networking now the table inserted in that upper left there shows the raw data which informs the position of each company in the dots with Net score in the ends listed in that rightmost column the red dotted line indicates a highly elevated Net score and finally we posted the breakdown those colors in the bottom right of cloudflare's Net score the lime green that's new adoptions the forest green is we're spending more six percent or more the gray is flat plus or minus uh five percent and you can see that the majority of customers you can see that's the majority of the customers that gray area the pink is we're spending Less in other words down six percent or worse and the bright red is churn which is minimal one percent very good indicator for for cloudflare what you do to get etr's proprietary Net score and they've done this for many many quarters so we have that time series data you subtract the Reds from the greens and that's Net score cloudflare is at 39 just under that magic red line now note that cloudflare and zscaler are right on top of each other Cisco has a dominant position on the x-axis that cloudflare and others are eyeing AWS is also dominant but note that its Net score is well above the red dotted line it's incredible Palo Alto networks is also very impressive it's got both a strong presence on the horizontal axis and it's got a Net score that's pretty comparable to cloudflare and z-scaler to much smaller companies Akamai is actually well positioned for a reasonably mature company and you can see fastly ATT Juniper and F5 have far less spending momentum on their platforms than does cloudflare but at least they are in positive Net score territory so what's going to be really interesting to see is whether cloudflare can continue to hold this momentum or even accelerate it as we've seen with some other clouds as it scales its Network and keeps adding more and more services cloudflare has a couple of potential strategic vectors that we want to talk about and it'll be going to be interesting to see how that plays out Now One path is to compete more directly as a Cloud Player offering secure access Edge services like firewall as a service and zero Trust Services like data loss prevention email security from its area one acquisition and other zero trust offerings as well as Network Services like routing and network connectivity this is The Sweet Spot of the company load balancing many others and then add in things like Object Store and database Services more Edge services in the future it might be telecom like services such as Network switching for offices so that's one route and cloudflare is clearly on that path more services more cohorts at innovating and and growing the company and bringing in more Revenue increasing acvs and and increasing long-term value and keeping retention high now the other Vector is what we're just going to refer to as super cloud as an enabler of cross-cloud infrastructure this is new value uh relative to the former Vector that we were just talking about now the title of this episode is what multi-cloud should have been meaning cloudflare could be the control plane providing a consistent experience across clouds one that is fast and secure at global scale now to give you Insight on this let's take a look at some of the comments made by Matthew Prince the CEO and co-founder of cloudflare cloudflare put its R2 Object Store into public beta this past May and I believe it's storing around a petabyte of data today I think that's what they said in their call here's what Prince said about that quote we are talking to very large companies about moving more and more of their stored objects to where we can store that with R2 and one of the benefits is not only can we help them save money on the egress fees but it allows them to then use those object stores or objects across any of the different Cloud platforms they're that they're using so by being that neutral third party we can let people adopt a little bit of Amazon a little bit of Microsoft a little bit of Google a little bit of SAS vendors and share that data across all those different places so what's interesting about this in the super cloud context is it suggests that customers could take the best of each Cloud to power their digital businesses I might like AWS for in redshift for my analytic database or I love Google's machine learning Microsoft's collaboration and I'd like a consistent way to connect those resources but of course he's strongly hinting and has made many public statements that aws's egress fees are a blocker to that vision now at a recent investor event Matthew Prince added some color to this concept when he talked about one metric of success being how much R2 capacity was consumed and how much they sold but perhaps a more interesting Benchmark is highlighted by the following statement that he made he said a completely different measure of success for R2 is Andy jassy says I'm sick and tired of these guys meaning cloudflare taking our objects away we're dropping our egress fees to zero I would be so excited because we've then unlocked the ability to be the network that interconnects the cloud together now of course it would be Adam solipski who would be saying that or maybe Andy Jesse you know still watching over AWS and I think it's highly unlikely that that's going to happen anytime soon and that of course but but in theory gets us closer to the super cloud value proposition and to further drive that point home and we're paraphrasing a little bit his comments here he said something the effect of quote customers need one consistent control plane across clouds and we are the neutral Network that can be consistent no matter which Cloud you're using interesting right that Prince sees the world that's similar to if not nearly identical to the concepts that the cube Community has been putting forth around supercloud now this vision is a ways off let's be real Prince even suggested that his initial vision of an application running across multiple clouds you know that's like super cloud Nirvana isn't what customers are doing today that's that's really hard to do and perhaps you know it's never going to happen but there's a little doubt that cloudflare could be and is positioning itself as that cross-cloud control plane it has the network economics and the business model levers to pull it's got an edge up on the competition at the edge pun intended cloudflare is the definition of Edge and it's distributed platform it's decentralized platform is much better suited for Edge workloads than these giant data centers that are you know set up to to try and handle that today the the hyperscalers are building out you know their Edge networks things like outposts you know going out to the edge and other local zones Etc now cloudflare is increasingly competitive to the hyperscalers and those traditional Stacks that it depositioned on an earlier slide that we showed but you know the likes of AWS and Dell and hpe and Cisco and those others they're not sitting in their hands they have a huge huge customer install bases and they are definitely a moving Target they're investing and they're building out their own Super clouds with really robust stacks as well let's face it it's going to take a decade or more for Enterprises to adopt a developer platform or a new database Cloud plus cloudflare's capabilities when compared to incumbent stacks and the hyperscalers is much less robust in these areas and even in storage you know despite all the great conversation that R2 generated and the buzz you take a specialist like Wasabi they're more mature they're more functional and they're way cheaper even than cloudflare so you know it's not a fake a complete that cloudflare is going to win in those markets but we love the disruption and if cloudflare wants to be the fourth us-based hyperscaler or join the the big four as the as the fifth if we put Alibaba in the mix it's got a lot of work to do in the ecosystem by its own admission as much to learn and is part of the value by the way that it sees in its area one acquisition it's email security company that it bought but even in that case much of the emphasis has been on reseller channels compare that to the AWS ecosystem which is not only a channel play but is as much an innovation flywheel filling gaps where companies like snowflake Thrive side by side with aws's data stores as well all the on-prem stacks are building hybrid connections to AWS and other clouds as a means of providing consistent experiences across clouds indeed many of them see what they call cross-cloud services or what we call super cloud hyper cloud or whatever you know Mega Cloud you want to call it we use super cloud they are really eyeing that opportunity so very few companies frankly are not going after that space but we're going to close with this cloudflare is one of those companies that's in a position to wake up each morning and ask who can we disrupt today and very few companies are in a position to disrupt the hyperscalers to the degree that cloudflare is and that my friends is going to be fascinating to watch unfold all right let's call it a wrap I want to thank Alex Meyerson who's on production and manages the podcast as well as Ken schiffman who's our newest addition to the Boston Studio Kristen Martin and Cheryl Knight help us get the word out on social media and in our newsletters and Rob Hof is our editor-in-chief over at silicon angle thank you to all remember all these episodes are available as podcasts wherever you listen all you're going to do is search breaking analysis podcasts I publish each week on wikibon.com and siliconangle.com you can email me at david.velante at siliconangle.com or DM me at divalante if you comment on my LinkedIn posts and please do check out etr.ai they got the best survey data in the Enterprise Tech business this is Dave vellante for the cube insights powered by ETR thank you very much for watching and we'll see you next time on breaking analysis

>>Okay, welcome back to everyone. Cube's live coverage of VMware Explorer, 2022. I'm John fur, host of the cube. Two sets three days of live coverage. Dave Ante's here. Lisa Martin, Dave Nicholson, all host of the cube 12 interviews today, just we're with Rocklin and rolling, getting down to the end of the show. As we wind down and look back and look at the future. We've got Steven Jones. Here's the general manager of the VMware cloud on AWS. He's with Amazon web service. Steven Jones. Welcome to the cube. >>Thanks John. >>Welcome back cube alumni. I've been on many times going back to 2015. Yeah. >>Pleasure to be here. Great >>To see you again. Thanks for coming on. Obviously 10 years at AWS, what a ride is that's been, come on. That's fantastic. Tell me it's been crazy. >>Wow. Learned a lot of stuff along the way, right? I mean, we, we, we knew that there was a lot of opportunity, right? Customers wanting the agility and flexibility of, of the cloud and, and we, we still think it's early days, right? I mean, you'll hear Andy say that animals say that, but it really is. Right. If you look at even just the amount of spend that's being spent on, on clouds, it's in the billions, right. And the amount of, of spend in it is still in the trillion. So there's, there's a long way to go and customers are pushing us hard. Obviously >>It's been interesting a lot going on with VM. We're obviously around with them, obviously changing the strategy with their, their third generation and their narrative. Obviously the Broadcom thing is going on around them. And 10 years at abs, we've been, we've been, this'll be our ninth year, no 10th year at reinvent coming up for us. So, but it's 10 years of everything at Amazon, 10 years of S three, 10 years of C two. So if you look at the, the marks of time, now, the history books are starting to be written about Amazon web services. You know, it's about 10 years of full throttle cube hyperscaler in action. I mean, I'm talking about real growth, like >>Hardcore, for sure. I'll give you just one anecdote. So when I first joined, I think we had maybe two EC two instances back in the day and the maximum amount of memory you could conversion into one of these machines was I think 128 gig of Ram fast forward to today. You literally can get a machine with 24 terabytes of Ram just in insane amounts. Right? My, my son who's a gamer tells me he's got 16 gig in his, in his PC. You need to, he thinks that's a lot. >>Yeah. >>That's >>Excited about that. That's not even on his graphics card. I mean, he's, I know it's coming next. The GPU, I mean, just all >>The it's like, right? >>I mean, all the hardware innovation that you guys have done, I mean, look at every it's changed. Everyone's changed their strategy to copy AWS nitro, Dave ante. And I talk about this all the time, especially with James Hamilton and the team over there, Peter DeSantos, these guys have, are constantly going at the atoms and innovating at the, at the level. I mean that, that's how hardcore it is over there right now. I mean, and the advances on the Silicon graviton performance wise is crazy. I mean, so what does that enabling? So given that's continuing, you guys are continuing to do great work there on the CapEx side, we think that's enabling another set of new net new applications because we're starting to see new things emerge. We saw snowflake come on, customer of AWS refactor, the data warehouse, they call it a data cloud. You're starting to see Goldman Sachs. You see capital one, you see enterprise customers building on top of AWS and building a cloud business without spending the CapEx >>Is exactly right. And Ziggy mentioned graviton. So graviton is one of our fastest growing compute families now. And you know, you mentioned a couple of ISVs and partners of ours who are leaning in heavily on porting their own software. Every event Adam announced that we're working with SAP to, to help them port their HANA cloud, which is a, a database of service offering HANA flagship to graviton as well. So it's, it's definitely changing. >>And I think, you know, one of the, and we're gonna circle back to VMware is kind of a point to this. This conversation is that, is that if you look at the trends, right, okay. VMware really tried hard to do cloud and they had a good shot at it V cloud air, but it just, they didn't have the momentum that you guys had at AWS. We saw a lot, lot of other stragglers try to do cloud. They fell off the road, OpenStack, HP, and the list goes on and on. I don't wanna get into that, but the point is, as you guys become more powerful and you're open, right? So you have open ecosystem, you have people now coming back, taking advantage and refactoring and picking up where they left off. VMware was the one of the first companies that actually said, you know what pat Gelsinger said? And I was there, let's clear up the positioning. Let's go all in with AWS. That's >>Right >>At that time, 2016. >>Yeah. This was new for us, for >>Sure. And then now that's set the standard. Now everybody else is kind of doing it. Where is the VMware cloud relationship right now? How is that going out? State's worked. >>It's working well very well. It's I mean, we're celebrating, I think we made the announcement what, five years ago at this conference. Yeah. 2016. So, I mean, it's, it's been a tremendous ride. The best part are the customers who were coming and adopting and proving to us that our vision back then was the right vision. And, and, and what's been different. I think about this relationship. And it was new for us was that we, we purposely went after a jointly engineered solution. This wasn't a, we've got a, a customer or a partner that's just going to run and build something on us. This is something where we both bring muscle and we actually build a, a joint offering together. Talk about, about the main difference. >>Yeah. And that, and that's been working, but now here at this show, if you look at, if you squint through the multi-cloud thing, which is like just, I think positioning for, you know, what could happen in, in a post broad Broadcom world, the cloud native has traction they're Tansu where, where customers were leaning in. So their enterprise customer is what I call the classic. It, you know, mainstream enterprise, which you guys have been doing a lot of business with. They're now thinking, okay, I'm gonna go on continu, accelerate on, in the public cloud, but I'm gonna have hybrid on premise as well. You guys have that solution. Now they're gonna need cloud native. And we were speculating that VMware is probably not gonna be able to get 'em all of it. And, and that there's a lot more cloud native options as customers want more cloud native. How do you see that piece on Amazon side? Because there's a lot of benefits between the VMware cloud on AWS and the services that you guys have natively in your cloud. So we see customers really taking advantage of the AWS goodness, as well as expanding the cloud side at VMware cloud on AWS. >>Yeah. There's probably two ways I would look at this. Right? So, so one is the combination of VMware cloud on AWS. And then both native services just generally brings more options to customers. And so typically what we're seeing now is customers are just able to move much faster, especially as it comes to data center, evacuations, migrating all their assets, right? So it used to be that, and still some customers they're like, I I've gotta think through my entire portfolio of applications and decide what to refactor. And the only way I can move it to cloud is to actually refactor it into some net new application, more and more. We're actually seeing customers. They've got their assets. A lot of them are still on premises in a VMware state, right. They can move those super quick and then modernize those. And so I think where you'll see VMware and AWS very aligned is on this, this idea of migrate. Now you need to get the benefits of TCO and, and the agility that comes with being in the cloud and then modernize. We took a step further, which is, and I think VMware would agree here too, but all of the, the myriad of services, I think it's 200 plus now AWS native services are for use right alongside any that a customer wants to run in VMware. And so we have examples of customers that are doing just, >>And that's, that's how you guys see the native and, and VMware cloud integrating in. Yeah, that's, that's important because this, I mean, if I always joke about, you know, we've been here 12 years listening in the hallways and stuff, you know, on the bus to the event last night, walking the parties and whatnot, listening in the streets, there's kind of two conversations that rise right to the top. And I wanna get your reaction to this Steven, because this seems to be representative of this demographic here at VMware conference, there's conversations around ransomware and storage and D dub and recovery. It's all, a lot of those happen. Yeah. Clearly a big crowd here that care about, you know, Veeam and NetApp and storage and like making sure stuff's secure and air gapped. And a lot of that kind of, I call nerdy conversations and then the other one is, okay, I gotta get the cloud story. >>Right. So there's kind of the operational security. And then there's like, okay, what's my path to true cloud. I need to get this moving. I need to have better applications. My company is the application now not it serves some sort of back office function. Yeah. It's like, my company is completely using technology as its business. So the app is the business. So that means everything's technology driven, not departmental siloed. So there's a, that's what I call the true cloud conversation. How do you, how do you see that evolving because VMware customers are now going there. And I won't say, I won't say they're behind, but they're certainly going there faster than ever before. >>I think, I think, I mean, it's an interesting con it's an interesting way to put it and I, I would completely agree. I think it's, it's very clear that I think a lot of customer companies are actually being disrupted. Right. And they have to move fast and reinvent themselves. You said the app is now becoming the company. Right. I mean, if, if you look at where not too many years back, there were, you know, big companies like Netflix that were born in the cloud. Right. Airbnb they're disruptors. >>There's, that's the >>App, right? That's the app. Yeah. So I, I would exactly agree. And, and that's who other companies are competing with. And so they have to move quickly. You talked about some, some technology that allows them to do that, right? So this week we announced the general availability of a NetApp on tap solution. It's been available on AWS for some time as a fully managed FSX storage solution. But now customers can actually leverage it with, with VMC. Now, why is that important? Well, there's tens of thousands of customers running VMware. On-premises still, there's thousands of them that are actually using NetApp filers, right? NetApp, NetApp filers, and the same enterprise features like replication. D do you were talking about and Snapp and clone. Those types of things can be done. Now within the V VMware state on AWS, what's even better is they can actually move faster. So consider replicating all this, you know, petabytes and petabytes of data that are in these S from on-premises into AWS, this, this NetApp service, and then connected connecting that up to the BMC option. So it just allows customers much, much. >>You guys, you guys have always been customer focus. Every time I sat down with the Andy jazzy and then last year with Adam, same thing we worked back from, I know it's kind of a canned answer on some of the questions from media, but, but they do really care. I've had those conversations. You guys do work backwards from the customer, actually have documents called working backwards. But one of the things that I observed, we talked about here yesterday on the cube was the observations of reinvent versus say, VM world. Now explore is VM world's ecosystem was very partner-centric in the sense of the partners needed to rely on VMware. And the customers came here for both more of the partners, not so much VMware in the sense there wasn't as much, many, many announcements can compare that to the past, say eight years of reinvent, where there's so much Amazon action going on the partners, I won't say take as a second, has a backseat to Amazon, but the, the attendees go there generally for what's going on with AWS, because there's always new stuff coming out. >>And it's, it's amazing. But this year it starts to see that there's an overlap or, or change between like the VMware ecosystem. And now Amazon there's, a lot of our interviews are like, they're on both ecosystems. They're at Amazon's show they're here. So you start to see what I call the naturalization of partners. You guys are continuing to grow, and you'll probably still have thousands of announcements at the event this year, as you always do, but the partners are much more part of the AWS equation, not just we're leasing all these new services and, and oh, for sure. Look at us, look at Amazon. We're growing. Cause you guys were building out and look, the growth has been great. But now as you guys get to this next level, the partners are integral to the ecosystem. How do you look at that? How has Amazon thinking about that? I know there's been some, some, a lot of active reorgs around AWS around solving this problem or no solve the problem, addressing the need and this next level of growth. What's your reaction to >>That? Well, I mean, it's, it's a, it's a good point. So I have to be honest with you, John. I, I, I spent eight of my 10 years so far at AWS within the partner organization. So partners are very near and dear to my heart. We've got tens of thousands of partners and you are you're right. You're starting to see some overlap now between the VMware partner ecosystem and what we've built now in AWS and partners are big >>By the way, you sell out every reinvent. So it's, you have a lot of partners. I'm not suggesting that you, that there's no partner network there, but >>Partners are critical. I mean, absolutely naturally we want a relationship with a customer, but in order to scale the way we need to do to meet the, the needs of customers, we need partners. Right. We, we can't, we can't interact with every single customer as much as we would like to. Right. And so partners have long built teams and expertise that, that caters to even niche workloads or opportunity areas. And, and we love partners >>For that. Yeah. I know you guys do. And also we'll point out just to kind of give props to you guys on the partner side, you don't, you keep that top of the stack open on Amazon. You've done some stuff for end to end where customers want all Amazon, but for the most part, you let competition come in, even on, so you guys are definitely partner friendly. I'm just observing more the maturization of partners within the reinvent ecosystem, cuz we're there every year. I mean, it's, I mean, first of all, they're all buzzing. I mean, it's not like there's no action. There's a lot of customers there it's sold out as big numbers, but it just seems that the partners are much more integrated into the value proposition of at a AWS because of the, the rising tide and, and now their enablement, cuz now they're part of the, of the value proposition. Even more than ever before >>They, they really are. And they, and they're building a lot of capabilities and services on us. And so their customers are our customers. And like you say, it's rising tide, right. We, we all do better together. >>Okay. So let's talk about the VMware cloud here. What's the update here in terms of the show, what's your, what's your main focus cuz a lot of people here are doing, doing sessions. What's been some of the con content that you guys are producing here. >>Yeah. So the best part obviously is a always the customer conversations to partner conversations. So a, a lot of, a lot of sessions there, we did keynote yesterday in Ryan and I, where we talked about a number of announcements that are, I think pretty material now to the offering a joint announcement with NetApp yesterday as well around the storage solution I was talking about. And then some, some really good technical deep dives on how the offering works. Customers are still interested in like how, how do I take what I've got on premises and easily move into AWS and technology like HSX H CX solution with VMware makes it really easy without having to re IP applications. I mean, you know, it is super difficult sometimes to, to move an application. If you've got figure out where all the firewall rules are and re iPing those, those things source. But yeah, it's, it's been fantastic. >>A lot of migrations to the cloud too. A lot of cloud action, new cloud action. You guys have probably seen an uptake on services right on the native side. >>Yes. Yes. For sure. So maybe I just outlined some of the, some of the assets we made this week. So absolutely >>Go ahead. >>We, we announced a new instance family as a, a major workhorse underneath the VMware cloud offering called I, I, you mentioned nitro earlier, this is on, based on our latest generation of nitro, which allows us to offer as you know, bare metal instances, which is, which is what VMware actually VMware was our first partnership and customer that I would say actually drove us to really get Nira done and out the door. And we've continued to iterate on that. And so this I four, I instance, it's based on the, the latest Intel isolate processor with more than double the Ram double the compute, a whopping 75 gigabytes per second network. So it's a real powerhouse. The cool thing is that with the, with the NetApp storage solution that we, we discussed, we're now disaggregating the need to provision, compute and storage at the same time. It used to be, if you wanted to add more storage to your VSAN array, that was on a V VMware cloud. Yeah. You'd add another note. You might not need more compute for memory. You'd have to add another note. And so now customers can simply start adding chunks of storage. And so this opens up customers. I had a customer come to me yesterday and said, there's no reason for us not to move. Now. We were waiting for something that like this, that allowed us to move our data heavy workloads yeah. Into VMware cloud. It's >>Like, it's like the, the alignment. You mentioned alignment earlier. You know, I would say that VMware customers are lined up now almost perfectly with the hybrid story that's that's seamless or somewhat seems it's never truly seamless. But if you look at like what Deepak's doing with Kubernetes and open source, you, you guys have that there talking that big here, you got vs a eight vSphere, eight out it's all cloud native. So that's lined up with what you guys are doing on your services and the horsepower. They have their stuff, you have yours that works better together. So it seems like it's more lined up than ever before. What's your take on that? Do you agree? And, and if so, what folks watching here that are VMware customers, what's, what's the motivation now to go faster? >>Look, it is, it is absolutely lined up. We are, as, as I mentioned earlier, we are jointly engineering and developing this thing together. And so that includes not just the nuts and bolts underneath, but kind of the vision of where it's going. And so we're, we're collectively bringing in customer feedback. >>What is that vision real quick? >>So that vision has to actually help an under help meet even the most demanding customer workloads. Okay. So you've got customer workloads that are still locked in on premises. And why is that? Well, it used to be, there was big for data and migration, right? And the speed. And so we continue to iterate this and that again is a joint thing. Instead of say, VMware, just building on AWS, it really is a, a tight partnership. >>Yeah. The lift and shift is a, an easy thing to do. And, and, and by the way, that could be a hassle too. But I hear most people say the reason holding us back on the workloads is it's just a lot of work, a hassle making it easier is what they want. And you guys are doing that. >>We are doing that. Absolutely. And by the way, we've got not just engineering teams, but we've got customer support teams on both sides working together. We also have flexible commercial options, right? If a customer wants to buy from AWS because they've negotiated some kind of deal with us, they can do that. They wanna buy from VMware for a similar reason. They could buy from VMware. So are >>They in the marketplace? >>They are in the market. There, there are some things in the marketplace. So you talked about Tansu, there's a Tansu offering in the marketplace. So yes. Customers can >>Contract. Yeah. Marketplaces. I'm telling you that's very disruptive. I'm Billy bullish on the market AIOS marketplace. I think that's gonna be a transformative way. People have what they procure and fully agree, deploy and how, and channel relationships are gonna shift. I think that's gonna be a disruptive enabler to the partner equation and, and we haven't even seen it yet. We're gonna be up there in September for their inaugural event. I think it's a small group, but we're gonna be documenting that. So even final question for you, what's next for you? What's on the agenda. You got reinvent right around the corner. Your P ones are done. Right? I know. Assuming all that, I turn that general joke. That's an internal Amazon joke. FYI. You've got your plan. What's next for the world. Obviously they're gonna go this, take this, explore global. No matter what happens with Broadcom, this is gonna be a growth wave with hybrid. What's next for you and your team with AWS and VMware's relationship? >>Yeah. So both of us are hyper focused on adding additional options, both from a, an instance compute perspective. You know, VMware announced some, some, some additional offerings that we've got. We've got a fully complete, like, so they're, they announce things like VMware flex compute V VMware flex storage. You mentioned earlier, there was a conversation around ransomware. There's a new ransomware based offering. So we're hyper focused on rounding out, continuing to round out the offering and giving customers even more choice >>Real quick. Jonathan made me think about the ransomware we were at reinforce Steven Schmidtz now the CSO. Now you got a CSO. AJ's the CSO. You got a whole focus, huge emphasis on security right now. I know you always have, but now it's much more public. It's PO more positive, I think, than some of the other events I've been to. It's been more Lum and doom. What's the security tie in here with VMware. Can you share a little bit real quick on the security piece update around this relationship? >>Yeah, you bet. So as you know, security for us is job zero. Like you don't have anything of security. And so what are the things that, that we're excited about specifically with VMware is, is the latest offering that, that we put together and it's called this, this ransomware offering. And it's, it's a little bit different than other ransomware. I mean, a lot of people have ransomware offerings today, just >>Air gap. >>Right, right, right. Exactly. No, that's easy. No, this one is different. So on the back end, so within VMC, there's this, this option where CU we can be to be taking iterative snapshots of a customer environment. Now, if an event were to occur, right. And a customer is like, I have to know if I'm compromised, we can actually spin up super easy. This is cloud. Remember? Yeah. We can spin up a, a copy of this environment, throw a switch, pick a snapshot with NSX. So VMware NSX firewall it off and then use some custom tooling from VMware to actually see if it's been compromised or not. And then iterate through that until you actually know you're clean. And that's different than just tools that do maybe a >>Little bit of scam. We had Tom gills on yesterday and, and one of the things Dave ante had to leave is taking the sun to college is last one in the house and B nester now, but Tom Gill was on. We were talking about how good their security story is ware. And they really weren't showboating it as much as they could have here. I thought they could have done a better job, but this is an example of kind of them really leaning in with you guys. That's the key part of the relationship. >>Yeah, it really is. And I think this is something is materially different than what you can get elsewhere. And it's exciting for, >>Okay. Now the, the real question I want to know is what's your plans for AWS reinvent the blockbuster end of the year, Amazon surf show that gets bigger and bigger. I know it's still hybrid now, but it's looking be hybrid, but people are back in person last year. You guys were the first event really come back and still had massive numbers. AWS summit, New York at 19,000. I heard last week in Chicago, big numbers. So we're expecting reinvent to be pretty large this year. What are you, what are you gonna do there? What's your role there? >>We are expecting, well, I'll be there. I cover multiple businesses. Obviously. We're, we're planning on some additional announcements, obviously in the VMware space as well. And one of the other businesses I run is around SAP. And you should look for some things there as well. Yeah. Really looking forward to reinvent, except for the fact that it's right after Thanksgiving. But I think it >>Always ruins my, I always get an article out. I like, why are you we're having, we're having Thanksgiving dinner. I gotta write this article. It's gotta get Adam, Adam. Leski exclusive. We, every year we do a, a CEO sit down with Andy was the CEO and then now Adam. But yeah, it's a great event to me. I think it sets the tone. And it's gonna be very interesting to see the big clouds are coming to the big cloud. You guys, and you guys are now called hyperscalers. Now, multiple words. It's interesting. You guys are providing the CapEx goodness for everybody else now. And that relationship seems to be the new, the new industry standard of you guys provide the enablement and then everyone you get paid, cuz it's a service. A whole nother level of cloud is emerging in the partner network, GSI other companies. Yeah. >>Yeah. I mean we're really scaling. I mean we continue to iterate and release regions at a fast clip. We just announced support for VMware in Hong Kong. Yeah. So now we're up to 21 regions for this service, >>The sovereign clouds right around the corner. Let's we'll talk about that soon. Steven. Thanks for coming. I know you gotta go. Thank you for your valuable time. Coming in. Put Steven Jones. Who's the general manager of the VMware cloud on AWS business. Four AWS here inside the cube day. Three of cube coverage. I'm John furrier. Thanks for watching. We'll be right back.

>> From the Cube studios in Palo Alto and Boston, bringing you data driven insights from theCUBE and ETR, this is Breaking Analysis with Dave Vellante. >> While the precise direction of VMware's future is unknown, given the plan Broadcom acquisition, one thing is clear. The topic of what Broadcom plans will not be the main focus of the agenda at the upcoming VMware Explore event next week in San Francisco. We believe that despite any uncertainty, VMware will lay out for its customers what it sees as its future. And that future is multi-cloud or cross-cloud services, what we call Supercloud. Hello, and welcome to this week's Wikibon Cube Insights powered by ETR. In this breaking analysis, we drill into the latest survey data on VMware from ETR. And we'll share with you the next iteration of the Supercloud definition based on feedback from dozens of contributors. And we'll give you our take on what to expect next week at VMware Explorer 2022. Well, VMware is maturing. You can see it in the numbers. VMware had a solid quarter just this week, which was announced beating earnings and growing the top line by 6%. But it's clear from its financials and the ETR data that we're showing here that VMware's Halcion glory days are behind it. This chart shows the spending profile from ETR's July survey of nearly 1500 IT buyers and CIOs. The survey included 722 VMware customers with the green bars showing elevated spending momentum, ie: growth, either new or growing at more than 6%. And the red bars show lower spending, either down 6% or worse or defections. The gray bars, that's the flat spending crowd, and it really tells a story. Look, nobody's throwing away their VMware platforms. They're just not investing as rapidly as in previous years. The blue line shows net score or spending momentum and subtracts the reds from the greens. The yellow line shows market penetration or pervasiveness in the survey. So the data is pretty clear. It's steady, but it's not remarkable. Now, the timing of the acquisition, quite rightly, is quite good, I would say. Now, this next chart shows the net score and pervasiveness juxtaposed on an XY graph and breaks down the VMware portfolio in those dimensions, the product portfolio. And you can see the dominance of respondents citing VMware as the platform. They might not know exactly which services they use, but they just respond VMware. That's on the X axis. You can see it way to the right. And the spending momentum or the net score is on the Y axis. That red dotted line at 4%, that indicates elevated levels and only VMware cloud on AWS is above that line. Notably, Tanzu has jumped up significantly from previous quarters, with the rest of the portfolio showing steady, as you would expect from a maturing platform. Only carbon black is hovering in the red zone, kind of ironic given the name. We believe that VMware is going to be a major player in cross cloud services, what we refer to as Supercloud. For months, we've been refining the concept and the definition. At Supercloud '22, we had discussions with more than 30 technology and business experts, and we've gathered input from many more. Based on that feedback, here's the definition we've landed on. It's somewhat refined from our earlier definition that we published a couple weeks ago. Supercloud is an emerging computing architecture that comprises a set of services abstracted from the underlying primitives of hyperscale clouds, e.g. compute, storage, networking, security, and other native resources, to create a global system spanning more than one cloud. Supercloud is three essential properties, three deployment models, and three service models. So what are those essential elements, those properties? We've simplified the picture from our last report. We show them here. I'll review them briefly. We're not going to go super in depth here because we've covered this topic a lot. But supercloud, it runs on more than one cloud. It creates that common or identical experience across clouds. It contains a necessary capability that we call a superPaaS that acts as a cloud interpreter, and it has metadata intelligence to optimize for a specific purpose. We'll publish this definition in detail. So again, we're not going to spend a ton of time here today. Now, we've identified three deployment models for Supercloud. The first is a single instantiation, where a control plane runs on one cloud but supports interactions with multiple other clouds. An example we use is Kubernetes cluster management service that runs on one cloud but can deploy and manage clusters on other clouds. The second model is a multi-cloud, multi-region instantiation where a full stack of services is instantiated on multiple clouds and multiple cloud regions with a common interface across them. We've used cohesity as one example of this. And then a single global instance that spans multiple cloud providers. That's our snowflake example. Again, we'll publish this in detail. So we're not going to spend a ton of time here today. Finally, the service models. The feedback we've had is IaaS, PaaS, and SaaS work fine to describe the service models for Supercloud. NetApp's Cloud Volume is a good example in IaaS. VMware cloud foundation and what we expect at VMware Explore is a good PaaS example. And SAP HANA Cloud is a good example of SaaS running as a Supercloud service. That's the SAP HANA multi-cloud. So what is it that we expect from VMware Explore 2022? Well, along with what will be an exciting and speculation filled gathering of the VMware community at the Moscone Center, we believe VMware will lay out its future architectural direction. And we expect it will fit the Supercloud definition that we just described. We think VMware will show its hand on a set of cross-cloud services and will promise a common experience for users and developers alike. As we talked about at Supercloud '22, VMware kind of wants to have its cake, eat it too, and lose weight. And by that, we mean that it will not only abstract the underlying primitives of each of the individual clouds, but if developers want access to them, they will allow that and actually facilitate that. Now, we don't expect VMware to use the term Supercloud, but it will be a cross-cloud multi-cloud services model that they put forth, we think, at VMworld Explore. With IaaS comprising compute, storage, and networking, a very strong emphasis, we believe, on security, of course, a governance and a comprehensive set of data protection services. Now, very importantly, we believe Tanzu will play a leading role in any announcements this coming week, as a purpose-built PaaS layer, specifically designed to create a common experience for cross clouds for data and application services. This, we believe, will be VMware's most significant offering to date in cross-cloud services. And it will position VMware to be a leader in what we call Supercloud. Now, while it remains to be seen what Broadcom exactly intends to do with VMware, we've speculated, others have speculated. We think this Supercloud is a substantial market opportunity generally and for VMware specifically. Look, if you don't own a public cloud, and very few companies do, in the tech business, we believe you better be supporting the build out of superclouds or building a supercloud yourself on top of hyperscale infrastructure. And we believe that as cloud matures, hyperscalers will increasingly I cross cloud services as an opportunity. We asked David Floyer to take a stab at a market model for super cloud. He's really good at these types of things. What he did is he took the known players in cloud and estimated their IaaS and PaaS cloud services, their total revenue, and then took a percentage. So this is super set of just the public cloud and the hyperscalers. And then what he did is he took a percentage to fit the Supercloud definition, as we just shared above. He then added another 20% on top to cover the long tail of Other. Other over time is most likely going to grow to let's say 30%. That's kind of how these markets work. Okay, so this is obviously an estimate, but it's an informed estimate by an individual who has done this many, many times and is pretty well respected in these types of forecasts, these long term forecasts. Now, by the definition we just shared, Supercloud revenue was estimated at about $3 billion in 2022 worldwide, growing to nearly $80 billion by 2030. Now remember, there's not one Supercloud market. It comprises a bunch of purpose-built superclouds that solve a specific problem. But the common attribute is it's built on top of hyperscale infrastructure. So overall, cloud services, including Supercloud, peak by the end of the decade. But Supercloud continues to grow and will take a higher percentage of the cloud market. The reasoning here is that the market will change and compute, will increasingly become distributed and embedded into edge devices, such as automobiles and robots and factory equipment, et cetera, and not necessarily be a discreet... I mean, it still will be, of course, but it's not going to be as much of a discrete component that is consumed via services like EZ2, that will mature. And this will be a key shift to watch in spending dynamics and really importantly, computing economics, the things we've talked about around arm and edge and AI inferencing and new low cost computing architectures at the edge. We're talking not the near edge, like, Lowes and Home Depot, we're talking far edge and embedded devices. Now, whether this becomes a seamless part of Supercloud remains to be seen. Look, if that's how we see it, the current and the future state of Supercloud, and we're committed to keeping the discussion going with an inclusive model that gathers input from all parts of the industry. Okay, that's it for today. Thanks to Alex Morrison, who's on production, and he also manages the podcast. Ken Schiffman, as well, is on production in our Boston office. Kristin Martin and Cheryl Knight, they help us get the word out on social media and in our newsletters. And Rob Hoffe is our editor in chief over at Silicon Angle and does some helpful editing. Thank you, all. Remember these episodes, they're all available as podcasts, wherever you listen. All you got to do is search Breaking Analysis Podcast. I publish each week on wikibon.com and siliconangle.com. You can email me directly at david.vellante@siliconangle.com or DM me @Dvellante or comment on our LinkedIn posts. Please do check out etr.ai. They've got some great enterprise survey research. So please go there and poke around, And if you need any assistance, let them know. This is Dave Vellante for the Cube Insights powered by ETR. Thanks for watching, and we'll see you next time on Breaking Analysis. (lively music)

>>Hello, everyone. Welcome to the cubes presentation of the 80 minutes startup showcase. Season two, episode two, the theme is data as code, the future of analytics. I'm John furry, your host. We had a great day lineup for you. Fast growing startups, great lineup of companies, founders, and stories around data as code. And we're going to kick it off here with our opening keynote with Rahul Pathak VP of analytics at AWS cube alumni. Right? We'll thank you for coming on and being the opening keynote for this awesome event. >>Yeah. And it's great to see you, and it's great to be part of this event, uh, excited to, um, to help showcase some of the great innovation that startups are doing on top of AWS. >>Yeah. We last spoke at AWS reinvent and, uh, a lot's happened there, service loss of serverless as the center of the, of the action, but all these start-ups rock set Dremio Cribble monks next Liccardo, a HANA imply all doing great stuff. Data as code has a lot of traction. So a lot of still momentum going on in the marketplace. Uh, pretty exciting. >>No, it's, uh, it's awesome. I mean, I think there's so much innovation happening and you know, the, the wonderful part of working with data is that the demand for services and products that help customers drive insight from data is just skyrocketing and has no sign of no sign of slowing down. And so it's a great time to be in the data business. >>It's interesting to see the theme of the show getting traction, because you start to see data being treated almost like how developers write software, taking things out of branches, working on them, putting them back in, uh, machine learnings, uh, getting iterated on you, seeing more models, being trained differently with better insights, action ones that all kind of like working like code. And this is a whole nother way. People are reinventing their businesses. This has been a big, huge wave. What's your reaction to that? >>Uh, I think it's spot on, I mean, I think the idea of data's code and bringing some of the repeatability of processes from software development into how people built it, applications is absolutely fundamental and especially so in machine learning where you need to think about the explainability of a model, what version of the world was it trained on? When you build a better model, you need to be able to explain and reproduce it. So I think your insights are spot on and these ideas are showing up in all stages of the data work flow from ingestion to analytics to I'm out >>This next way is about modernization and going to the next level with cloud-scale. Uh, thank you so much for coming on and being the keynote presenter here for this great event. Um, I'll let you take it away. Reinventing businesses, uh, with ads analytics, right? We'll take it away. >>Okay, perfect. Well, folks, we're going to talk about, uh, um, reinventing your business with, uh, data. And if you think about it, the first wave of reinvention was really driven by the cloud. As customers were able to really transform how they thought about technology and that's well on her way. Although if you stop and think about it, I think we're only about five to 10% of the way done in terms of it span being on the cloud. So lots of work to do there, but we're seeing another wave of reinvention, which is companies reinventing their businesses with data and really using data to transform what they're doing to look for new opportunities and look for ways to operate more efficiently. And I think the past couple of years of the pandemic, it really only accelerated that trend. And so what we're seeing is, uh, you know, it's really about the survival of the most informed folks for the best data are able to react more quickly to what's happening. >>Uh, we've seen customers being able to scale up if they're in, say the delivery business or scale down, if they were in the travel business at the beginning of all of this, and then using data to be able to find new opportunities and new ways to serve customers. And so it's really foundational and we're seeing this across the board. And so, um, you know, it's great to see the innovation that's happening to help customers make sense of all of this. And our customers are really looking at ways to put data to work. It's about making better decisions, finding new efficiencies and really finding new opportunities to succeed and scale. And, um, you know, when it comes to, uh, good examples of this FINRA is a great one. You may not have heard of them, but that the U S equities regulators, all trading that happens in equities, they keep track of they're look at about 250 billion records per day. >>Uh, the examiner, I was only EMR, which is our spark and Hadoop service, and they're processing 20 terabytes of data running across tens of thousands of nodes. And they're looking for fraud and bad actors in the market. So, um, you know, huge, uh, transformation journey for FINRA over the years of customer I've gotten to work with personally since really 2013 onward. So it's been amazing to see their journey, uh, Pinterest, not a great customer. I'm sure everyone's familiar with, but, um, you know, they're about visual search and discovery and commerce, and, um, they're able to scale their daily lot searches, um, really a factor of three X or more, uh, drive down their costs. And they're using the Amazon Opus search service. And really what we're trying to do at AWS is give our customers the most comprehensive set of services for the end-to-end journey around, uh, data from ingestion to analytics and machine learning. And we will want to provide a comprehensive set of capabilities for ingestion, cataloging analytics, and then machine learning. And all of these are things that our partners and the startups that are run on us have available to them to build on as they build and deliver value for their customers. >>And, you know, the way we think about this is we want customers to be able to modernize what they're doing and their infrastructure. And we provide services for that. It's about unifying data, wherever it lives, connecting it. So the customers can build a complete picture of their customers and business. And then it's about innovation and really using machine learning to bring all of this unified data, to bear on driving new innovation and new opportunities for customers. And what we're trying to do AWS is really provide a scalable and secure cloud platform that customers and partners can build on a unifying is about connecting data. And it's also about providing well-governed access to data. So one of the big trends that we see is customers looking for the ability to make self-service data available to that customer there and use. And the key to that is good foundational governance. >>Once you can define good access controls, you then are more comfortable setting data free. And, um, uh, the other part of it is, uh, data lakes play a huge role because you need to be able to think about structured and unstructured data. In fact, about 80% of the data being generated today, uh, is unstructured. And you want to be able to connect data that's in data lakes with data that's in purpose-built data stores, whether that's databases on AWS databases, outside SAS products, uh, as well as things like data warehouses and machine learning systems, but really connecting data as key. Uh, and then, uh, innovation, uh, how can we bring to bear? And we imagine all processes with new technologies like AI and machine learning, and AI is also key to unlocking a lot of the value that's in unstructured data. If you can figure out what's in an imagine the sentiment of audio and do that in real-time that lets you then personalize and dynamically tailor experiences, all of which are super important to getting an edge, um, in, uh, in the modern marketplace. And so at AWS, we, when we think about connecting the dots across sources of data, allowing customers to use data, lakes, databases, analytics, and machine learning, we want to provide a common catalog and governance and then use these to help drive new experiences for customers and their apps and their devices. And then this, you know, in an ideal world, we'll create a closed loop. So you create a new experience. You observe our customers interact with it, that generates more data, which is a data source that feeds into the system. >>And, uh, you know, on AWS, uh, thinking about a modern data strategy, uh, really at the core is a data lakes built on us three. And I'll talk more about that in a second. Then you've got services like Athena included, lake formation for managing that data, cataloging it and querying it in place. And then you have the ability to use the right tool for the right job. And so we're big believers in purpose-built services for data because that's where you can avoid compromising on performance functionality or scale. Uh, and then as I mentioned, unification and inter interconnecting, all of that data. So if you need to move data between these systems, uh, there's well-trodden pathways that allow you to do that, and then features built into services that enable that. >>And, um, you know, some of the core ideas that guide the work that we do, um, scalable data lakes at key, um, and you know, this is really about providing arbitrarily scalable high throughput systems. It's about open format data for future-proofing. Uh, then we talk about purpose-built systems at the best possible functionality, performance, and cost. Uh, and then from a serverless perspective, this has been another big trend for us. We announced a bunch of serverless services and reinvented the goal here is to really take away the need to manage infrastructure from customers. They can really focus about driving differentiated business value, integrated governance, and then machine learning pervasively, um, not just as an end product for data scientists, but also machine learning built into data, warehouses, visualization and a database. >>And so it's scalable data lakes. Uh, data three is really the foundation for this. One of our, um, original services that AWS really the backbone of so much of what we do, uh, really unmatched your ability, availability, and scale, a huge portfolio of analytics services, uh, both that we offer, but also that our partners and customers offer and really arbitrary skin. We've got individual customers and estimator in the expert range, many in the hundreds of petabytes. And that's just growing. You know, as I mentioned, we see roughly a 10 X increase in data volume every five years. So that's a exponential increase in data volumes, Uh, from a purpose-built perspective, it's the right tool for the right job, the red shift and data warehousing Athena for querying all your data. Uh, EMR is our managed sparking to do, uh, open search for log analytics and search, and then Kinesis and Amex care for CAFCA and streaming. And that's been another big trend is, uh, real time. Data has been exploding and customers wanting to make sense of that data in real time, uh, is another big deal. >>Uh, some examples of how we're able to achieve differentiated performance and purpose-built systems. So with Redshift, um, using managed storage and it's led us and since types, uh, the three X better price performance, and what's out there available to all our customers and partners in EMR, uh, with things like spark, we're able to deliver two X performance of open source with a hundred percent compatibility, uh, almost three X and Presto, uh, with on two, which is our, um, uh, new Silicon chips on AWS, better price performance, about 10 to 12% better price performance, and 20% lower costs. And then, uh, all compatible source. So drop your jobs, then have them run faster and cheaper. And that translates to customer benefits for better margins for partners, uh, from a serverless perspective, this is about simplifying operations, reducing total cost of ownership and freeing customers from the need to think about capacity management. If we invent, we, uh, announced serverless redshifts EMR, uh, serverless, uh, Kinesis and Kafka, um, and these are all game changes for customers in terms of freeing our customers and partners from having to think about infrastructure and allowing them to focus on data. >>And, um, you know, when it comes to several assumptions in analytics, we've really got a very full and complete set. So, uh, whether that's around data warehousing, big data processing streaming, or cataloging or governance or visualization, we want all of our customers to have an option to run something struggles as well as if they have specialized needs, uh, uh, instances are available as well. And so, uh, really providing a comprehensive deployment model, uh, based on the customer's use cases, uh, from a governance perspective, uh, you know, like information is about easy build and management of data lakes. Uh, and this is what enables data sharing and self service. And, um, you know, with you get very granular access controls. So rule level security, uh, simple data sharing, and you can tag data. So you can tag a group of analysts in the year when you can say those only have access to the new data that's been tagged with the new tags, and it allows you to very, scaleably provide different secure views onto the same data without having to make multiple copies, another big win for customers and partners, uh, support transactions on data lakes. >>So updates and deletes. And time-travel, uh, you know, John talked about data as code and with time travel, you can look at, um, querying on different versions of data. So that's, uh, a big enabler for those types of strategies. And with blue, you're able to connect data in multiple places. So, uh, whether that's accessing data on premises in other SAS providers or, uh, clouds, uh, as well as data that's on AWS and all of this is, uh, serverless and interconnected. And, um, and really it's about plugging all of your data into the AWS ecosystem and into our partner ecosystem. So this API is all available for integration as well, but then from an AML perspective, what we're really trying to do is bring machine learning closer to data. And so with our databases and warehouses and lakes and BI tools, um, you know, we've infused machine learning throughout our, by, um, the state of the art machine running that we offer through SageMaker. >>And so you've got a ML in Aurora and Neptune for broths. Uh, you can train machine learning models from SQL, directly from Redshift and a female. You can use free inference, and then QuickSight has built in forecasting built in natural language, querying all powered by machine learning, same with anomaly detection. And here are the ideas, you know, how can we up our systems get smarter at the surface, the right insights for our customers so that they don't have to always rely on smart people asking the right questions, um, and you know, uh, really it's about bringing data back together and making it available for innovation. And, uh, thank you very much. I appreciate your attention. >>Okay. Well done reinventing the business with AWS analytics rural. That was great. Thanks for walking through that. That was awesome. I have to ask you some questions on the end-to-end view of the data. That seems to be a theme serverless, uh, in there, uh, Mel integration. Um, but then you also mentioned picking the right tool for the job. So then you've got like all these things moving on, simplify it for me right now. So from a business standpoint, how do they modernize? What's the steps that the clients are taking with analytics, what's the best practice? How do they, what's the what's the high order bit here? >>Uh, so the basic hierarchy is, you know, historically legacy systems are rigid and inflexible, and they weren't really designed for the scale of modern data or the variety of it. And so what customers are finding is they're moving to the cloud. They're moving from legacy systems with punitive licensing into more flexible, more systems. And that allows them to really think about building a decoupled, scalable future proof architecture. And so you've got the ability to combine data lakes and databases and data warehouses and connect them using common KPIs and common data protection. And that sets you up to deal with arbitrary scale and arbitrary types. And it allows you to evolve as the future changes since it makes it easy to add in a new type of engine, as we invent a better one a few years from now. Uh, and then, uh, once you've kind of got your data in a cloud and interconnected in this way, you can now build complete pictures of what's going on. You can understand all your touch points with customers. You can understand your complete supply chain, and once you can build that complete picture of your business, you can start to use analytics and machine learning to find new opportunities. So, uh, think about modernizing, moving to the cloud, setting up for the future, connecting data end to end, and then figuring out how to use that to your advantage. >>I know as you mentioned, modern data strategy gives you the best of both worlds. And you've mentioned, um, briefly, I want to get a little bit more, uh, insight from you on this. You mentioned open, open formats. One of the themes that's come out of some of the interviews, these companies we're going to be hearing from today is open source. The role opens playing. Um, how do you see that integrating in? Because again, this is just like software, right? Open, uh, open source software, open source data. It seems to be a trend. What does open look like to you? How do you see that progressing? >>Uh, it's a great question. Uh, open operates on multiple dimensions, John, as you point out, there's open data formats. These are things like JSI and our care for analytics. This allows multiple engines tend to operate on data and it'll, it, it creates option value for customers. If you're going to data in an open format, you can use it with multiple technologies and that'll be future-proofed. You don't have to migrate your data. Now, if you're thinking about using a different technology. So that's one piece now that sort of software, um, also, um, really a big enabler for innovation and for customers. And you've got things like squat arc and Presto, which are popular. And I know some of the startups, um, you know, that we're talking about as part of the showcase and use these technologies, and this allows for really the world to contribute, to innovating and these engines and moving them forward together. And we're big believers in that we've got open source services. We contribute to open-source, we support open source projects, and that's another big part of what we do. And then there's open API is things like SQL or Python. Uh, again, uh, common ways of interacting with data that are broadly adopted. And this one, again, create standardization. It makes it easier for customers to inter-operate and be flexible. And so open is really present all the way through. And it's a big part, I think, of, uh, the present and the future. >>Yeah. It's going to be fun to watch and see how that grows. It seems to be a lot of traction there. I want to ask you about, um, the other comment I thought was cool. You had the architectural slides out there. One was data lakes built on S3, and you had a theme, the glue in lake formation kind of around S3. And then you had the constellation of, you know, Kinesis SageMaker and other things around it. And you said, you know, pick the tool for the right job. And then you had the other slide on the analytics at the center and you had Redshift and all the other, other, other services around it around serverless. So one was more about the data lake with Athena glue and lake formation. The other one's about serverless. Explain that a little bit more for me, because I'm trying to understand where that fits. I get the data lake piece. Okay. Athena glue and lake formation enables it, and then you can pick and choose what you need on the serverless side. What does analytics in the center mean? >>So the idea there is that really, we wanted to talk about the fact that if you zoom into the analytics use case within analytics, everything that we offer, uh, has a serverless option for our customers. So, um, you could look at the bucket of analytics across things like Redshift or EMR or Athena, or, um, glue and league permission. You have the option to use instances or containers, but also to just not worry about infrastructure and just think declaratively about the data that you want to. >>Oh, so basically you're saying the analytics is going serverless everywhere. Talking about volumes, you mentioned 10 X volumes. Um, what are other stats? Can you share in terms of volumes? What are people seeing velocity I've seen data warehouses can't move as fast as what we're seeing in the cloud with some of your customers and how they're using data. How does the volume and velocity community have any kind of other kind of insights into those numbers? >>Yeah, I mean, I think from a stats perspective, um, you know, take Redshift, for example, customers are processing. So reading and writing, um, multiple exabytes of data there across from each shift. And, uh, you know, one of the things that we've seen in, uh, as time has progressed as, as data volumes have gone up and did a tapes have exploded, uh, you've seen data warehouses get more flexible. So we've added things like the ability to put semi-structured data and arbitrary, nested data into Redshift. Uh, we've also seen the seamless integration of data warehouses and data lakes. So, um, actually Redshift was one of the first to enable a straightforward acquiring of data. That's sitting in locally and drives as well as feed and that's managed on a stream and, uh, you know, those trends will continue. I think you'll kind of continue to see this, um, need to query data wherever it lives and, um, and, uh, allow, uh, leaks and warehouses and purpose-built stores to interconnect. >>You know, one of the things I liked about your presentation was, you know, kind of had the theme of, you know, modernize, unify, innovate, um, and we've been covering a lot of companies that have been, I won't say stumbling, but like getting to the future, some go faster than others, but they all kind of get stuck in an area that seems to be the same spot. It's the silos, breaking down the silos and get in the data lakes and kind of blending that purpose built data store. And they get stuck there because they're so used to silos and their teams, and that's kind of holding back the machine learning side of it because the machine learning can't do its job if they don't have access to all the data. And that's where we're seeing machine learning kind of being this new iterative model where the models are coming in faster. And so the silo brake busting is an issue. So what's your take on this part of the equation? >>Uh, so there's a few things I plan it. So you're absolutely right. I think that transition from some old data to interconnected data is always straightforward and it operates on a number of levels. You want to have the right technology. So, um, you know, we enable things like queries that can span multiple stores. You want to have good governance, you can connect across multiple ones. Uh, then you need to be able to get data in and out of these things and blue plays that role. So there's that interconnection on the technical side, but the other piece is also, um, you know, you want to think through, um, organizationally, how do you organize, how do you define it once data when they share it? And one of the asylees for enabling that sharing and, um, think about, um, some of the processes that need to get put in place and create the right incentives in your company to enable that data sharing. And then the foundational piece is good guardrails. You know, it's, uh, it can be scary to open data up. And, uh, the key to that is to put good governance in place where you can ensure that data can be shared and distributed while remaining protected and adhering to the privacy and compliance and security regulations that you have for that. And once you can assert that level of protection, then you can set that data free. And that's when, uh, customers really start to see the benefits of connecting all of it together, >>Right? And then we have a batch of startups here on this episode that are doing a lot of different things. Uh, some have, you know, new lake new lakes are forming observability lakes. You have CQL innovation on the front end data, tiering innovation at the data tier side, just a ton of innovation around this new data as code. How do you see as executive at AWS? You're enabling all this, um, where's the action going? Where are the white spaces? Where are the opportunities as this architecture continues to grow, um, and get traction because of the relevance of machine learning and AI and the apps are embedding data in there now as code where's the opportunities for these startups and how can they continue to grow? >>Yeah, the, I mean, the opportunity is it's amazing, John, you know, we talked a little bit about this at the beginning, but the, there is no slow down insight for the volume of data that we're generating pretty much everything that we have, whether it's a watch or a phone or the systems that we interact with are generating data and, uh, you know, customers, uh, you know, we talk a lot about the things that'll stay the same over time. And so, you know, the data volumes will continue to go up. Customers are gonna want to keep analyzing that data to make sense of it. They're going to want to be able to do it faster and more cheaply than they were yesterday. And then we're going to want to be able to make decisions and innovate, uh, in a shorter cycle and run more experiments than they were able to do. >>And so I think as long as, and they're always going to want this data to be secure and well-protected, and so I think as long as we, and the startups that we work with can continue to push on making these things better. Can I deal with more data? Can I deal with it more cheaply? Can I make it easier to get insight? And can I maintain a super high bar in security investments in these areas will just be off. Um, because, uh, the demand side of this equation is just in a great place, given what we're seeing in terms of theater and the architect for forum. >>I also love your comment about, uh, ML integration being the last leg of the equation here or less likely the journey, but you've got that enablement of the AIP solves a lot of problems. People can see benefits from good machine learning and AI is creating opportunities. Um, and also you also have mentioned the end to end with security piece. So data and security are kind of going hand in hand these days, not just the governments and the compliance stuff we're talking about security. So machine learning integration kind of connects all of this. Um, what's it all mean for the customers, >>For customers. That means that with machine learning and really enabling themselves to use machine learning, to make sense of data, they're able to find patterns that can represent new opportunities, um, quicker than ever before. And they're able to do it, uh, dynamically. So, you know, in a prior version of the world, we'd have little bit of systems and they would be relatively rigid and then we'd have to improve them. Um, with machine learning, this can be dynamic and near real time and you can customize them. So, uh, that just represents an opportunity to deepen relationships with customers and create more value and to find more efficiency in how businesses are run. So that piece is there. Um, and you know, your ideas around, uh, data's code really come into play because machine learning needs to be repeatable and explainable. And that means versioning, uh, keeping track of everything that you've done from a code and data and learning and training perspective >>And data sets are updating the machine learning. You got data sets growing, they become code modules that can be reused and, uh, interrogated, um, security okay. Is a big as a big theme data, really important security is seen as one of our top use cases. Certainly now in this day and age, we're getting a lot of, a lot of breaches and hacks coming in, being defended. It brings up the open, brings up the data as code security is a good proxy for kind of where this is going. What's your what's take on that and your reaction to that. >>So I'm, I'm security. You can, we can never invest enough. And I think one of the things that we, um, you know, guide us in AWS is security, availability, durability sort of jobs, you know, 1, 2, 3, and, um, and it operates at multiple levels. You need to protect data and rest with encryption, good key management and good practices though. You need to protect data on the wire. You need to have a good sense of what data is allowed to be seen by whom. And then you need to keep track of who did what and be able to verify and come back and prove that, uh, you know, uh, only the things that were allowed to happen actually happened. And you can actually then use machine learning on top of all of this apparatus to say, uh, you know, can I detect things that are happening that shouldn't be happening in near real time so they could put a stop to them. So I don't think any of us can ever invest enough in securing and protecting my data and our systems, and it is really fundamental or adding customer trust and it's just good business. So I think it is absolutely crucial. And we think about it all the time and are always looking for ways to raise >>Well, I really appreciate you taking the time to give the keynote final word here for the folks watching a lot of these startups that are presenting, they're doing well. Business wise, they're being used by large enterprises and people buying their products and using their services for customers are implementing more and more of the hot startups products they're relevant. What's your advice to the customer out there as they go on this journey, this new data as code this new future of analytics, what's your recommendation. >>So for customers who are out there, uh, recommend you take a look at, um, what, uh, the startups on AWS are building. I think there's tremendous innovation and energy, uh, and, um, there's really great technology being built on top of a rock solid platform. And so I encourage customers thinking about it to lean forward, to think about new technology and to embrace, uh, move to the cloud suite, modernized, you know, build a single picture of our data and, and figure out how to innovate and when >>Well, thanks for coming on. Appreciate your keynote. Thanks for the insight. And thanks for the conversation. Let's hand it off to the show. Let the show begin. >>Thank you, John pleasure, as always.

(upbeat music) >> Once a staid and boring business dominated by IBM, Oracle, and at the time newcomer Microsoft, along with a handful of wannabes, the database business has exploded in the past decade and has become a staple of financial excellence, customer experience, analytic advantage, competitive strategy, growth initiatives, visualizations, not to mention compliance, security, privacy and dozens of other important use cases and initiatives. And on the vendor's side of the house, we've seen the rapid ascendancy of cloud databases. Most notably from Snowflake, whose massive raises leading up to its IPO in late 2020 sparked a spate of interest and VC investment in the separation of compute and storage and all that elastic resource stuff in the cloud. The company joined AWS, Azure and Google to popularize cloud databases, which have become a linchpin of competitive strategies for technology suppliers. And if I get you to put your data in my database and in my cloud, and I keep innovating, I'm going to build a moat and achieve a hugely attractive lifetime customer value in a really amazing marginal economics dynamic that is going to fund my future. And I'll be able to sell other adjacent services, not just compute and storage, but machine learning and inference and training and all kinds of stuff, dozens of lucrative cloud offerings. Meanwhile, the database leader, Oracle has invested massive amounts of money to maintain its lead. It's building on its position as the king of mission critical workloads and making typical Oracle like claims against the competition. Most were recently just yesterday with another announcement around MySQL HeatWave. An extension of MySQL that is compatible with on-premises MySQLs and is setting new standards in price performance. We're seeing a dramatic divergence in strategies across the database spectrum. On the far left, we see Amazon with more than a dozen database offerings each with its own API and primitives. AWS is taking a right tool for the right job approach, often building on open source platforms and creating services that it offers to customers to solve very specific problems for developers. And on the other side of the line, we see Oracle, which is taking the Swiss Army Knife approach, converging database functionality, enabling analytic and transactional workloads to run in the same data store, eliminating the need to ETL, at the same time adding capabilities into its platform like automation and machine learning. Welcome to this database Power Panel. My name is Dave Vellante, and I'm so excited to bring together some of the most respected industry analyst in the community. Today we're going to assess what's happening in the market. We're going to dig into the competitive landscape and explore the future of database and database platforms and decode what it means to customers. Let me take a moment to welcome our guest analyst today. Matt Kimball is a vice president and principal analysts at Moor Insights and Strategy, Matt. He knows products, he knows industry, he's got real world IT expertise, and he's got all the angles 25 plus years of experience in all kinds of great background. Matt, welcome. Thanks very much for coming on theCUBE. Holgar Mueller, friend of theCUBE, vice president and principal analyst at Constellation Research in depth knowledge on applications, application development, knows developers. He's worked at SAP and Oracle. And then Bob Evans is Chief Content Officer and co-founder of the Acceleration Economy, founder and principle of Cloud Wars. Covers all kinds of industry topics and great insights. He's got awesome videos, these three minute hits. If you haven't seen 'em, checking them out, knows cloud companies, his Cloud Wars minutes are fantastic. And then of course, Marc Staimer is the founder of Dragon Slayer Research. A frequent contributor and guest analyst at Wikibon. He's got a wide ranging knowledge across IT products, knows technology really well, can go deep. And then of course, Ron Westfall, Senior Analyst and Director Research Director at Futurum Research, great all around product trends knowledge. Can take, you know, technical dives and really understands competitive angles, knows Redshift, Snowflake, and many others. Gents, thanks so much for taking the time to join us in theCube today. It's great to have you on, good to see you. >> Good to be here, thanks for having us. >> Thanks, Dave. >> All right, let's start with an around the horn and briefly, if each of you would describe, you know, anything I missed in your areas of expertise and then you answer the following question, how would you describe the state of the database, state of platform market today? Matt Kimball, please start. >> Oh, I hate going first, but that it's okay. How would I describe the world today? I would just in one sentence, I would say, I'm glad I'm not in IT anymore, right? So, you know, it is a complex and dangerous world out there. And I don't envy IT folks I'd have to support, you know, these modernization and transformation efforts that are going on within the enterprise. It used to be, you mentioned it, Dave, you would argue about IBM versus Oracle versus this newcomer in the database space called Microsoft. And don't forget Sybase back in the day, but you know, now it's not just, which SQL vendor am I going to go with? It's all of these different, divergent data types that have to be taken, they have to be merged together, synthesized. And somehow I have to do that cleanly and use this to drive strategic decisions for my business. That is not easy. So, you know, you have to look at it from the perspective of the business user. It's great for them because as a DevOps person, or as an analyst, I have so much flexibility and I have this thing called the cloud now where I can go get services immediately. As an IT person or a DBA, I am calling up prevention hotlines 24 hours a day, because I don't know how I'm going to be able to support the business. And as an Oracle or as an Oracle or a Microsoft or some of the cloud providers and cloud databases out there, I'm licking my chops because, you know, my market is expanding and expanding every day. >> Great, thank you for that, Matt. Holgar, how do you see the world these days? You always have a good perspective on things, share with us. >> Well, I think it's the best time to be in IT, I'm not sure what Matt is talking about. (laughing) It's easier than ever, right? The direction is going to cloud. Kubernetes has won, Google has the best AI for now, right? So things are easier than ever before. You made commitments for five plus years on hardware, networking and so on premise, and I got gray hair about worrying it was the wrong decision. No, just kidding. But you kind of both sides, just to be controversial, make it interesting, right. So yeah, no, I think the interesting thing specifically with databases, right? We have this big suite versus best of breed, right? Obviously innovation, like you mentioned with Snowflake and others happening in the cloud, the cloud vendors server, where to save of their databases. And then we have one of the few survivors of the old guard as Evans likes to call them is Oracle who's doing well, both their traditional database. And now, which is really interesting, remarkable from that because Oracle it was always the power of one, have one database, add more to it, make it what I call the universal database. And now this new HeatWave offering is coming and MySQL open source side. So they're getting the second (indistinct) right? So it's interesting that older players, traditional players who still are in the market are diversifying their offerings. Something we don't see so much from the traditional tools from Oracle on the Microsoft side or the IBM side these days. >> Great, thank you Holgar. Bob Evans, you've covered this business for a while. You've worked at, you know, a number of different outlets and companies and you cover the competition, how do you see things? >> Dave, you know, the other angle to look at this from is from the customer side, right? You got now CEOs who are any sort of business across all sorts of industries, and they understand that their future success is going to be dependent on their ability to become a digital company, to understand data, to use it the right way. So as you outline Dave, I think in your intro there, it is a fantastic time to be in the database business. And I think we've got a lot of new buyers and influencers coming in. They don't know all this history about IBM and Microsoft and Oracle and you know, whoever else. So I think they're going to take a long, hard look, Dave, at some of these results and who is able to help these companies not serve up the best technology, but who's going to be able to help their business move into the digital future. So it's a fascinating time now from every perspective. >> Great points, Bob. I mean, digital transformation has gone from buzzword to imperative. Mr. Staimer, how do you see things? >> I see things a little bit differently than my peers here in that I see the database market being segmented. There's all the different kinds of databases that people are looking at for different kinds of data, and then there is databases in the cloud. And so database as cloud service, I view very differently than databases because the traditional way of implementing a database is changing and it's changing rapidly. So one of the premises that you stated earlier on was that you viewed Oracle as a database company. I don't view Oracle as a database company anymore. I view Oracle as a cloud company that happens to have a significant expertise and specialty in databases, and they still sell database software in the traditional way, but ultimately they're a cloud company. So database cloud services from my point of view is a very distinct market from databases. >> Okay, well, you gave us some good meat on the bone to talk about that. Last but not least-- >> Dave did Marc, just say Oracle's a cloud company? >> Yeah. (laughing) Take away the database, it would be interesting to have that discussion, but let's let Ron jump in here. Ron, give us your take. >> That's a great segue. I think it's truly the era of the cloud database, that's something that's rising. And the key trends that come with it include for example, elastic scaling. That is the ability to scale on demand, to right size workloads according to customer requirements. And also I think it's going to increase the prioritization for high availability. That is the player who can provide the highest availability is going to have, I think, a great deal of success in this emerging market. And also I anticipate that there will be more consolidation across platforms in order to enable cost savings for customers, and that's something that's always going to be important. And I think we'll see more of that over the horizon. And then finally security, security will be more important than ever. We've seen a spike (indistinct), we certainly have seen geopolitical originated cybersecurity concerns. And as a result, I see database security becoming all the more important. >> Great, thank you. Okay, let me share some data with you guys. I'm going to throw this at you and see what you think. We have this awesome data partner called Enterprise Technology Research, ETR. They do these quarterly surveys and each period with dozens of industry segments, they track clients spending, customer spending. And this is the database, data warehouse sector okay so it's taxonomy, so it's not perfect, but it's a big kind of chunk. They essentially ask customers within a category and buy a specific vendor, you're spending more or less on the platform? And then they subtract the lesses from the mores and they derive a metric called net score. It's like NPS, it's a measure of spending velocity. It's more complicated and granular than that, but that's the basis and that's the vertical axis. The horizontal axis is what they call market share, it's not like IDC market share, it's just pervasiveness in the data set. And so there are a couple of things that stand out here and that we can use as reference point. The first is the momentum of Snowflake. They've been off the charts for many, many, for over two years now, anything above that dotted red line, that 40%, is considered by ETR to be highly elevated and Snowflake's even way above that. And I think it's probably not sustainable. We're going to see in the next April survey, next month from those guys, when it comes out. And then you see AWS and Microsoft, they're really pervasive on the horizontal axis and highly elevated, Google falls behind them. And then you got a number of well funded players. You got Cockroach Labs, Mongo, Redis, MariaDB, which of course is a fork on MySQL started almost as protest at Oracle when they acquired Sun and they got MySQL and you can see the number of others. Now Oracle who's the leading database player, despite what Marc Staimer says, we know, (laughs) and they're a cloud player (laughing) who happens to be a leading database player. They dominate in the mission critical space, we know that they're the king of that sector, but you can see here that they're kind of legacy, right? They've been around a long time, they get a big install base. So they don't have the spending momentum on the vertical axis. Now remember this is, just really this doesn't capture spending levels, so that understates Oracle but nonetheless. So it's not a complete picture like SAP for instance is not in here, no Hana. I think people are actually buying it, but it doesn't show up here, (laughs) but it does give an indication of momentum and presence. So Bob Evans, I'm going to start with you. You've commented on many of these companies, you know, what does this data tell you? >> Yeah, you know, Dave, I think all these compilations of things like that are interesting, and that folks at ETR do some good work, but I think as you said, it's a snapshot sort of a two-dimensional thing of a rapidly changing, three dimensional world. You know, the incidents at which some of these companies are mentioned versus the volume that happens. I think it's, you know, with Oracle and I'm not going to declare my religious affiliation, either as cloud company or database company, you know, they're all of those things and more, and I think some of our old language of how we classify companies is just not relevant anymore. But I want to ask too something in here, the autonomous database from Oracle, nobody else has done that. So either Oracle is crazy, they've tried out a technology that nobody other than them is interested in, or they're onto something that nobody else can match. So to me, Dave, within Oracle, trying to identify how they're doing there, I would watch autonomous database growth too, because right, it's either going to be a big plan and it breaks through, or it's going to be caught behind. And the Snowflake phenomenon as you mentioned, that is a rare, rare bird who comes up and can grow 100% at a billion dollar revenue level like that. So now they've had a chance to come in, scare the crap out of everybody, rock the market with something totally new, the data cloud. Will the bigger companies be able to catch up and offer a compelling alternative, or is Snowflake going to continue to be this outlier. It's a fascinating time. >> Really, interesting points there. Holgar, I want to ask you, I mean, I've talked to certainly I'm sure you guys have too, the founders of Snowflake that came out of Oracle and they actually, they don't apologize. They say, "Hey, we not going to do all that complicated stuff that Oracle does, we were trying to keep it real simple." But at the same time, you know, they don't do sophisticated workload management. They don't do complex joints. They're kind of relying on the ecosystems. So when you look at the data like this and the various momentums, and we talked about the diverging strategies, what does this say to you? >> Well, it is a great point. And I think Snowflake is an example how the cloud can turbo charge a well understood concept in this case, the data warehouse, right? You move that and you find steroids and you see like for some players who've been big in data warehouse, like Sentara Data, as an example, here in San Diego, what could have been for them right in that part. The interesting thing, the problem though is the cloud hides a lot of complexity too, which you can scale really well as you attract lots of customers to go there. And you don't have to build things like what Bob said, right? One of the fascinating things, right, nobody's answering Oracle on the autonomous database. I don't think is that they cannot, they just have different priorities or the database is not such a priority. I would dare to say that it's for IBM and Microsoft right now at the moment. And the cloud vendors, you just hide that right through scripts and through scale because you support thousands of customers and you can deal with a little more complexity, right? It's not against them. Whereas if you have to run it yourself, very different story, right? You want to have the autonomous parts, you want to have the powerful tools to do things. >> Thank you. And so Matt, I want to go to you, you've set up front, you know, it's just complicated if you're in IT, it's a complicated situation and you've been on the customer side. And if you're a buyer, it's obviously, it's like Holgar said, "Cloud's supposed to make this stuff easier, but the simpler it gets the more complicated gets." So where do you place your bets? Or I guess more importantly, how do you decide where to place your bets? >> Yeah, it's a good question. And to what Bob and Holgar said, you know, the around autonomous database, I think, you know, part of, as I, you know, play kind of armchair psychologist, if you will, corporate psychologists, I look at what Oracle is doing and, you know, databases where they've made their mark and it's kind of, that's their strong position, right? So it makes sense if you're making an entry into this cloud and you really want to kind of build momentum, you go with what you're good at, right? So that's kind of the strength of Oracle. Let's put a lot of focus on that. They do a lot more than database, don't get me wrong, but you know, I'm going to short my strength and then kind of pivot from there. With regards to, you know, what IT looks at and what I would look at you know as an IT director or somebody who is, you know, trying to consume services from these different cloud providers. First and foremost, I go with what I know, right? Let's not forget IT is a conservative group. And when we look at, you know, all the different permutations of database types out there, SQL, NoSQL, all the different types of NoSQL, those are largely being deployed by business users that are looking for agility or businesses that are looking for agility. You know, the reason why MongoDB is so popular is because of DevOps, right? It's a great platform to develop on and that's where it kind of gained its traction. But as an IT person, I want to go with what I know, where my muscle memory is, and that's my first position. And so as I evaluate different cloud service providers and cloud databases, I look for, you know, what I know and what I've invested in and where my muscle memory is. Is there enough there and do I have enough belief that that company or that service is going to be able to take me to, you know, where I see my organization in five years from a data management perspective, from a business perspective, are they going to be there? And if they are, then I'm a little bit more willing to make that investment, but it is, you know, if I'm kind of going in this blind or if I'm cloud native, you know, that's where the Snowflakes of the world become very attractive to me. >> Thank you. So Marc, I asked Andy Jackson in theCube one time, you have all these, you know, data stores and different APIs and primitives and you know, very granular, what's the strategy there? And he said, "Hey, that allows us as the market changes, it allows us to be more flexible. If we start building abstractions layers, it's harder for us." I think also it was not a good time to market advantage, but let me ask you, I described earlier on that spectrum from AWS to Oracle. We just saw yesterday, Oracle announced, I think the third major enhancement in like 15 months to MySQL HeatWave, what do you make of that announcement? How do you think it impacts the competitive landscape, particularly as it relates to, you know, converging transaction and analytics, eliminating ELT, I know you have some thoughts on this. >> So let me back up for a second and defend my cloud statement about Oracle for a moment. (laughing) AWS did a great job in developing the cloud market in general and everything in the cloud market. I mean, I give them lots of kudos on that. And a lot of what they did is they took open source software and they rent it to people who use their cloud. So I give 'em lots of credit, they dominate the market. Oracle was late to the cloud market. In fact, they actually poo-pooed it initially, if you look at some of Larry Ellison's statements, they said, "Oh, it's never going to take off." And then they did 180 turn, and they said, "Oh, we're going to embrace the cloud." And they really have, but when you're late to a market, you've got to be compelling. And this ties into the announcement yesterday, but let's deal with this compelling. To be compelling from a user point of view, you got to be twice as fast, offer twice as much functionality, at half the cost. That's generally what compelling is that you're going to capture market share from the leaders who established the market. It's very difficult to capture market share in a new market for yourself. And you're right. I mean, Bob was correct on this and Holgar and Matt in which you look at Oracle, and they did a great job of leveraging their database to move into this market, give 'em lots of kudos for that too. But yesterday they announced, as you said, the third innovation release and the pace is just amazing of what they're doing on these releases on HeatWave that ties together initially MySQL with an integrated builtin analytics engine, so a data warehouse built in. And then they added automation with autopilot, and now they've added machine learning to it, and it's all in the same service. It's not something you can buy and put on your premise unless you buy their cloud customers stuff. But generally it's a cloud offering, so it's compellingly better as far as the integration. You don't buy multiple services, you buy one and it's lower cost than any of the other services, but more importantly, it's faster, which again, give 'em credit for, they have more integration of a product. They can tie things together in a way that nobody else does. There's no additional services, ETL services like Glue and AWS. So from that perspective, they're getting better performance, fewer services, lower cost. Hmm, they're aiming at the compelling side again. So from a customer point of view it's compelling. Matt, you wanted to say something there. >> Yeah, I want to kind of, on what you just said there Marc, and this is something I've found really interesting, you know. The traditional way that you look at software and, you know, purchasing software and IT is, you look at either best of breed solutions and you have to work on the backend to integrate them all and make them all work well. And generally, you know, the big hit against the, you know, we have one integrated offering is that, you lose capability or you lose depth of features, right. And to what you were saying, you know, that's the thing I found interesting about what Oracle is doing is they're building in depth as they kind of, you know, build that service. It's not like you're losing a lot of capabilities, because you're going to one integrated service versus having to use A versus B versus C, and I love that idea. >> You're right. Yeah, not only you're not losing, but you're gaining functionality that you can't get by integrating a lot of these. I mean, I can take Snowflake and integrate it in with machine learning, but I also have to integrate in with a transactional database. So I've got to have connectors between all of this, which means I'm adding time. And what it comes down to at the end of the day is expertise, effort, time, and cost. And so what I see the difference from the Oracle announcements is they're aiming at reducing all of that by increasing performance as well. Correct me if I'm wrong on that but that's what I saw at the announcement yesterday. >> You know, Marc, one thing though Marc, it's funny you say that because I started out saying, you know, I'm glad I'm not 19 anymore. And the reason is because of exactly what you said, it's almost like there's a pseudo level of witchcraft that's required to support the modern data environment right in the enterprise. And I need simpler faster, better. That's what I need, you know, I am no longer wearing pocket protectors. I have turned from, you know, break, fix kind of person, to you know, business consultant. And I need that point and click simplicity, but I can't sacrifice, you know, a depth of features of functionality on the backend as I play that consultancy role. >> So, Ron, I want to bring in Ron, you know, it's funny. So Matt, you mentioned Mongo, I often and say, if Oracle mentions you, you're on the map. We saw them yesterday Ron, (laughing) they hammered RedShifts auto ML, they took swipes at Snowflake, a little bit of BigQuery. What were your thoughts on that? Do you agree with what these guys are saying in terms of HeatWaves capabilities? >> Yes, Dave, I think that's an excellent question. And fundamentally I do agree. And the question is why, and I think it's important to know that all of the Oracle data is backed by the fact that they're using benchmarks. For example, all of the ML and all of the TPC benchmarks, including all the scripts, all the configs and all the detail are posted on GitHub. So anybody can look at these results and they're fully transparent and replicate themselves. If you don't agree with this data, then by all means challenge it. And we have not really seen that in all of the new updates in HeatWave over the last 15 months. And as a result, when it comes to these, you know, fundamentals in looking at the competitive landscape, which I think gives validity to outcomes such as Oracle being able to deliver 4.8 times better price performance than Redshift. As well as for example, 14.4 better price performance than Snowflake, and also 12.9 better price performance than BigQuery. And so that is, you know, looking at the quantitative side of things. But again, I think, you know, to Marc's point and to Matt's point, there are also qualitative aspects that clearly differentiate the Oracle proposition, from my perspective. For example now the MySQL HeatWave ML capabilities are native, they're built in, and they also support things such as completion criteria. And as a result, that enables them to show that hey, when you're using Redshift ML for example, you're having to also use their SageMaker tool and it's running on a meter. And so, you know, nobody really wants to be running on a meter when, you know, executing these incredibly complex tasks. And likewise, when it comes to Snowflake, they have to use a third party capability. They don't have the built in, it's not native. So the user, to the point that he's having to spend more time and it increases complexity to use auto ML capabilities across the Snowflake platform. And also, I think it also applies to other important features such as data sampling, for example, with the HeatWave ML, it's intelligent sampling that's being implemented. Whereas in contrast, we're seeing Redshift using random sampling. And again, Snowflake, you're having to use a third party library in order to achieve the same capabilities. So I think the differentiation is crystal clear. I think it definitely is refreshing. It's showing that this is where true value can be assigned. And if you don't agree with it, by all means challenge the data. >> Yeah, I want to come to the benchmarks in a minute. By the way, you know, the gentleman who's the Oracle's architect, he did a great job on the call yesterday explaining what you have to do. I thought that was quite impressive. But Bob, I know you follow the financials pretty closely and on the earnings call earlier this month, Ellison said that, "We're going to see HeatWave on AWS." And the skeptic in me said, oh, they must not be getting people to come to OCI. And then they, you remember this chart they showed yesterday that showed the growth of HeatWave on OCI. But of course there was no data on there, it was just sort of, you know, lines up and to the right. So what do you guys think of that? (Marc laughs) Does it signal Bob, desperation by Oracle that they can't get traction on OCI, or is it just really a smart tame expansion move? What do you think? >> Yeah, Dave, that's a great question. You know, along the way there, and you know, just inside of that was something that said Ellison said on earnings call that spoke to a different sort of philosophy or mindset, almost Marc, where he said, "We're going to make this multicloud," right? With a lot of their other cloud stuff, if you wanted to use any of Oracle's cloud software, you had to use Oracle's infrastructure, OCI, there was no other way out of it. But this one, but I thought it was a classic Ellison line. He said, "Well, we're making this available on AWS. We're making this available, you know, on Snowflake because we're going after those users. And once they see what can be done here." So he's looking at it, I guess you could say, it's a concession to customers because they want multi-cloud. The other way to look at it, it's a hunting expedition and it's one of those uniquely I think Oracle ways. He said up front, right, he doesn't say, "Well, there's a big market, there's a lot for everybody, we just want on our slice." Said, "No, we are going after Amazon, we're going after Redshift, we're going after Aurora. We're going after these users of Snowflake and so on." And I think it's really fairly refreshing these days to hear somebody say that, because now if I'm a buyer, I can look at that and say, you know, to Marc's point, "Do they measure up, do they crack that threshold ceiling? Or is this just going to be more pain than a few dollars savings is worth?" But you look at those numbers that Ron pointed out and that we all saw in that chart. I've never seen Dave, anything like that. In a substantive market, a new player coming in here, and being able to establish differences that are four, seven, eight, 10, 12 times better than competition. And as new buyers look at that, they're going to say, "What the hell are we doing paying, you know, five times more to get a poor result? What's going on here?" So I think this is going to rattle people and force a harder, closer look at what these alternatives are. >> I wonder if the guy, thank you. Let's just skip ahead of the benchmarks guys, bring up the next slide, let's skip ahead a little bit here, which talks to the benchmarks and the benchmarking if we can. You know, David Floyer, the sort of semiretired, you know, Wikibon analyst said, "Dave, this is going to force Amazon and others, Snowflake," he said, "To rethink actually how they architect databases." And this is kind of a compilation of some of the data that they shared. They went after Redshift mostly, (laughs) but also, you know, as I say, Snowflake, BigQuery. And, like I said, you can always tell which companies are doing well, 'cause Oracle will come after you, but they're on the radar here. (laughing) Holgar should we take this stuff seriously? I mean, or is it, you know, a grain salt? What are your thoughts here? >> I think you have to take it seriously. I mean, that's a great question, great point on that. Because like Ron said, "If there's a flaw in a benchmark, we know this database traditionally, right?" If anybody came up that, everybody will be, "Oh, you put the wrong benchmark, it wasn't audited right, let us do it again," and so on. We don't see this happening, right? So kudos to Oracle to be aggressive, differentiated, and seem to having impeccable benchmarks. But what we really see, I think in my view is that the classic and we can talk about this in 100 years, right? Is the suite versus best of breed, right? And the key question of the suite, because the suite's always slower, right? No matter at which level of the stack, you have the suite, then the best of breed that will come up with something new, use a cloud, put the data warehouse on steroids and so on. The important thing is that you have to assess as a buyer what is the speed of my suite vendor. And that's what you guys mentioned before as well, right? Marc said that and so on, "Like, this is a third release in one year of the HeatWave team, right?" So everybody in the database open source Marc, and there's so many MySQL spinoffs to certain point is put on shine on the speed of (indistinct) team, putting out fundamental changes. And the beauty of that is right, is so inherent to the Oracle value proposition. Larry's vision of building the IBM of the 21st century, right from the Silicon, from the chip all the way across the seven stacks to the click of the user. And that what makes the database what Rob was saying, "Tied to the OCI infrastructure," because designed for that, it runs uniquely better for that, that's why we see the cross connect to Microsoft. HeatWave so it's different, right? Because HeatWave runs on cheap hardware, right? Which is the breadth and butter 886 scale of any cloud provider, right? So Oracle probably needs it to scale OCI in a different category, not the expensive side, but also allow us to do what we said before, the multicloud capability, which ultimately CIOs really want, because data gravity is real, you want to operate where that is. If you have a fast, innovative offering, which gives you more functionality and the R and D speed is really impressive for the space, puts away bad results, then it's a good bet to look at. >> Yeah, so you're saying, that we versus best of breed. I just want to sort of play back then Marc a comment. That suite versus best of breed, there's always been that trade off. If I understand you Holgar you're saying that somehow Oracle has magically cut through that trade off and they're giving you the best of both. >> It's the developing velocity, right? The provision of important features, which matter to buyers of the suite vendor, eclipses the best of breed vendor, then the best of breed vendor is in the hell of a potential job. >> Yeah, go ahead Marc. >> Yeah and I want to add on what Holgar just said there. I mean the worst job in the data center is data movement, moving the data sucks. I don't care who you are, nobody likes it. You never get any kudos for doing it well, and you always get the ah craps, when things go wrong. So it's in- >> In the data center Marc all the time across data centers, across cloud. That's where the bleeding comes. >> It's right, you get beat up all the time. So nobody likes to move data, ever. So what you're looking at with what they announce with HeatWave and what I love about HeatWave is it doesn't matter when you started with it, you get all the additional features they announce it's part of the service, all the time. But they don't have to move any of the data. You want to analyze the data that's in your transactional, MySQL database, it's there. You want to do machine learning models, it's there, there's no data movement. The data movement is the key thing, and they just eliminate that, in so many ways. And the other thing I wanted to talk about is on the benchmarks. As great as those benchmarks are, they're really conservative 'cause they're underestimating the cost of that data movement. The ETLs, the other services, everything's left out. It's just comparing HeatWave, MySQL cloud service with HeatWave versus Redshift, not Redshift and Aurora and Glue, Redshift and Redshift ML and SageMaker, it's just Redshift. >> Yeah, so what you're saying is what Oracle's doing is saying, "Okay, we're going to run MySQL HeatWave benchmarks on analytics against Redshift, and then we're going to run 'em in transaction against Aurora." >> Right. >> But if you really had to look at what you would have to do with the ETL, you'd have to buy two different data stores and all the infrastructure around that, and that goes away so. >> Due to the nature of the competition, they're running narrow best of breed benchmarks. There is no suite level benchmark (Dave laughs) because they created something new. >> Well that's you're the earlier point they're beating best of breed with a suite. So that's, I guess to Floyer's earlier point, "That's going to shake things up." But I want to come back to Bob Evans, 'cause I want to tap your Cloud Wars mojo before we wrap. And line up the horses, you got AWS, you got Microsoft, Google and Oracle. Now they all own their own cloud. Snowflake, Mongo, Couchbase, Redis, Cockroach by the way they're all doing very well. They run in the cloud as do many others. I think you guys all saw the Andreessen, you know, commentary from Sarah Wang and company, to talk about the cost of goods sold impact of cloud. So owning your own cloud has to be an advantage because other guys like Snowflake have to pay cloud vendors and negotiate down versus having the whole enchilada, Safra Catz's dream. Bob, how do you think this is going to impact the market long term? >> Well, Dave, that's a great question about, you know, how this is all going to play out. If I could mention three things, one, Frank Slootman has done a fantastic job with Snowflake. Really good company before he got there, but since he's been there, the growth mindset, the discipline, the rigor and the phenomenon of what Snowflake has done has forced all these bigger companies to really accelerate what they're doing. And again, it's an example of how this intense competition makes all the different cloud vendors better and it provides enormous value to customers. Second thing I wanted to mention here was look at the Adam Selipsky effect at AWS, took over in the middle of May, and in Q2, Q3, Q4, AWS's growth rate accelerated. And in each of those three quotas, they grew faster than Microsoft's cloud, which has not happened in two or three years, so they're closing the gap on Microsoft. The third thing, Dave, in this, you know, incredibly intense competitive nature here, look at Larry Ellison, right? He's got his, you know, the product that for the last two or three years, he said, "It's going to help determine the future of the company, autonomous database." You would think he's the last person in the world who's going to bring in, you know, in some ways another database to think about there, but he has put, you know, his whole effort and energy behind this. The investments Oracle's made, he's riding this horse really hard. So it's not just a technology achievement, but it's also an investment priority for Oracle going forward. And I think it's going to form a lot of how they position themselves to this new breed of buyer with a new type of need and expectations from IT. So I just think the next two or three years are going to be fantastic for people who are lucky enough to get to do the sorts of things that we do. >> You know, it's a great point you made about AWS. Back in 2018 Q3, they were doing about 7.4 billion a quarter and they were growing in the mid forties. They dropped down to like 29% Q4, 2020, I'm looking at the data now. They popped back up last quarter, last reported quarter to 40%, that is 17.8 billion, so they more doubled and they accelerated their growth rate. (laughs) So maybe that pretends, people are concerned about Snowflake right now decelerating growth. You know, maybe that's going to be different. By the way, I think Snowflake has a different strategy, the whole data cloud thing, data sharing. They're not trying to necessarily take Oracle head on, which is going to make this next 10 years, really interesting. All right, we got to go, last question. 30 seconds or less, what can we expect from the future of data platforms? Matt, please start. >> I have to go first again? You're killing me, Dave. (laughing) In the next few years, I think you're going to see the major players continue to meet customers where they are, right. Every organization, every environment is, you know, kind of, we use these words bespoke in Snowflake, pardon the pun, but Snowflakes, right. But you know, they're all opinionated and unique and what's great as an IT person is, you know, there is a service for me regardless of where I am on my journey, in my data management journey. I think you're going to continue to see with regards specifically to Oracle, I think you're going to see the company continue along this path of being all things to all people, if you will, or all organizations without sacrificing, you know, kind of richness of features and sacrificing who they are, right. Look, they are the data kings, right? I mean, they've been a database leader for an awful long time. I don't see that going away any time soon and I love the innovative spirit they've brought in with HeatWave. >> All right, great thank you. Okay, 30 seconds, Holgar go. >> Yeah, I mean, the interesting thing that we see is really that trend to autonomous as Oracle calls or self-driving software, right? So the database will have to do more things than just store the data and support the DVA. It will have to show it can wide insights, the whole upside, it will be able to show to one machine learning. We haven't really talked about that. How in just exciting what kind of use case we can get of machine learning running real time on data as it changes, right? So, which is part of the E5 announcement, right? So we'll see more of that self-driving nature in the database space. And because you said we can promote it, right. Check out my report about HeatWave latest release where I post in oracle.com. >> Great, thank you for that. And Bob Evans, please. You're great at quick hits, hit us. >> Dave, thanks. I really enjoyed getting to hear everybody's opinion here today and I think what's going to happen too. I think there's a new generation of buyers, a new set of CXO influencers in here. And I think what Oracle's done with this, MySQL HeatWave, those benchmarks that Ron talked about so eloquently here that is going to become something that forces other companies, not just try to get incrementally better. I think we're going to see a massive new wave of innovation to try to play catch up. So I really take my hat off to Oracle's achievement from going to, push everybody to be better. >> Excellent. Marc Staimer, what do you say? >> Sure, I'm going to leverage off of something Matt said earlier, "Those companies that are going to develop faster, cheaper, simpler products that are going to solve customer problems, IT problems are the ones that are going to succeed, or the ones who are going to grow. The one who are just focused on the technology are going to fall by the wayside." So those who can solve more problems, do it more elegantly and do it for less money are going to do great. So Oracle's going down that path today, Snowflake's going down that path. They're trying to do more integration with third party, but as a result, aiming at that simpler, faster, cheaper mentality is where you're going to continue to see this market go. >> Amen brother Marc. >> Thank you, Ron Westfall, we'll give you the last word, bring us home. >> Well, thank you. And I'm loving it. I see a wave of innovation across the entire cloud database ecosystem and Oracle is fueling it. We are seeing it, with the native integration of auto ML capabilities, elastic scaling, lower entry price points, et cetera. And this is just going to be great news for buyers, but also developers and increased use of open APIs. And so I think that is really the key takeaways. Just we're going to see a lot of great innovation on the horizon here. >> Guys, fantastic insights, one of the best power panel as I've ever done. Love to have you back. Thanks so much for coming on today. >> Great job, Dave, thank you. >> All right, and thank you for watching. This is Dave Vellante for theCube and we'll see you next time. (soft music)

(upbeat music) >> When Oracle acquired Sun in 2009, it paid $5.6 billion net of Sun's cash and debt. Now I argued at the time that Oracle got one of the best deals in the history of enterprise tech, and I got a lot of grief for saying that because Sun had a declining business, it was losing money, and its revenue was under serious pressure as it tried to hang on for dear life. But Safra Catz understood that Oracle could pay Sun's lower profit and lagging businesses, like its low index 86 product lines, and even if Sun's revenue was cut in half, because Oracle has such a high revenue multiple as a software company, it could almost instantly generate $25 to $30 billion in shareholder value on paper. In addition, it was a catalyst for Oracle to initiate its highly differentiated engineering systems business, and was actually the precursor to Oracle's Cloud. Oracle saw that it could capture high margin dollars that used to go to partners like HP, it's original exit data partner, and get paid for the full stack across infrastructure, middleware, database, and application software, when eventually got really serious about cloud. Now there was also a major technology angle to this story. Remember Sun's tagline, "the network is the computer"? Well, they should have just called it cloud. Through the Sun acquisition. Oracle also got a couple of key technologies, Java, the number one programming language in the world, and MySQL, a key ingredient of the LAMP stack, that's Linux, Apache, MySQL and PHP, Perl or Python, on which the internet is basically built, and is used by many cloud services like Facebook, Twitter, WordPress, Flicker, Amazon, Aurora, and many other examples, including, by the way, Maria DB, which is a fork of MySQL created by MySQL's creator, basically in protest to Oracle's acquisition; the drama is Oscar worthy. It gets even better. In 2020, Oracle began introducing a new version of MySQL called MySQL HeatWave, and since late 2020 it's been in sort of a super cycle rolling, out three new releases in less than a year and a half in an attempt to expand its Tam and compete in new markets. Now we covered the release of MySQL Autopilot, which uses machine learning to automate management functions. And we also covered the bench marketing that Oracle produced against Snowflake, AWS, Azure, and Google. And Oracle's at it again with HeatWave, adding machine learning into its database capabilities, along with previously available integrations of OLAP and OLTP. This, of course, is in line with Oracle's converged database philosophy, which, as we've reported, is different from other cloud database providers, most notably Amazon, which takes the right tool for the right job approach and chooses database specialization over a one size fits all strategy. Now we've asked Oracle to come on theCUBE and explain these moves, and I'm pleased to welcome back Nipun Agarwal, who's the senior vice president for MySQL Database and HeatWave at Oracle. And today, in this video exclusive, we'll discuss machine learning, other new capabilities around elasticity and compression, and then any benchmark data that Nipun wants to share. Nipun's been a leading advocate of the HeatWave program. He's led engineering in that team for over 10 years, and he has over 185 patents in database technologies. Welcome back to the show Nipun. Great to see you again. Thanks for coming on. >> Thank you, Dave. Very happy to be back. >> Yeah, now for those who may not have kept up with the news, maybe to kick things off you could give us an overview of what MySQL HeatWave actually is so that we're all on the same page. >> Sure, Dave, MySQL HeatWave is a fully managed MySQL database service from Oracle, and it has a builtin query accelerator called HeatWave, and that's the part which is unique. So with MySQL HeatWave, customers of MySQL get a single database which they can use for transactional processing, for analytics, and for mixed workloads because traditionally MySQL has been designed and optimized for transaction processing. So in the past, when customers had to run analytics with the MySQL based service, they would need to move the data out of MySQL into some other database for running analytics. So they would end up with two different databases and it would take some time to move the data out of MySQL into this other system. With MySQL HeatWave, we have solved this problem and customers now have a single MySQL database for all their applications, and they can get the good performance of analytics without any changes to their MySQL application. >> Now it's no secret that a lot of times, you know, queries are not, you know, most efficiently written, and critics of MySQL HeatWave will claim that this product is very memory and cluster intensive, it has a heavy footprint that adds to cost. How do you answer that, Nipun? >> Right, so for offering any database service in the cloud there are two dimensions, performance and cost, and we have been very cognizant of both of them. So it is indeed the case that HeatWave is a, in-memory query accelerator, which is why we get very good performance, but it is also the case that we have optimized HeatWave for commodity cloud services. So for instance, we use the least expensive compute. We use the least expensive storage. So what I would suggest is for the customers who kind of would like to know what is the price performance advantage of HeatWave compared to any database we have benchmark against, Redshift, Snowflake, Google BigQuery, Azure Synapse, HeatWave is significantly faster and significantly lower price on a multitude of workloads. So not only is it in-memory database and optimized for that, but we have also optimized it for commodity cloud services, which makes it much lower price than the competition. >> Well, at the end of the day, it's customers that sort of decide what the truth is. So to date, what's been the customer reaction? Are they moving from other clouds from on-prem environments? Both why, you know, what are you seeing? >> Right, so we are definitely a whole bunch of migrations of customers who are running MySQL on-premise to the cloud, to MySQL HeatWave. That's definitely happening. What is also very interesting is we are seeing that a very large percentage of customers, more than half the customers who are coming to MySQL HeatWave, are migrating from other clouds. We have a lot of migrations coming from AWS Aurora, migrations from RedShift, migrations from RDS MySQL, TerriData, SAP HANA, right. So we are seeing migrations from a whole bunch of other databases and other cloud services to MySQL HeatWave. And the main reason we are told why customers are migrating from other databases to MySQL HeatWave are lower cost, better performance, and no change to their application because many of these services, like AWS Aurora are ETL compatible with MySQL. So when customers try MySQL HeatWave, not only do they get better performance at a lower cost, but they find that they can migrate their application without any changes, and that's a big incentive for them. >> Great, thank you, Nipun. So can you give us some names? Are there some real world examples of these customers that have migrated to MySQL HeatWave that you can share? >> Oh, absolutely, I'll give you a few names. Stutor.com, this is an educational SaaS provider raised out of Brazil. They were using Google BigQuery, and when they migrated to MySQL HeatWave, they found a 300X, right, 300 times improvement in performance, and it lowered their cost by 85 (audio cut out). Another example is Neovera. They offer cybersecurity solutions and they were running their application on an on-premise version of MySQL when they migrated to MySQL HeatWave, their application improved in performance by 300 times and their cost reduced by 80%, right. So by going from on-premise to MySQL HeatWave, they reduced the cost by 80%, improved performance by 300 times. We are Glass, another customer based out of Brazil. They were running on AWS EC2, and when they migrated, within hours they found that there was a significant improvement, like, you know, over 5X improvement in database performance, and they were able to accommodate a very large virtual event, which had more than a million visitors. Another example, Genius Senority. They are a game designer in Japan, and when they moved to MySQL HeatWave, they found a 90 times percent improvement in performance. And there many, many more like a lot of migrations, again, from like, you know, Aurora, RedShift and many other databases as well. And consistently what we hear is (audio cut out) getting much better performance at a much lower cost without any change to their application. >> Great, thank you. You know, when I ask that question, a lot of times I get, "Well, I can't name the customer name," but I got to give Oracle credit, a lot of times you guys have at your fingertips. So you're not the only one, but it's somewhat rare in this industry. So, okay, so you got some good feedback from those customers that did migrate to MySQL HeatWave. What else did they tell you that they wanted? Did they, you know, kind of share a wishlist and some of the white space that you guys should be working on? What'd they tell you? >> Right, so as customers are moving more data into MySQL HeatWave, as they're consolidating more data into MySQL HeatWave, customers want to run other kinds of processing with this data. A very popular one is (audio cut out) So we have had multiple customers who told us that they wanted to run machine learning with data which is stored in MySQL HeatWave, and for that they have to extract the data out of MySQL (audio cut out). So that was the first feedback we got. Second thing is MySQL HeatWave is a highly scalable system. What that means is that as you add more nodes to a HeatWave cluster, the performance of the system improves almost linearly. But currently customers need to perform some manual steps to add most to a cluster or to reduce the cluster size. So that was other feedback we got that people wanted this thing to be automated. Third thing is that we have shown in the previous results, that HeatWave is significantly faster and significantly lower price compared to competitive services. So we got feedback from customers that can we trade off some performance to get even lower cost, and that's what we have looked at. And then finally, like we have some results on various data sizes with TPC-H. Customers wanted to see if we can offer some more data points as to how does HeatWave perform on other kinds of workloads. And that's what we've been working on for the several months. >> Okay, Nipun, we're going to get into some of that, but, so how did you go about addressing these requirements? >> Right, so the first thing is we are announcing support for in-database machine learning, meaning that customers who have their data inside MySQL HeatWave can now run training, inference, and prediction all inside the database without the data or the model ever having to leave the database. So that's how we address the first one. Second thing is we are offering support for real time elasticity, meaning that customers can scale up or scale down to any number of nodes. This requires no manual intervention on part of the user, and for the entire duration of the resize operation, the system is fully available. The third, in terms of the costs, we have double the amount of data that can be processed per node. So if you look at a HeatWave cluster, the size of the cluster determines the cost. So by doubling the amount of data that can be processed per node, we have effectively reduced the cluster size which is required for planning a given workload to have, which means it reduces the cost to the customer by half. And finally, we have also run the TPC-DS workload on HeatWave and compared it with other vendors. So now customers can have another data point in terms of the performance and the cost comparison of HeatWave with other services. >> All right, and I promise, I'm going to ask you about the benchmarks, but I want to come back and drill into these a bit. How is HeatWave ML different from competitive offerings? Take for instance, Redshift ML, for example. >> Sure, okay, so this is a good comparison. Let's start with, let's say RedShift ML, like there are some systems like, you know, Snowflake, which don't even offer any, like, processing of machine learning inside the database, and they expect customers to write a whole bunch of code, in say Python or Java, to do machine learning. RedShift ML does have integration with SQL. That's a good start. However, when customers of Redshift need to run machine learning, and they invoke Redshift ML, it makes a call to another service, SageMaker, right, where so the data needs to be exported to a different service. The model is generated, and the model is also outside RedShift. With HeatWave ML, the data resides always inside the MySQL database service. We are able to generate models. We are able to train the models, run inference, run explanations, all inside the MySQL HeatWave service. So the data, or the model, never have to leave the database, which means that both the data and the models can now be secured by the same access control mechanisms as the rest of the data. So that's the first part, that there is no need for any ETL. The second aspect is the automation. Training is a very important part of machine learning, right, and it impacts the quality of the predictions and such. So traditionally, customers would employ data scientists to influence the training process so that it's done right. And even in the case of Redshift ML, the users are expected to provide a lot of parameters to the training process. So the second thing which we have worked on with HeatWave ML is that it is fully automated. There is absolutely no user intervention required for training. Third is in terms of performance. So one of the things we are very, very sensitive to is performance because performance determines the eventual cost to the customer. So again, in some benchmarks, which we have published, and these are all available on GitHub, we are showing how HeatWave ML is 25 times faster than Redshift ML, and here's the kicker, at 1% of the cost. So four benefits, the data all remain secure inside the database service, it's fully automated, much faster, much lower cost than the competition. >> All right, thank you Nipun. Now, so there's a lot of talk these days about explainability and AI. You know, the system can very accurately tell you that it's a cat, you know, or for you Silicon Valley fans, it's a hot dog or not a hot dog, but they can't tell you how the system got there. So what is explainability, and why should people care about it? >> Right, so when we were talking to customers about what they would like from a machine learning based solution, one of the feedbacks we got is that enterprise is a little slow or averse to uptaking machine learning, because it seems to be, you know, like magic, right? And enterprises have the obligation to be able to explain, or to provide a answer to their customers as to why did the database make a certain choice. With a rule based solution it's simple, it's a rule based thing, and you know what the logic was. So the reason explanations are important is because customers want to know why did the system make a certain prediction? One of the important characteristics of HeatWave ML is that any model which is generated by HeatWave ML can be explained, and we can do both global explanations or model explanations as well as we can also do local explanations. So when the system makes a specific prediction using HeatWave ML, the user can find out why did the system make such a prediction? So for instance, if someone is being denied a loan, the user can figure out what were the attribute, what were the features which led to that decision? So this ensures, like, you know, fairness, and many of the times there is also like a need for regulatory compliance where users have a right to know. So we feel that explanations are very important for enterprise workload, and that's why every model which is generated by HeatWave ML can be explained. >> Now I got to give Snowflakes some props, you know, this whole idea of separating compute from storage, but also bringing the database to the cloud and driving elasticity. So that's been a key enabler and has solved a lot of problems, in particular the snake swallowing the basketball problem, as I often say. But what about elasticity and elasticity in real time? How is your version, and there's a lot of companies chasing this, how is your approach to an elastic cloud database service different from what others are promoting these days? >> Right, so a couple of characteristics. One is that we have now fully automated the process of elasticity, meaning that if a user wants to scale up or scale down, the only thing they need to specify is the eventual size of the cluster and the system completely takes care of it transparently. But then there are a few characteristics which are very unique. So for instance, we can scale up or scale down to any number of nodes. Whereas in the case of Snowflake, the number of nodes someone can scale up or scale down to are the powers of two. So if a user needs 70 CPUs, well, their choice is either 64 or 128. So by providing this flexibly with MySQL HeatWave, customers get a custom fit. So they can get a cluster which is optimized for their specific portal. So that's the first thing, flexibility of scaling up or down to any number of nodes. The second thing is that after the operation is completed, the system is fully balanced, meaning the data across the various nodes is fully balanced. That is not the case with many solutions. So for instance, in the case of Redshift, after the resize operation is done, the user is expected to manually balance the data, which can be very cumbersome. And the third aspect is that while the resize operation is going on, the HeatWave cluster is completely available for queries, for DMLS, for loading more data. That is, again, not the case with Redshift. Redshift, suppose the operation takes 10 to 15 minutes, during that window of time, the system is not available for writes, and for a big part of that chunk of time, the system is not even available for queries, which is very limiting. So the advantages we have are fully flexible, the system is in a balanced state, and the system is completely available for the entire duration operation. >> Yeah, I guess you got that hypergranularity, which, you know, sometimes they say, "Well, t-shirt sizes are good enough," but then I think of myself, some t-shirts fit me better than others, so. Okay, I saw on the announcement that you have this lower price point for customers. How did you actually achieve this? Could you give us some details around that please? >> Sure, so there are two things for announcing this service, which lower the cost for the customers. The first thing is that we have doubled the amount of data that can be processed by a HeatWave node. So if we have doubled the amount of data, which can be a process by a node, the cluster size which is required by customers reduces to half, and that's why the cost drops to half. The way we have managed to do this is by two things. One is support for Bloom filters, which reduces the amount of intermediate memory. And second is we compress the base data. So these are the two techniques we have used to process more data per node. The second way by which we are lowering the cost for the customers is by supporting pause and resume of HeatWave. And many times you find customers of like HeatWave and other services that they want to run some other queries or some other workloads for some duration of time, but then they don't need the cluster for a few hours. Now with the support for pause and resume, customers can pause the cluster and the HeatWave cluster instantaneously stops. And when they resume, not only do we fetch the data, in a very, like, you know, a quick pace from the object store, but we also preserve all the statistics, which are used by Autopilot. So both the data and the metadata are fetched, extremely fast from the object store. So with these two capabilities we feel that it'll drive down the cost to our customers even more. >> Got it, thank you. Okay, I promised I was going to get to the benchmarks. Let's have it. How do you compare with others but specifically cloud databases? I mean, and how do we know these benchmarks are real? My friends at EMC, they were back in the day, they were brilliant at doing benchmarks. They would produce these beautiful PowerPoints charts, but it was kind of opaque, but what do you say to that? >> Right, so there are multiple things I would say. The first thing is that this time we have published two benchmarks, one is for machine learning and other is for SQL analytics. All the benchmarks, including the scripts which we have used are available on GitHub. So we have full transparency, and we invite and encourage customers or other service providers to download the scripts, to download the benchmarks and see if they get any different results, right. So what we are seeing, we have published it for other people to try and validate. That's the first part. Now for machine learning, there hasn't been a precedence for enterprise benchmarks so we talk about aiding open data sets and we have published benchmarks for those, right? So both for classification, as well as for aggression, we have run the training times, and that's where we find that HeatWave MLS is 25 times faster than RedShift ML at one percent of the cost. So fully transparent, available. For SQL analytics, in the past we have shown comparisons with TPC-H. So we would show TPC-H across various databases, across various data sizes. This time we decided to use TPC-DS. the advantage of TPC-DS over TPC-H is that it has more number of queries, the queries are more complex, the schema is more complex, and there is a lot more data skew. So it represents a different class of workloads, and which is very interesting. So these are queries derived from the TPC-DS benchmark. So the numbers we have are published this time are for 10 terabyte TPC-DS, and we are comparing with all the four majors services, Redshift, Snowflake, Google BigQuery, Azure Synapse. And in all the cases, HeatWave is significantly faster and significantly lower priced. Now one of the things I want to point out is that when we are doing the cost comparison with other vendors, we are being overly fair. For instance, the cost of HeatWave includes the cost of both the MySQL node as well as the HeatWave node, and with this setup, customers can run transaction processing analytics as well as machine learning. So the price captures all of it. Whereas with the other vendors, the comparison is only for the analytic queries, right? So if customers wanted to run RDP, you would need to add the cost of that database. Or if customers wanted to run machine learning, you would need to add the cost of that service. Furthermore, with the case of HeatWave, we are quoting pay as you go price, whereas for other vendors like, you know, RedShift, and like, you know, where applicable, we are quoting one year, fully paid upfront cost rate. So it's like, you know, very fair comparison. So in terms of the numbers though, price performance for TPC-DS, we are about 4.8 times better price performance compared to RedShift We are 14.4 times better price performance compared to Snowflake, 13 times better than Google BigQuery, and 15 times better than Synapse. So across the board, we are significantly faster and significantly lower price. And as I said, all of these scripts are available in GitHub for people to drive for themselves. >> Okay, all right, I get it. So I think what you're saying is, you could have said this is what it's going to cost for you to do both analytics and transaction processing on a competitive platform versus what it takes to do that on Oracle MySQL HeatWave, but you're not doing that. You're saying, let's take them head on in their sweet spot of analytics, or OLTP separately and you're saying you still beat them. Okay, so you got this one database service in your cloud that supports transactions and analytics and machine learning. How much do you estimate your saving companies with this integrated approach versus the alternative of kind of what I called upfront, the right tool for the right job, and admittedly having to ETL tools. How can you quantify that? >> Right, so, okay. The numbers I call it, right, at the end of the day in a cloud service price performance is the metric which gives a sense as to how much the customers are going to save. So for instance, for like a TPC-DS workload, if we are 14 times better price performance than Snowflake, it means that our cost is going to be 1/14th for what customers would pay for Snowflake. Now, in addition, in other costs, in terms of migrating the data, having to manage two different databases, having to pay for other service for like, you know, machine learning, that's all extra and that depends upon what tools customers are using or what other services they're using for transaction processing or for machine learning. But these numbers themselves, right, like they're very, very compelling. If we are 1/5th the cost of Redshift, right, or 1/14th of Snowflake, these numbers, like, themselves are very, very compelling. And that's the reason we are seeing so many of these migrations from these databases to MySQL HeatWave. >> Okay, great, thank you. Our last question, in the Q3 earnings call for fiscal 22, Larry Ellison said that "MySQL HeatWave is coming soon on AWS," and that caught a lot of people's attention. That's not like Oracle. I mean, people might say maybe that's an indication that you're not having success moving customers to OCI. So you got to go to other clouds, which by the way I applaud, but any comments on that? >> Yep, this is very much like Oracle. So if you look at one of the big reasons for success of the Oracle database and why Oracle database is the most popular database is because Oracle database runs on all the platforms, and that has been the case from day one. So very akin to that, the idea is that there's a lot of value in MySQL HeatWave, and we want to make sure that we can offer same value to the customers of MySQL running on any cloud, whether it's OCI, whether it's the AWS, or any other cloud. So this shows how confident we are in our offering, and we believe that in other clouds as well, customers will find significant advantage by having a single database, which is much faster and much lower price then what alternatives they currently have. So this shows how confident we are about our products and services. >> Well, that's great, I mean, obviously for you, you're in MySQL group. You love that, right? The more places you can run, the better it is for you, of course, and your customers. Okay, Nipun, we got to leave it there. As always it's great to have you on theCUBE, really appreciate your time. Thanks for coming on and sharing the new innovations. Congratulations on all the progress you're making here. You're doing a great job. >> Thank you, Dave, and thank you for the opportunity. >> All right, and thank you for watching this CUBE conversation with Dave Vellante for theCUBE, your leader in enterprise tech coverage. We'll see you next time. (upbeat music)

>>Hey everyone. Welcome back to the cubes. Live coverage of women in data science, worldwide conference widths 2022. I'm Lisa Martin coming to you from Stanford university at the Arriaga alumni center. And I'm pleased to welcome my next guest. Hannah Sperling joins me business process intelligence or BPI, academic and research alliances at SAP HANA. Welcome to the program. >>Hi, thank you so much for having me. >>So you just flew in from Germany. >>I did last week. Yeah. Long way away. I'm very excited to be here. Uh, but before we get started, I would like to say that I feel very fortunate to be able to be here and that my heart and vicious still goes out to people that might be in more difficult situations right now. I agree >>Such a it's one of my favorite things about Wiz is the community that it's grown into. There's going to be about a 100,000 people that will be involved annually in woods, but you walk into the Arriaga alumni center and you feel this energy from all the women here, from what Margo and teams started seven years ago to what it has become. I was happened to be able to meet listening to one of the panels this morning, and they were talking about something that's just so important for everyone to hear, not just women, the importance of mentors and sponsors, and being able to kind of build your own personal board of directors. Talk to me about some of the mentors that you've had in the past and some of the ones that you have at SAP now. >>Yeah. Thank you. Um, that's actually a great starting point. So maybe talk a bit about how I got involved in tech. Yeah. So SAP is a global software company, but I actually studied business and I was hired directly from university, uh, around four years ago. And that was to join SAP's analytics department. And I've always had a weird thing for databases, even when I was in my undergrad. Um, I did enjoy working with data and so working in analytics with those teams and some people mentoring me, I got into database modeling and eventually ventured even further into development was working in analytics development for a couple of years. And yeah, still am with a global software provider now, which brought me to women and data science, because now I'm also involved in research again, because yeah, some reason couldn't couldn't get enough of that. Um, maybe learn about the stuff that I didn't do in my undergrad. >>And post-grad now, um, researching at university and, um, yeah, one big part in at least European data science efforts, um, is the topic of sensitive data and data privacy considerations. And this is, um, also topic very close to my heart because you can only manage what you measure, right. But if everybody is afraid to touch certain pieces of sensitive data, I think we might not get to where we want to be as fast as we possibly could be. And so I've been really getting into a data and anonymization procedures because I think if we could random a workforce data usable, especially when it comes to increasing diversity in stem or in technology jobs, we should really be, um, letting the data speak >>And letting the data speak. I like that. One of the things they were talking about this morning was the bias in data, the challenges that presents. And I've had some interesting conversations on the cube today, about data in health care data in transportation equity. Where do you, what do you think if we think of international women's day, which is tomorrow the breaking the bias is the theme. Where do you think we are from your perspective on breaking the bias that's across all these different data sets, >>Right. So I guess as somebody working with data on a daily basis, I'm sometimes amazed at how many people still seem to think that data can be unbiased. And this has actually touched upon also in the first keynote that I very much enjoyed, uh, talking about human centered data science people that believe that you can take the human factor out of any effort related to analysis, um, are definitely on the wrong path. So I feel like the sooner that we realize that we need to take into account certain bias sees that will definitely be there because data is humanly generated. Um, the closer we're going to get to something that represents reality better and might help us to change reality for the better as well, because we don't want to stick with the status quo. And any time you look at data, it's definitely gonna be a backward looking effort. So I think the first step is to be aware of that and not to strive for complete objectivity, but understanding and coming to terms with the fact just as it was mentioned in the equity panel, that that is logically impossible, right? >>That's an important, you bring up a really important point. It's important to understand that that is not possible, but what can we work with? What is possible? What can we get to, where do you think we are on the journey of being able to get there? >>I think that initiatives like widths of playing an important role in making that better and increasing that awareness there a big trend around explainability interpretability, um, an AI that you see, not just in Europe, but worldwide, because I think the awareness around those topics is increasing. And that will then, um, also show you the blind spots that you may still have, no matter how much you think about, um, uh, the context. Um, one thing that we still need to get a lot better at though, is including everybody in these types of projects, because otherwise you're always going to have a certain selection in terms of prospectus that you're getting it >>Right. That thought diversity there's so much value in thought diversity. That's something that I think I first started talking about thought diversity at a Wood's conference a few years ago, and really understanding the impact there that that can make to every industry. >>Totally. And I love this example of, I think it was a soap dispenser. I'm one of these really early examples of how technology, if you don't watch out for these, um, human centered considerations, how technology can, can go wrong and just, um, perpetuate bias. So a soap dispenser that would only recognize the hand, whether it was a certain, uh, light skin type that w you know, be placed underneath it. So it's simple examples like that, um, that I think beautifully illustrate what we need to watch out for when we design automatic decision aids, for example, because anywhere where you don't have a human checking, what's ultimately decided upon you end up, you might end up with much more grave examples, >>Right? No, it's, it's I agree. I, Cecilia Aragon gave the talk this morning on the human centered guy. I was able to interview her a couple of weeks ago for four winds and a very inspiring woman and another herself, but she brought up a great point about it's the humans and the AI working together. You can't ditch the humans completely to your point. There are things that will go wrong. I think that's a sends a good message that it's not going to be AI taking jobs, but we have to have those two components working better. >>Yeah. And maybe to also refer to the panel discussion we heard, um, on, on equity, um, I very much liked professor Bowles point. Um, I, and how she emphasized that we're never gonna get to this perfectly objective state. And then also during that panel, um, uh, data scientists said that 80% of her work is still cleaning the data most likely because I feel sometimes there is this, um, uh, almost mysticism around the role of a data scientist that sounds really catchy and cool, but, um, there's so many different aspects of work in data science that I feel it's hard to put that all in a nutshell narrowed down to one role. Um, I think in the end, if you enjoy working with data, and maybe you can even combine that with a certain domain that you're particularly interested in, be it sustainability, or, you know, urban planning, whatever that is the perfect match >>It is. And having that passion that goes along with that also can be very impactful. So you love data. You talked about that, you said you had a strange love for databases. Where do you, where do you want to go from where you are now? How much more deeply are you going to dive into the world of data? >>That's a good question because I would, at this point, definitely not consider myself a data scientist, but I feel like, you know, taking baby steps, I'm maybe on a path to becoming one in the future. Um, and so being at university, uh, again gives me, gives me the opportunity to dive back into certain courses and I've done, you know, smaller data science projects. Um, and I was actually amazed at, and this was touched on in a panel as well earlier. Um, how outdated, so many, um, really frequently used data sets are shown the realm of research, you know, AI machine learning, research, all these models that you feed with these super outdated data sets. And that's happened to me like something I can relate to. Um, and then when you go down that path, you come back to the sort of data engineering path that I really enjoy. So I could see myself, you know, keeping on working on that, the whole data, privacy and analytics, both topics that are very close to my heart, and I think can be combined. They're not opposites. That is something I would definitely stay true to >>Data. Privacy is a really interesting topic. We're seeing so many, you know, GDPR was how many years did a few years old that is now, and we've got other countries and states within the United States, for example, there's California has CCPA, which will become CPRA next year. And it's expanding the definition of what private sensitive data is. So we're companies have to be sensitive to that, but it's a huge challenge to do so because there's so much potential that can come from the data yet, we've got that personal aspect, that sensitive aspect that has to be aware of otherwise there's huge fines. Totally. Where do you think we are with that in terms of kind of compliance? >>So, um, I think in the past years we've seen quite a few, uh, rather shocking examples, um, in the United States, for instance, where, um, yeah, personal data was used or all proxies, um, that led to, uh, detrimental outcomes, um, in Europe, thanks to the strong data regulations. I think, um, we haven't had as many problems, but here the question remains, well, where do you draw the line? And, you know, how do you design this trade-off in between increasing efficiency, um, making business applications better, for example, in the case of SAP, um, while protecting the individual, uh, privacy rights of, of people. So, um, I guess in one way, SAP has a, as an easier position because we deal with business data. So anybody who doesn't want to care about the human element maybe would like to, you know, try building models and machine generated data first. >>I mean, at least I would feel much more comfortable because as soon as you look at personally identifiable data, you really need to watch out, um, there is however ways to make that happen. And I was touching upon these anonymization techniques that I think are going to be, um, more and more important in the, in the coming years, there is a proposed on the way by the European commission. And I was actually impressed by the sophisticated newness of legislation in, in that area. And the plan is for the future to tie the rules around the use of data science, to the specific objectives of the project. And I think that's the only way to go because of the data's out there it's going to be used. Right. We've sort of learned that and true anonymization might not even be possible because of the amount of data that's out there. So I think this approach of, um, trying to limit the, the projects in terms of, you know, um, looking at what do they want to achieve, not just for an individual company, but also for us as a society, think that needs to play a much bigger role in any data-related projects where >>You said getting true anonymization isn't really feasible. Where are we though on the anonymization pathway, >>If you will. I mean, it always, it's always the cost benefit trade off, right? Because if the question is not interesting enough, so if you're not going to allocate enough resources in trying to reverse engineer out an old, the tie to an individual, for example, sticking true to this, um, anonymization example, um, nobody's going to do it right. We live in a world where there's data everywhere. So I feel like that that's not going to be our problem. Um, and that is why this approach of trying to look at the objectives of a project come in, because, you know, um, sometimes maybe we're just lucky that it's not valuable enough to figure out certain details about our personal lives so that nobody will try, because I am sure that if people, data scientists tried hard enough, um, I wonder if there's challenges they wouldn't be able to solve. >>And there has been companies that have, you know, put out data sets that were supposedly anonymized. And then, um, it wasn't actually that hard to make interferences and in the, in the panel and equity one lab, one last thought about that. Um, we heard Jessica speak about, uh, construction and you know, how she would, um, she was trying to use, um, synthetic data because it's so hard to get the real data. Um, and the challenge of getting the synthetic data to, um, sort of, uh, um, mimic the true data. And the question came up of sensors in, in the household and so on. That is obviously a huge opportunity, but for me, it's somebody who's, um, very sensitive when it comes to privacy considerations straight away. I'm like, but what, you know, if we generate all this data, then somebody uses it for the wrong reasons, which might not be better urban planning for all different communities, but simple profit maximization. Right? So this is something that's also very dear to my heart, and I'm definitely going to go down that path further. >>Well, Hannah, it's been great having you on the program. Congratulations on being a Wood's ambassador. I'm sure there's going to be a lot of great lessons and experiences that you'll take back to Germany from here. Thank you so much. We appreciate your time for Hannah Sperling. I'm Lisa Martin. You're watching the QS live coverage of women in data science conference, 2020 to stick around. I'll be right back with my next guest.

(bright music) >> Welcome back everyone to theCUBE's coverage of AWS re:Invent 2021 in person. So a live event, physical in-person, also virtual hybrid. So a lot of great action online, check out the website. All the videos are there on theCUBE, as well as what's going on all of the actions on site and theCUBE's here. I'm John Furrier, your host with Dave Vellante, my cohost. Finally, we've got David Brown, VP of Elastic Compute Cloud. EC2, the bread and butter. Our favorite part of Amazon. David, great to have you back on theCUBE in person. >> John, it's great to be back. It's the first time I'd been on theCUBE in person as well. A lot of virtual events with you guys, but it's amazing to be back at re:Invent. >> We're so excited for you. I know, Matt Garman and I've talked in the past. We've talked in the past. EC2 is just an amazing product. It's always been the core block of AWS. More and more action happening and developers are now getting more action and there's well, we wrote a big piece about it. What's going on? The Silicon's really paying off. You've got to also general purpose Intel and AMD, and you've got the custom silicon, all working together. What's the new update? Give us a scoop. >> Well, John, it's actually 15 years of EC2 this year and I've been lucky to be on that team for 14 years and so incredible to see the growth. It's been an amazing journey. The thing that's really driven us, two things. One is supporting new workloads. And so what are the workloads that customers have available out there trying to do on the cloud that we don't support and launch new instance types. And that's the first thing. The second one is price performance. How do we give customers more performance at a continuously decreasing price year-over-year? And that's just driven innovation across EC2 over the years with things like Graviton. All of our inferential chips are custom silicon, but also instance types with the latest Intel Ice Lake CPU's, latest Milan. We just announced the AMD Milan instance. It's just constantly innovation across the ever-increasing list of instances. So super exciting. >> So instances become the new thing. Provision an instance, spin up an instance. Instance becomes, and you can get instances, flavors, almost like flavors, right? >> David: Yeah. >> Take us through the difference between an instance and then the EC2 itself. >> That's correct, yeah. So we actually have, by end of the year, right now we have over 475 different instances available to you whether it's GPU accelerators, high-performance computing instances, memory optimized, just enormous number. We'll actually hit 500 by the end of the year, but that is it. I mean, customers are looking for different types of machines and those are the instances. >> So the Custom Silicon, it's one of the most interesting developments. We've written about it. AWS secret weapon is one of them. I wonder if you could take us back to the decision points and the journey. The Annapurna acquisition, you started working with them as a partner, then you said, all right, let's just buy the company. >> David: Yeah. >> And then now, you're seeing the acceleration, your time to tapeout is way, way compressed. Maybe what was the catalyst and maybe we can get into where it's going. >> Yeah, absolutely. Super interesting story 'cause it actually starts all the way back in 2008. In 2008, EC2 had actually been around for just a little under two years. And if you remember back then, everybody was like, will virtualize and hypervisors, specialization would never really get you the same performances, what they were calling bare metal back then. Everybody's looking at the cloud. And so we took a look at that. And I mean, network latencies, in some cases with hypervisors were as high as 200 or 300 milliseconds. And it was a number of real challenges. And so we knew that we would have to change the way that virtualization works and get into hardware. And so in 2010, 2011, we started to look at how could I offload my network processing, my IO processing to additional hardware. And that's what we delivered our first Nitro card in 2012 and 2013. We actually offloaded all of the processing of network to a Nitro card. And that Nitro card actually had a Annapurna arm chip on it. Our Nitro 1 chip. >> For the offload? >> The offload card, yeah. And so that's when my team started to code for Arm. We started to work on our Linux works for Arm. We actually had to write our own operating system initially 'cause there weren't any operating systems available we could use. And so that's what we started this journey. And over the years, when we saw how well it worked for networking, we said, let's do it for storage as well. And then we said, Hey, we could actually improve security significantly. And by 2017, we'd actually offloaded 100% of everything we did on that server to our offload cards Leaving a 100% of the server available for customers. And we're still actually the only cloud provider that does that today. >> Just to interject, in the data center today, probably 30% of the general purpose cores are used for offloads. You're saying 0% in the cloud. >> On our nitro instances, so every instance we've launched since 2017, our C5. We use 0% of that central core. And you can actually see that in our instance types. If you look at our largest instance type, you can see that we're giving you 96 cores and we're giving you, and our largest instance, 24 terabytes of memory. We're not giving you 23.6 terabytes 'cause we need some. It's all given to you as the customer. >> So much more efficient, >> Much, much more efficient, much better, better price performance as well. But then ultimately those Nitro chips, we went through Nitro 1, Nitro 2, Nitro 3, Nitro 4. We said, Hey, could we build a general purpose server chip? Could we actually bring Arm into the cloud? And in 2018, we launched the A1 instance, which was our Graviton1 instance. And what we didn't tell people at the time is that it was actually the same chip we were using on our network card. So essentially, it was a network card that we were giving to you as a server. But what it did is it sparked the ecosystem. That's why we put it out there. And I remember before launch, some was saying, is this just going to be a university project? Are we going to see people from big universities using Arm in the cloud? Was it really going to take off? And the response was amazing. The ecosystem just grew. We had customers move to it and immediately begin to see improvements. And we knew that a year later, Graviton2 was going to come out. And Graviton2 was just an amazing chip. It continues to see incredible adoption, 40% price performance improvement over other instances. >> So this is worth calling out because I think that example of the network card, I mean, innovation can come from anywhere. This is what Jassy always would say is do the experiments. Think about the impact of what's going on here. You're focused on a mission. Let's get that processing of the lowest cost, pick up some workloads. So you're constantly tinkering with tuning the engine. New discovery comes in. Nitro is born. The chip comes in. But I think the fundamental thing, and I want to get your reaction to this 'cause we've put this out there on our post on Sunday. And I said, in every inflection point, I'm old enough, my birthday was yesterday. I'm old enough to know that. >> David: I saw that. >> I'm old enough to know that in the eighties, the client server shifts. Every inflection point where development changed, the methodology, the mindset or platforms change, all the apps went to the better platform. Who wants to run their application on a slower platform? And so, and those inflects. So now that's happening now, I believe. So you got better performance and I'm imagining that the app developers are coding for it. Take us through how you see that because okay, you're offering up great performance for workloads. Now it's cloud workloads. That's almost all apps. Can you comment on that? >> Well, it has been really interesting to see. I mean, as I said, we were unsure who was going to use it when we initially launched and the adoption has been amazing. Initially, obviously it's always, a lot of the startups, a lot of the more agile companies that can move a lot faster, typically a little bit smaller. They started experimenting, but the data got out there. That 40% price performance was a reality. And not only for specific workloads, it was broadly successful across a number of workloads. And so we actually just had SAP who obviously is an enormous enterprise, supporting enterprises all over the world, announced that they are going to be moving the S/4 HANA Cloud to run on Graviton2. It's just phenomenal. And we've seen enterprises of that scale and game developers, every single vertical looking to move to Graviton2 and get that 40% price performance. >> Now we have to, as analysts, we have to say, okay, how did you get to that 40%? And you have to make some assumptions obviously. And it feels like you still have some dry powder when you looked at Graviton2. I think you were running, I don't know, it's speculated anyway. I don't know if you guys, it's your data, two and a half, 2.5 gigahertz. >> David: Yeah. >> I don't know if we can share what's going on with Graviton3, but my point is you had some dry powder and now with Graviton3, quite a range of performance, 'cause it really depends on the workload. >> David: That's right. >> Maybe you could give some insight as to that. What can you share about how you tuned Graviton3? >> When we look at benchmarking, we don't want to be trying to find that benchmark that's highly tuned and then put out something that is, Hey, this is the absolute best we can get it to and that's 40%. So that 40% is actually just on average. So we just went and ran real world workloads. And we saw some that were 55%. We saw some that were 25. It depends on what it was, but on average, it was around the 35, 45%, and we said 40%. And the great thing about that is customers come back and say, Hey, we saw 40% in this workload. It wasn't that I had to tune it. And so with Graviton3, launching this week. Available in our C7g instance, we said 25%. And that is just a very standard benchmark in what we're seeing. And as we start to see more customer workloads, I think it's going to be incredible to see what that range looks like. Graviton2 for single-threaded applications, it didn't give you that much of a performance. That's what we meant by cloud applications, generally, multi-threaded. In Graviton3, that's no longer the case. So we've had some customers report up to 80% performance improvements of Graviton2 to Graviton3 when the application was more of a single-threaded application. So we started to see. (group chattering) >> You have to keep going, the time to market is compressing. So you have that, go ahead, sorry. >> No, no, I always want to add one thing on the difference between single and multi-threaded applications. A lot of legacy, you're single threaded. So this is kind of an interesting thing. So the mainframe, migration stuff, you start to see that. Is that where that comes in the whole? >> Well, a lot of the legacy apps, but also even some of the new apps, like single threading like video transcoding, for example, is all done on a single core. It's very difficult. I mean, almost impossible to do that multi-threaded way. A lot of the crypto algorithms as well, encryption and cryptography is often single core. So with Graviton3, we've seen a significant performance boost for video encoding, cryptographic algorithms, that sort of thing, which really impacts even the most modern applications. >> So that's an interesting point because now single threaded is where the vertical use cases come in. It's not like more general purpose OS kind of things. >> Yeah, and Graviton has already been very broad. I think we're just knocking down the last few verticals where maybe it didn't support it and now it absolutely does. >> And if an ISV then ports, like an SAP's ports to Graviton, then the customer doesn't see any, I mean, they're going to see the performance difference, but they don't have to think about it. >> David: Yeah. >> They just say, I choose that instance and I'm going to get better price performance. >> Exactly, so we've seen that from our ISVs. We've also been doing that with our AWS services. So services like EMR, RDS, Elastic Cache, it will be moving and making Graviton2 available for customers, which means the customer doesn't have to do the migration at all. It's all done for them. They just pick the instance and get the price performance benefits, and so yeah. >> I think, oh, no, that was serverless. Sorry. >> Well, Lambda actually just did launch on Graviton2. And I think they were talking about a 35% price performance improvement. >> Who was that? >> Lambda, a couple of months ago. >> So what does an ISV have to do to port to Graviton. >> It's relatively straightforward, and this is actually one of the things that has slowed customers down is the, wow, that must be a big migration. And that ecosystem that I spoke about is the important part. And today, with all the Linux operating systems being available for Arm running on Graviton2, with all of the container runtimes being available, and then slowly open source applications in ISV is being available. It's actually really, really easy. And we just ran the Graviton2 four-day challenge. And we did that because we actually had an enterprise migrate one of the largest production applications in just four days. Now, I probably wouldn't recommend that to most enterprises that we see is a little too fast, but they could actually do that. >> But just from a numbers standpoint, that's insanely amazing. I mean, when you think about four days. >> Yeah. >> And when we talked on virtually last year, this year, I can't remember now. You said, we'll just try it. >> David: That's right. >> And see what happens, so I presume a lot of people have tried it. >> Well, that's my advice. It's the unknown, it's the what will it take? So take a single engineer, tell them and give them a time. Say you have one week, get this running on Graviton2, and I think the results are pretty amazing, very surprised. >> We were one of the first, if not the first to say that Arm is going to be dominant in the enterprise. We know it's dominant in the Edge. And when you look at the performance curves and the time to tape out, it's just astounding. And I don't know if people appreciate that relative to the traditional Moore's law curve. I mean, it's a style. And then when you combine the power of the CPU, the GPU, the NPU, kind of what Apple does in the iPhone, it blows away the historical performance curves. And you're on that curve. >> That's right. >> I wonder if you could sort of explain that. >> So with Graviton, we're optimizing just across every single part of AWS. So one of the nice things is we actually own that end-to-end. So when it starts with the early design of Graviton2 and Graviton3, and we obviously working on other chips right now. We're actually using the cloud to do all of the electronic design automation. So we're able to test with AWS how that Graviton3 chip is going to work long before we've even started taping it out. And so those workloads are running on high-frequency CPU's on Graviton. Actually we're using Graviton to build Graviton now in the cloud. The other thing we're doing is we're making sure that the Annapurna team that's building those CPUs is deeply engaged with my team and we're going to ultimately go and build those instances so that when that chip arrives from tapeout. I'm not waiting nine months or two years, like would normally be the case, but I actually had an instance up and running within a week or two on somebody's desk studying to do the integration. And that's something we've optimized significantly to get done. And so it allows us to get that iteration time. It also allows us to be very, very accurate with our tapeouts. We're not having to go back with Graviton. They're all A1 chips. We're not having to go back and do multiple runs of these things because we can do so much validation and performance testing in the cloud ahead of time. >> This is the epiphany of the Arm model. >> It really is. >> It's a standard. When you send it to the fab, they know what's going to work. You hit volume and it's just no fab. >> Well, this is a great thread. We'll stay on this 'cause Adam told us when we met with them for re:Invent that they're seeing a lot more visibility into use cases at the scale. So the scale gives you an advantage on what instances might work. >> And makes the economics works. >> Makes the economics work, hence the timing, the shrinking time to market, not there, but also for the apps. Talk about the scale advantage you guys have. >> Absolutely. I mean, the scale advantage of AWS plays out in a number of ways for our customers. The first thing is being able to deliver highly optimized hardware. So we don't just look at the Graviton3 CPU, you were speaking about the core count and the frequency and Peter spoke about a lot of that in his keynote yesterday. But we look at how does the Graviton3 CPU work with the rest of the instance. What is the right balance between the CPU and memory? The CPU and the Hydro. What's the performance and the drive? We just launched the Nitro SSD, which is now we've actually building our own custom SSDs for Nitro getting better performance, being able to do updates, better security, making it more cloudy. We're just saying, we've been challenged with the SSD in the parts. The other place that scales really helping is in capacity. Being able to make sure that we can absorb things like the COVID spike, or the stuff you see in the financial industry with just enormous demand for compute. We can do that because of our scale. We are able to scale. And the final area is actually in quality because I have such an enormous fleet. I'm actually able to drive down AFR. So annual failure rates, are we well below what the mathematical theoretical tenant or possibility is? So if you look at what's put on that actual sticker on the box that says you should be able to get a full percent AFR. At scale and with focus, we're actually able to get that down to significantly below what the mathematical entitlement was actually be. >> Yeah, it's incredible. I've got a great, and this is the advantage, and that's why I believe anyone who's writing applications that has includes a database, data transfer, any kind of execution of code will use the stack. >> Why would they? Really, why? We've seen this, like you said before, whether it was PC, then the fastest Pentium or somebody. >> Why would you want your app to run slower? >> Unix box, right? ISVS want it to run as fast and as cheaply as possible. Now power plays into it as well. >> Yeah, well, we do have, I agree with what you're saying. We do have a number of customers that are still looking to run on x86, but obviously customers that want windows. Windows isn't available for Arm and so that's a challenge. They'll continue to do that. And you know the way we do look at it is most law kind of died out on us in 2002, 2003. And what I'm hoping is, not necessarily bringing wars a little back, but then we say, let's not accept the 10%, 15% improvement year-over-year. There's absolutely more we can all be doing. And so I'm excited to see where the x86 world's going and they doing a lot of great stuff. Intel Ice Lakes looking amazing. Milan is really great to have an AWS as well. >> Well, I'm thinking it's fair point 'cause we certainly look what Pat's doing it at Intel and he's remaking the company. I've said he's going to follow on the Arm playbook in my mind a little bit, and which is the right thing to do. So competition is a good thing. >> David: Absolutely. >> We're excited for you and a great to see Graviton and you guys have this kind of inflection point. We've been tracking for a while, but now the world's starting to see it. So congratulations to your team. >> David: Thank you. >> Just a couple of things. You guys have some news on instances. Talk about the deprecation issue and how you guys are keeping instances alive real quick. >> Yeah, we're super customer obsessed at Amazon. And so that really drives us. And one of the worst things for us to do is to have to tell a customer that we no longer supporting a service. We recently actually just deprecated the ECG classic network. I'm not sure if you saw that and that's actually off the 10 years of continuing to support it. And the only reason we did it is we have a tiny percentage of customers still using that from back in 2012. But one of the challenges is obviously instance hardware eventually will ultimately time out and fail and have hardware issues as it gets older and older. And so we didn't want to be in a place, in EC2, where we would have to constantly go to customers and say that M1 small, that C3, whatever you were running, it's no longer supported, please move. That's just a text that customers shouldn't have to do. And if they still getting value out of an older instance, let them keep using it. So we actually just announced at re:Invent, in my keynote on Tuesday, the longevity support for EC2 instances, which means we will never come back to you again and ask you to please get off an instance, because we can actually emulate all those instances on our Nitro system. And so all of these instances are starting to migrate to Nitro. You're getting all the benefits of Nitro for now some of our older zen instances, but also you don't have to worry about that work. That's just not something you need to do to get off in all the instance. >> That's great. That's a great test service. Stay on as long as you want. When you're ready to move, move. Okay, final question for you. I know we've got time, I want to get this in. The global network, you guys are known for AWS cloud WAN serve. Gives you updates on what's going on with that. >> So Werner just announced that in his keynote and over the last two to three years or so, we've seen a lot of customers starting to use the AWS backbone, which is extensive. I mean, you've seen the slides in Werner's keynote. It really does span the world. I think it's probably one of the largest networks out there. Customers starting to use that for actually their branch office communication. So instead of going and provisioning the own international MPLS networks and that sort of thing, they say, let me onboard to AWS with VPN or direct connect, and I can actually run the AWS backbone around the world. Now doing that actually has some complexity. You got to think about transit gateways. You got to think about those inter-region peering. And AWS cloud when takes all of that complexity away, you essentially create a cloud WAN, connecting to it to VPN or direct connect, and you can even go and actually set up network segments. So essentially VLANs for different parts of the organization. So super excited to get out that out of there. >> So the ease of use is the key there. >> Massively easy to use. and we have 26 SD-WAN partners. We even partnering with folks like Verizon and Swisscom in Switzerland to telco to actually allow them to use it for their customers as well. >> We'll probably use your service someday when we have a global rollout date. >> Let's do that, CUBE Global. And then the other was the M1 EC2 instance, which got a lot of applause. >> David: Absolutely. >> M1, I think it was based on A15. >> Yeah, that's for Mac. We've got to be careful 'cause M1 is our first instance as well. >> Yeah right, it's a little confusion there. >> So it's a Mac. The EC2 Mac is with M1 silicon from Apple, which super excited to put out there. >> Awesome. >> David Brown, great to see you in person. Congratulations to you and the team and all the work you guys have done over the years. And now that people starting to realize the cloud platform, the compute just gets better and better. It's a key part of the system. >> Thanks John, it's great to be here. >> Thanks for sharing. >> The SiliconANGLE is here. We're talking about custom silicon here on AWS. I'm John Furrier with Dave Vellante. You're watching theCUBE. The global leader in tech coverage. We'll be right back with more covers from re:Invent after this break. (bright music)

(upbeat music) >> Welcome back to theCUBE's continuous coverage of AWS storage day. My name is Dave Vellante and we're here from Seattle. And we're going to look at the really hard workloads, those business and mission critical workloads, the most sensitive data. They're harder to move to the cloud. They're hardened. They have a lot of technical debt. And the blocker in some cases has been storage. Ashish Palekar is here. He's the general manager of EBS snapshots, and he's joined by Cami Tavares who's a senior manager of product management for Amazon EBS. Folks, good to see you. >> Ashish: Good to see you again Dave. >> Dave: Okay, nice to see you again Ashish So first of all, let's start with EBS. People might not be familiar. Everybody knows about S3 is famous, but how are customers using EBS? What do we need to know? >> Yeah, it's super important to get the basics, right? Right, yeah. We have a pretty broad storage portfolio. You talked about S3 and S3 glacier, which are an object and object and archival storage. We have EFS and FSX that cover the file site, and then you have a whole host of data transfer services. Now, when we think about block, we think of a really four things. We think about EBS, which is the system storage for EC2 volumes. When we think about snapshots, which is backups for EBS volumes. Then we think about instant storage, which is really a storage that's directly attached to an instance and manages and then its life cycle is similar to that of an instance. Last but not the least, data services. So things like our elastic volumes capability of fast snapshot restore. So the answer to your question really is EBS is persistent storage for EC2 volumes. So if you've used EC2 instances, you'll likely use EBS volumes. They service boot volumes and they service data volumes, and really cover a wide gamut of workloads from relational databases, no SQL databases, file streaming, media and coding. It really covers the gamut of workloads. >> Dave: So when I heard SAN in the cloud, I laughed out loud. I said, oh, because I could think about a box, a bunch of switches and this complicated network, and then you're turning it into an API. I was like, okay. So you've made some announcements that support SAN in the cloud. What, what can you tell us about? >> Ashish: Yeah, So SANs and for customers and storage, those are storage area networks, really our external arrays that customers buy and connect their performance critical and mission critical workloads. With block storage and with EBS, we got a bunch of customers that came to us and said, I'm thinking about moving those kinds of workloads to the cloud. What do you have? And really what they're looking for and what they were looking for is performance availability and durability characteristics that they would get from their traditional SANs on premises. And so that's what the team embarked on and what we launched at reinvent and then at GEd in July is IO2 block express. And what IO2 block express does is it's a complete ground app, really the invention of our storage product offering and gives customers the same availability, durability, and performance characteristics that can, we'll go into little later about that they're used to in their on premises. The other thing that we realized is that it's not just enough to have a volume. You need an instance that can drive that kind of throughput and IOPS. And so coupled with our trends in EC2 we launched our R5b that now triples the amount of IOPS and throughput that you can get from a single instance to EBS storage. So when you couple the sub millisecond latency, the capacity and the performance that you get from IO2 block express with R5b, what we hear from customers is that gives them enough of the performance availability characteristics and durability characteristics to move their workloads from on premises, into the cloud, for the mission critical and business critical apps. >> Dave: Thank you for that. So Cami when I, if I think about how the prevailing way in which storage works, I drop off a box at the loading dock and then I really don't know what happens. There may be a service organization that's maybe more intimate with the customer, but I don't really see the innovations and the use cases that are applied clouds, different. You know, you live it every day. So you guys always talk about customer inspired innovation. So what are you seeing in terms of how people are using this capability and what innovations they're driving? >> Cami: Yeah, so I think when we look at the EBS portfolio and this, the evolution over the years, you can really see that it was driven by customer need and we have different volume types and they have very specific performance characteristics, and they're built to meet these unique needs of customer workloads. So I'll tell you a little bit about some of our specific volume types to kind of illustrate this evolution over the years. So starting with our general purpose volumes, we have many customers that are using these volumes today. They really are looking for high performance at a low cost, and you have all kinds of transactional workloads and low-latency interactive applications and boot volumes, as Ashish mentioned. And they tell us, the customer is using these general purpose volumes, they tell us that they really like this balanced cost and performance. And customers also told us, listen, I have these more demanding applications that need higher performance. I need more IOPS, more throughput. And so looking at that customer need, we were really talking about these IO intensive applications like SAP HANA and Oracle and databases that require just higher durability. And so we looked at that customer feedback and we launched our provisioned IOPS IO2 volume. And with that volume, you get five nines of durability and four times the IOPS that you would get with general purpose volumes. So it's a really compelling offering. Again, customers came to us and said, this is great. I need more performance, I need more IOPS, more throughput, more storage than I can get with a single IO2 volume. And so these were talking about, you mentioned mission critical applications, SAP HANA, Oracle, and what we saw customers doing often is they were striping together multiple IO2 volumes to get the maximum performance, but very quickly with the most demanding applications, it got to a point where we have more IO2 volumes that you want to manage. And so we took that feedback to heart and we completely reinvented the underlying EBS hardware and the software and networking stacks. And we'll launched block express. With block express, you can get four times the IOPS throughput and storage that you would get with a single io2 volume. So it's a really compelling offering for customers. >> Dave: If I had to go back and ask you, what was the catalyst, what was the sort of business climate that really drove the decision here. Was that people were just sort of fed up with you know, I'll use the phrase, the undifferentiated, heavy lifting around SAN, what was it, was it COVID driven? What was the climate? >> You know, it's important to recognize when we are talking about business climate today, every business is a data business and block storage is really a foundational part of that. And so with SAN in the cloud specifically, we have seen enterprises for several years, buying these traditional hardware arrays for on premises SANs. And it's a very expensive investment. Just this year alone, they're spending over $22 billion on SANs. And with this old model on premises SANs, you would probably spend a lot of time doing this upfront capacity planning, trying to figure out how much storage you might need. And in the end, you'd probably end up overbuying for peak demand because you really don't want to get stuck, not having what you need to scale your business. And so now with block express, you don't have to do that anymore. You pay for what you need today, and then you can increase your storage as your business needs change. So that's cost and cost is a very important factor. But really when we're talking to customers and enterprises that are looking for SAN in the cloud, the number one reason that they want to move to the cloud with their SANs and these mission, critical workloads is agility and speed. And it's really transformational for businesses to be able to change the customer experience for their customers and innovate at a much faster pace. And so with the block express product, you get to do that much faster. You can go from an idea to an implementation orders of magnitude faster. Whereas before if you had these workloads on premises, it would take you several weeks just to get the hardware. And then you have to build all this surrounding infrastructure to get it up and running. Now, you don't have to do that anymore. You get your storage in minutes, and if you change your mind, if your business needs change, if your workloads change, you can modify your EBS volume types without interrupting your workload. >> Dave: Thank you for that. So Cami kind of addressed some of this, but I know store admins say, don't touch my SAN, I'm not moving it. This is a big decision for a lot of people. So kind of a two-part question, you know, why now, what do people need to know? And give us the north star close it out with, with where you see the future. >> Ashish: Yeah, so let's, I'll kick things off and then Cami, do jump in. So first of the volume is one part of the story, right? And with IO2 block express, I think we've given customers an extremely compelling offering to go build their mission critical and business critical applications on. We talked about the instance type R5b in terms of giving that instance level performance, but all this is on the foundation of AWS in terms of availability zones and regions. So you think about the constructs and we talk them in terms of building blocks, but our building blocks are really availability zones and regions. And that gives you that core availability infrastructure that you need to build your mission critical and business critical applications. You then take layer on top of that our regional footprint, right. And now you can spin up those workloads globally, if you need to. And then last but not the least, once you're in AWS, you have access to other services. Be it AI, be it ML, be it our relational database services that you can start to think about undifferentiated, heavy lifting. So really you get the smorgasbord really from the availability footprint to global footprint and all the way up to sort of our service stack that you get access to. >> Dave: So that's really thinking out of the box. We're out of time. Cami we'll give you the last word. >> Cami: I just want to say, if you want to learn more about EBS, there's a deep dive session with our principal engineer, Marc Olson later today. So definitely join that. >> Dave: Folks, thanks so much for coming to theCUBE. (in chorus )Thank you. >> Thank you for watching. Keep it right there for more great content from AWS storage day from Seattle.

>>Welcome back to HPD discovered 2021. The virtual edition. My name is Dave Volonte and you're watching the cubes continuous coverage of H. P. S. Big customer event. Patrick Moorehead is here of moor insights and strategy is the number one analyst in the research analyst. Business. Patrick. Always a pleasure. Great to see you, >>David. Great to see you too. And I know you're you're up there fighting for that number one spot to. It's great to see you and it's great to see you in the meetings that were in. But it's even more fun to be here on the cube. I love to be on the cube and every once in a while you'll even call me a friend of the cube, >>unquestionably my friend and so and I can't wait second half. I mean you're traveling right now. We're headed to Barcelona to mobile World Congress later on this month. So so we're gonna we're gonna see each other face to face this year. 100%. So looking forward to that. So you know, let's get into it. Um you know, before we get into H. P. E. Let's talk a little bit about what you're seeing in the market. We've got, you know, we we finally, it feels like the on prem guys are finally getting their cloud act together. Um it's maybe taken a while, but we're seeing as a service models emerge. I think it's resonating with customers. The clearly not everything is moving to the cloud. There's this hybrid model emerging. Multi cloud is real despite what, you know, >>some some >>cloud players want to say. And then there's this edges like jump ball, what are you seeing in the marketplace? >>Yeah. Davis, as exciting as ever in. Just to put in perspective, I mean the public cloud has been around for about 10 years and still only 20% around 20% of the data in 20% of the applications are there now will be a very important ones and I'm certainly not a public cloud denier, I never have been, but there are some missing pieces that need to come together. And you know, even five years ago we were debating dave the hybrid cloud. And I feel like when amazon brought out outposts, the conversation was over right now, what you have is cloud native folks building out hybrid and on prem capabilities, you have a classic on, on prem folks building out hybrid and as a service capabilities. And I really think it boils down 22 things. I mean it's, it's wanting to have more flexibility and you know, I hate to use it because it sounds like a marketing word, but agility, the ability to spin up things and spin down things in a very, a quick way. And uh you know what they've learned, The veterans also know, hey, let's do this in a way that doesn't lock us in too much into a certain vendor. And I've been around for a long time. David and I'm a realist too. Well, you have to lock yourself into something. Uh it just depends on what do you want to lock yourself into, but super exciting and what H. P. E. You know, when they further acts in the sea with Green Lake, I think it was four years ago, uh I think really started to stir the pot. >>You know, you mentioned the term cloud denial, but you know, and I feel like the narrative from, I like to determine as I think you should use the term veteran. You know, it's very, they're ours is the only industry patrick where legacy is a pejorative, but so, but the point I want to make is I feel like there's been a lot of sort of fear from the veteran players, but, but I look at it differently, I wonder what your take is. I, I think, I think I calculated that the Capex spending by the big four public clouds including Alibaba last year was $100 billion. That's like a gift to the world. Here we're gonna spend $100 billion like the internet. Here you go build. And so I, and I feel like companies like HP are finally saying, yeah, we're gonna build, we're gonna build a layer and we're gonna hide the complexity and we're gonna add value on top. What do you think about that? >>Yeah. So I think it's now, I wish, I wish the on prem folks like HP, you would have done it 10 years ago, but I don't think anybody expected the cloud to be as big as it's become over the last 10 years. I think we saw companies like salesforce with sas taking off, but I think it is the right direction because there are advantages to having workloads on prem and if you add an as a service capability on top of the top of that, and let's say even do a Coehlo or a managed service, it's pretty close to being similar to the public cloud with the exception, that you can't necessarily swipe a credit card for a bespoke workload if you're a developer and it is a little harder to scale out. But that is the next step in the equation day, which is having, having these folks make capital expenditures, make them in a Polo facility and then put a layer to swipe a credit card and you literally have the public cloud. >>Yeah. So that's, that's a great point. And that's where it's headed, isn't it? Um, so let's, let's talk about the horses on the track. Hp as you mentioned, I didn't realize it was four years ago. I thought it was, wow, That's amazing. So everybody's followed suit. You see, Dallas announced, Cisco has announced, uh, Lenovo was announced, I think IBM as well. So we, so everybody's sort of following suit there. The reality is, is it's taken some time to get this stuff standardized. What are you seeing from, from HP? They've made some additional announcements, discover what's your take on all this. >>Yeah. So HPD was definitely the rabbit here and they were first in the market. It was good to see. First off some of their, Um, announcements on, on how it's going and they talked about $428 billion 1200 customers over 900 partners and 95% retention. And I think that's important. Anybody who's in the lead and remember what aws I used to do with the slide with the amount of customers would just get bigger and bigger and bigger and that's a good way to show momentum. I like the retention part two which is 95%. And I think that that says a lot uh probably the more important announcements that they made is they talked about the G. A. Of some of their solutions on Green Lake and whether it is A. S. A. P. Hana. Ml apps HPC with Francis, VD. I was Citrus and video but they also brought more of what I would call a vertical layer and I'm sure you've seen the vertical ization of all of these cloud and as a service workloads. But what they're doing with Epic, with EMR and looseness, with financial payments and Splunk and intel with data and risk analysis and finally, a full stack for telco five G. One of the biggest secrets and I covered this about five years ago is HPV actually has a full stack that Western european carriers use and they're now extending that to five G. And um, so more horizontal, uh, and, and more vertical. That was the one of the big swipes, uh, that I saw that there was a second though, but maybe we can talk about these. >>Yeah. Okay. Okay. So, so the other piece of that of course is standardization right there there because there was a, there was a, there was a lot of customization leading up to this and everybody sort of, everybody always had some kind of financial game they can play and say, hey, there's an adversary as a service model, but this is definitely more of a standardized scalable move that H P E. Is making with what they call Lighthouse. Right? >>Yeah, that's exactly right. And I've talked to some Green Lake customers and they obviously gave it kudos or they wouldn't have HP wouldn't have served them up and they wouldn't have been buying it. But they did say, um, it took, it took a while, took some paperwork to get it going. It's not 100% of push button, but that's partially because hp allows you to customize the hardware. You want a one off network adapter. Hp says yes, right. You want to integrate a different type of storage? They said yes. But with Green Lake Lighthouse, it's more of a, what you see is what you get, which by the way, is very much like the public cloud or you go to a public cloud product sheet or order sheet. You're picking from a list and you really don't know everything that's underneath the covers, aside from, let's say, the speed of the network, the type of the storage and the amount of the storage you get. You do get to pick between, let's say, an intel processor, Graviton two or an M. D processor. You get to pick your own GPU. But that's pretty much it. And HP Lighthouse, sorry, Green Lake Lighthouse uh is bringing, I think a simplification to Green Lake that it needs to truly scale beyond, let's say the White House customers that HP Yeah, >>Well done. So, you know, and I hear your point about we're 10 years in plus. And to me this is like a mandate. I mean, this is okay, good, good job guys about time. But if I had a, you know, sort of look at the big player, it's like we have an oligopoly here in this, in this business. It's HP, Cisco, you got Dell Lenovo, you've got, you know, IBM, they're all doing this and they all have a different little difference, you know, waste of skin of catch. And your point about simplicity, it seems like HP HP is all in antony's like, okay, here's what we're going to announce that, you know, a while ago. So, and they seem to have done a good job with Wall Street and they got a simple model, you know, Dell is obviously bigger portfolio, much more complicated. IBM is even more complicated than that. I don't know so much about Lenovo and in Cisco of course, has acquired a ton of SAAS companies and sort of they've got a lot of bespoke products that they're trying to put together. So they've got, but they do have SAS models. So each of them is coming at it from a different perspective. How do you think? And so and the other point we got lighthouse, which is sort of Phase one, get product market fit. Phase two now is scale, codify standardized and then phase three is the moat build your unique advantage that protects your business. What do you see as HP ES sort of unique value proposition and moat that they can build longer term. >>That's a great, great question. And let me rattle off kind of what I'm seeing that some of these players here, So Cisco, ironically has sells the most software of any of those players that you mentioned, uh with the exception of IBM um and yeah, C I >>CSDB two. Yeah, >>yeah, they're the they're the number two security player, uh Microsoft, number one, So and I think the evaluation on the street uh indicate that shows that I feel like Dell tech is a very broad play because not only do they have servers, storage, networking insecurity, but they also have Pcs and devices. So it's a it's a scale and end play with a focus on VM ware solutions, not exclusively of course. Uh And um then you've got Lenovo who is just getting into the as a service game and are gosh, they're doing great in hyper scale, they've got scale there vertically integrated. I don't know if if too many people talk about that, but Lenovo does a lot of their own manufacturing and they actually manufacture Netapp storage solutions as well. So yeah, each of these folks brings a different game to the table. I think with h P e, what you're bringing the table is nimble. When HP and HP split, the number one thing that I said was that ah, h P E is going to have to be so much faster than it offsets the scale that Dell technology has and the HBs credit, although there, I don't think we're getting credit for this in the stock market yet. Um and I know you and I are both industry folks, not financial folks, but I think their biggest thing is speed and the ability to move faster. And that is what I've seen as it relates to the moat, which is a unique uh competitive advantage. Quite frankly, I'm still looking for that day uh in in in what that is. And I think in this industry it's nearly impossible. And I would posit that that any, even the cloud folks, if you say, is there something that AWS can do that as your can't if it put it put its mind to it or G C P. I don't think so. I think it's more of a kind of land and expand and I think for H P E. When it comes to high performance computing and I'm not just talking about government installations, I'm talking about product development, drug development. I think that is a landing place where H P. E already does pretty well can come in and expand its footprint. >>You know, that's really interesting um, observations. So, and I would agree with you. It's kind of like, this is a copycat industry. It's like the west coast offense like the NFL, >>so, >>so the moat comes from, you know, brand execution and your other point about when HP and HP split, that was a game changer because all of a sudden you saw companies like them, you always had a long term relationship with H P E, but or HP, but then they came out of the woodworks and started to explode. And so it really opened up opportunities. So it really is a execution, isn't it? But go ahead please. >>Dave if I had to pick something that I think HP HPV needs to always be ahead in as a service and listen you and I both know announcements don't mean delivery, but there is correlation between if you start four years ahead of somebody that other company is going to have to put just, I mean they're going to have to turn that ship and many of its competitors really big ships to be able to get there. So I think what Antonio needs to do is run like hell, right? Because it, it I think it is in the lead and as a service holistically doesn't mean they're going to be there forever, but they have to stay ahead. They have to add more horizontal solutions. They have to add more vertical solutions. And I believe that at some point it does need to invest in some Capex at somebody like Anna Quinn X play credit card swiper on top of that. And Dave, you have the public, you have the public cloud, you don't have all the availability zones, but you have a public cloud. >>Yeah, that's going to happen. I think you're right on. So we see this notion of cloud expanding. It's no longer just remote set of services. Somewhere out in the cloud. It's like you said, outpost was the sort of signal. Okay, We're coming on prem. Clearly the on prem uh, guys are connecting to the cloud. Multi cloud exists, we know this and then there's the edge but but but that brings me to that sort of vision and everybody's laying out of this this this seamless integration hiding the complexity log into my cloud and then life will be good. But the edge is different. Right? It's not just, you know, retail store or a race track. I mean there's the far edge, there's the Tesla car, there's gonna be compute everywhere and that sort of ties into the data. The data flows, you know the real time influencing at the edge ai new semiconductor models. You you came out of the semiconductor industry, you know it inside and out arm is exploding, dominating in the edge with apple and amazon Alexa and things like that. That's really where the action is. So this is a really interesting cocktail and soup that we have going on. How do >>you say? Well, you know, Dave if the data most data, I think one thing most everybody agrees on is that most of the data will be created on the edge, whether that's a moving edge a car, a smartphone or what I call an edge data center without tile flooring. Like that server that's bolted to the wall of Mcdonald's. When you drive through, you can see it versus the walmart. Every walmart has a raised tile floor. It's the edge to economically and performance wise, it doesn't make any sense to send all that data to the mother ships. Okay. And whether that's unproven data center or the giant public cloud, more efficient way is to do the compute at the closest way possible. But what it does, it does bring up challenges. The first challenge is security. If I wanted to, I could walk in and I could take that server off the Mcdonald's or the Shell gas station wall. So I can't do that in a big data center. Okay, so security, physical security is a challenge. The second is you don't have the people to go in there and fix stuff that are qualified. If you have a networking problem that goes wrong in Mcdonald's, there's nobody there that can help uh they can they can help you fix that. So this notion of autonomy and management and not keeping hyper critical data sitting out there and it becomes it becomes a security issue becomes a management issue. Let me talk about the benefits though. The benefits are lower latency. You want you want answers more quickly when that car is driving down the road And it has a 5GV 2 x communication cameras can't see around corners. But that car communicating ahead, that ran into the stop sign can, through Vita X talked to the car behind it and say, hey, something is going on there, you can't go to, you can't go to the big data center in the sky, let's make that happen, that is to be in near real time and that computer has to happen on the edge. So I think this is a tremendous opportunity and ironically the classic on prem guys, they own this, they own this space aside from smartphones of course, but if you look at compute on a light pole, companies like Intel have built complete architecture is to do that, putting compute into five G base stations, heck, I just, there was an announcement this week of google cloud and its gaming solution putting compute in a carrier edge to give lower latency to deliver a better experience. >>Yeah, so there, of course there is no one edge, it's highly fragmented, but I'm interested in your thoughts on kinda whose stack actually can play at the edge. And I've been sort of poking uh H P E about this. And the one thing that comes back consistently is Aruba, we we could take a room but not only to the, to the near edge, but to the far edge. And and that, do you see that as a competitive advantage? >>Oh gosh, yes. I mean, I would say the best acquisition That hp has made in 10 years has been aruba, it's fantastic and they also managed it in the right way. I mean it was part of HB but it was, it was managed a lot more loosely then, you know, a company that might get sucked into the board and I think that paid off tremendously. They're giving Cisco on the edge a absolute run for their money, their first with new technologies, but it's about the solution. What I love about what a ruble looks at is it's looking at entertainment solutions inside of a stadium, a information solution inside of an airport as opposed to just pushing the technology forward. And then when you integrate compute with with with Aruba, I think that's where the real magic happens. Most of the data on a permanent basis is actually video data. And a lot of it's for security, uh for surveillance. And quite frankly, people taking videos off, they're off their smartphones and downloaded video. I I just interviewed the chief network officer of T mobile and their number one bit of data is video, video uploaded, video download. But that's where the magic happens when you put that connectivity and the compute together and you can manage it in a, in an orderly and secure fashion. >>Well, I have you we have a ton of time here, but I I don't pick your brain about intel the future of intel. I know you've been following it quite closely, you always have Intel's fighting a forefront war, you got there battling a. M. D. There, battling your arm slash and video. They're they're taking on TSMC now and in foundry and, and I'll add china for the looming threat there. So what's your prognosis for for intel? >>Yeah, I liked bob the previous Ceo and I think he was doing a lot of of the right things, but I really think that customers and investors and even their ecosystem wanted somebody leading the company with a high degree of technical aptitude and Pat coming, I mean, Pat had a great job at VM or, I mean he had a great run there and I think it is a very positive move. I've never seen the energy at Intel. Probably in the last 10 years that I've seen today. I actually got a chance to talk with Pat. I visited Pat uhh last month and and talk to him about pretty much everything and where he wanted to take the company the way you looked at technology, what was important, what's not important. But I think first off in the world of semiconductors, there are no quick fixes. Okay. Intel has a another two years Before we see what the results are. And I think 2023 for them is gonna be a huge year. But even with all this competition though, Dave they still have close to 85% market share in servers and revenue share for client computing around 90%. Okay. So and they built out there networking business, they build out a storage business um with obtain they have the leading Aid as provider with Mobileye. And and listen I was I was one of Intel's biggest, I was into one of Intel's biggest, I was Intel's biggest customer when I was a compact. I was their biggest competitor at A. M. B. So um I'm not obviously not overly pushing or there's just got to wait and see. They're doing the right things. They have the right strategy. They need to execute. One of the most important things That Intel did is extend their alliance with TSMC. So in 2023 we're going to see Intel compute units these tiles they integrate into the larger chips called S. O. C. S. B. Manufactured by TSMC. Not exclusively, but we could see that. So literally we could have AMG three nanometer on TSMC CPU blocks, competing with intel chips with TSMC three nanometer CPU blocks and it's on with regard to video. I mean in video is one of these companies that just keeps going charging, charging hard and I'm actually meeting with Jensen wang this week and Arm Ceo Simon Segers to talk about this opportunity and that's a company that keeps on moving interestingly enough in video. If the Arm deal does go through will be the largest chip license, see CPU licensee and have the largest CPU footprint on on the planet. So here we have A and D. Who's CPU and Gpu and buying an F. P. G. A company called Xilinx, you have Intel, Cpus, Gpus machine learning accelerators and F. P. G. S and then you've got arms slashing video bit with everything as well. We have three massive ecosystems. They're gonna be colliding here and I think it's gonna be great for competition date. Competition is great. You know, when there's not competition in Cpus and Gpus, we know what happens, right. Uh, the B just does not go on and we start to stagnate. And I did, I do feel like the industry on CPU started to stagnate when intel had no competition. So bring it on. This is gonna be great for for enterprises then customers to, and then, oh, by the way, the custom Chip providers, WS has created no less than 15 custom semiconductors started with networking uh, and, and nitro and building out an edge that surrounded the general compute and then it moved to Inferential to for inference trainee um, is about to come out for training Graviton and gravitas to for general purpose CPU and then you've got Apple. So innovation is huge and you know, I love to always make fun of the software is eating the world. I always say yeah but has to run on something. And so I think the combination of semiconductors, software and cloud is just really a magical combination. >>Real quick handicap the video arm acquisition. What what are the odds that that they will be successful? They say it's on track. You've got to 2 to 13 to 1 10 to 1. >>I say 75%. Yes 25%. No China is always the has been the odd odd man out for the last three years. They scuttled the qualcomm NXP deal. You just don't know what china is going to do. I think the Eu with some conditions is gonna let this fly. I think the U. S. Is absolutely going to let this fly. And even though the I. P. Will still stay over in the UK, I think the U. S. Wants to see, wants to see this happen. Japan and Korea. I think we'll allow this china is the odd man out. >>In a word, the future of H. P. E. Is blank >>as a service >>patrick Moorehead. Always a pleasure my friend. Great to see you. Thanks so much for coming back in the cube. >>Yeah, Thanks for having me on. I appreciate that. >>Everybody stay tuned for more great coverage from HP discover 21 this is day Volonte for the cube. The leader and enterprise tech coverage. We'll be right back. >>Mm.

>>Welcome back to HPD discovered 2021. The virtual edition. My name is Dave Volonte and you're watching the cubes continuous coverage of H. P. S. Big customer event. Patrick Moorehead is here of moor insights and strategy is the number one analyst in the research analyst. Business. Patrick. Always a pleasure. Great to see you, >>David. Great to see you too. And I know you're you're up there fighting for that number one spot to. It's great to see you and it's great to see you in the meetings that were in. But it's even more fun to be here on the cube. I love to be on the cube and every once in a while you'll even call me a friend of the cube, >>unquestionably my friend and so and I can't wait second half. I mean you're traveling right now. We're headed to Barcelona to mobile World Congress later on this month. So so we're gonna we're gonna see each other face to face this year. 100%. So looking forward to that. So, you know, let's get into it. Um you know, before we get into H. P. E. Let's talk a little bit about what you're seeing in the market. We've got, you know, we we we finally, it feels like the on prem guys are finally getting their cloud act together. Um, it's maybe taken a while, but we're seeing as a service models emerge. I think it's resonating with customers. The clearly not everything is moving to the cloud. There's this hybrid model emerging. Multi cloud is real despite what, you know, >>some some >>cloud players want to say. And then there's this edges like jump ball, what are you seeing in the marketplace? >>Yeah. Davis, as exciting as ever in. Just to put in perspective, I mean, the public cloud has been around for about 10 years and still only 20%. Around 20% of the data in 20% of the applications are there now, albeit very important ones. And I'm certainly not a public cloud denier, I never have been, but there are some missing pieces that need to come together. And you know, even five years ago we were debating dave the hybrid cloud and I feel like when Amazon brought out outposts, the conversation was over right now, what you have is cloud native folks building out hybrid and on prem capabilities, you have the classic on prem folks building out hybrid and as a service capabilities. And I really think it boils down 22 things. I mean it's wanting to have more flexibility and you know, I hate to use it because it sounds like a marketing word, but agility, the ability to spin up things and spin down things in a very quick way. And uh, you know what they've learned. The veterans also know, hey, let's do this in a way that doesn't lock us in too much into a certain vendor. And I've been around for a long time. David and I'm a realist too. Well, you have to lock yourself into something. It just depends on what do you want to lock yourself into, but super exciting. And what H. P. E. When they threw the acts in the sea with Green Lake, I think it was four years ago, I think really started to stir the pot. >>You know, you mentioned the term cloud denial, but you know, and I feel like the narrative from, I like to determine is I think you should use the term veteran. You know, it's very, they're ours is the only industry patrick where legacy is a pejorative, but but but so but the point I want to make is I feel like there's been a lot of sort of fear from the veteran players, but I look at it differently. I wonder what you're taking. I think, I think, I think I calculated that the Capex spending by the big four public clouds including Alibaba last year was $100 billion. That's like a gift to the world. Here, we're going to spend $100 billion like the internet here you go build. And and so I, and I feel like companies like HP are finally saying, yeah, we're gonna build, we're gonna build a layer and we're gonna hide the complexity and we're gonna add value on top. What do you think about that? >>Yeah. So I think it's now, I wish, I wish the on prem folks like HP, you would have done it 10 years ago, but I don't think anybody expected the cloud to be as big as it's become over the last 10 years. I think we saw companies like salesforce with sas taking off, but I think it is the right direction because there are advantages to having workloads on prem and if you add an as a service capability on top of the top of that, and let's say even do a Coehlo or a managed service, it's pretty close to being similar to the public cloud with the exception, that you can't necessarily swipe a credit card for a bespoke workload if you're a developer and it is a little harder to scale out. But that is the next step in the equation day, which is having, having these folks make capital expenditures, make them in a polo facility and then put a layer to swipe a credit card and you literally have the public cloud. >>Yeah. So that's, that's a great point and that's where it's headed, isn't it? Um, so let's, let's talk about the horses on the track. Hp. As you mentioned, I didn't realize it was four years ago. I thought it was, wow, That's amazing. So everybody's followed suit. You see, Dallas announced, Cisco has announced, uh, Lenovo was announced, I think IBM as well. So we, so everybody started following suit there. The reality is, is it's taken some time to get this stuff standardized. What are you seeing from, from HP? They've made some additional announcements, discover what's your take on all this. >>Yeah. So HPD was definitely the rabbit here and they were first in the market. It was good to see, first off some of their, Um, announcements on, on how it's going. And they talked about 4, $28 billion 1200 customers over 900 partners and 95% retention. And I think that's important anybody who's in the lead and remember what Aws used to do with the slide with the amount of customers would just get bigger and bigger and bigger and that's a good way to show momentum. I like the retention part two which is 95%. And I think that that says a lot uh probably the more important announcements that they made is they talked about the G. A. Of some of their solutions on Green Lake and whether it was S. A. P. Hana Ml apps HPC with Francis V. I was Citrus in video but they also brought more of what I would call a vertical layer and I'm sure you've seen the vertical ization of all of these cloud and as a service workloads. But what they're doing with Epic with EMR and looseness, with financial payments and Splunk and intel with data and risk analysis and finally, a full stack for telco five G. One of the biggest secrets and I covered this about five years ago is HPV actually has a full stack that western european carriers use and they're now extending that to five G. And um, so more horizontal uh and and more vertical. That was the one of the big swipes uh that I saw that there was a second though, but maybe we can talk about these. >>Yeah. Okay, Okay. So, so the other piece of that of course is standardization right there there because there was a, there was, there was a lot of customization leading up to this and everybody sort of, everybody always had some kind of financial game they can play and say, hey, there's an adversary as a service model, but this is definitely more of a standardized scalable move that H P E. Is making with what they call Lighthouse, Right? >>Yeah, that's exactly right. And I've talked to some Green Lake customers and they obviously gave it kudos or they wouldn't have HP wouldn't have served them up and they wouldn't have been buying it. But they did say, um, it took, it took a while, took some paperwork to get it going. It's not 100% of push button, but that's partially because hp allows you to customize the hardware. You want a one off network adapter. Hp says yes, right. You want to integrate a different type of storage? They said yes. But with Green Lake Lighthouse, it's more of a, what you see is what you get, which by the way is very much like the public cloud or you go to a public cloud product sheet or order sheet. You're picking from a list and you really don't know everything that's underneath the covers, aside from, let's say the speed of the network, the type of the storage and the amount of the storage you get. You do get to pick between, let's say, an intel processor, Graviton two or an M. D processor. You get to pick your own GPU. But that's pretty much it. And HP Lighthouse, sorry, Green Lake Lighthouse uh, is bringing, I think a simplification to Green Lake that it needs to truly scale beyond, let's say, the white house customers at HP. Yeah, >>Well done. So, you know, and I hear your point about 10 years in, you know, plus and to me this is like a mandate. I mean, this is okay. Good, good job guys about time. But if I had a, you know, sort of look at the big players, like, can we have an oligopoly here in this, in this business? It's HP, Cisco, you got Dell Lenovo, you've got, you know, IBM, they're all doing this and they all have a different little difference, you know, waste of skin of catch. And your point about simplicity, it seems like HP HP is all in Antonio's like, okay, here's what we're going to announce that, you know, while ago, so, and they seem to have done a good job with Wall Street and they get a simple model, you know, Dell's obviously bigger portfolio, much more complicated. IBM is even more complicated than that. I don't know so much about Lenovo and in Cisco of course, has acquired a ton of SAAS companies and sort of they've got a lot of bespoke products that they're trying to put together, so they've got, but they do have SAS models. So each of them is coming at it from a different perspective. How do you think? And so and the other point we got lighthouse, which is sort of Phase one, get product market fit. Phase two now is scale codify standardized and then phase three is the moat build your unique advantage that protects your business. What do you see as HP? Es sort of unique value proposition and moat that they can build longer term. >>That's a great, great question. And let me rattle off kind of what I'm seeing that some of these these players here. So Cisco, ironically, has sells the most software of any of those players that you mentioned, uh with the exception of IBM. Um, and yeah, C >>ICSDB two. Yeah, >>yeah, they're the they're the number two security player, uh, Microsoft, number one. So and I think the evaluation on the street uh indicate that shows that I feel like uh Deltek is a is a very broad play because not only do they have servers, storage, networking and security, but they also have Pcs and devices, so it's a it's a scale and end play with a focus on VM ware solutions, not exclusively, of course. Uh And um then you've got Lenovo who is just getting into the as a service game and are gosh, they're doing great in hyper scale, they've got scale there vertically integrated. I don't know if if too many people talk about that, but Lenovo does a lot of their own manufacturing and they actually manufacture Netapp storage solutions as well. So yeah, each of these folks brings a different game to the table, I think with h P E, what your bring to the table is nimble. When HP and HP split, the number one thing that I said was that uh huh H P E is going to have to be so much faster than it offsets the scale that Dell technology has and the HBs credit, although there, I don't think we're getting credit for this in the stock market yet. Um, and I know you and I are both industry folks, not financial folks, but I think their biggest thing is speed and the ability to move faster and that is what I've seen as it relates to the moat, which is a unique uh, competitive advantage. Quite frankly, I'm still looking for that day in, in, in what that is and I think in this industry it's nearly impossible and I would posit that that any, even the cloud folks, if you say, is there something that AWS can do that Azure can't, if it put it put its mind to it or G C P. I don't think so. I think it's more of a kind of land and expand and I think for H P E, when it comes to high performance computing and I'm not just talking about government installations, I'm talking about product development, drug development, I think that is a landing place where H P E already does pretty well can come in and expand its footprint, >>you know, that's really interesting um, observations. So, and I would agree with you, it's kind of like, this is a copycat industry, it's like the west coast offense, like the NFL >>and >>so, so the moat comes from, you know, brand execution and your other point about when HP and HP split, that was a game changer, because all of a sudden you saw companies like them, you always had a long term relationship with H P E but or HP, but then they came out of the woodworks and started to explode. And so it really opened up opportunities. So it really >>is an execution, >>isn't it? But go ahead, please >>Dave if I had to pick something that I think HP HPV needs to always be ahead and as a service and listen, you know, I both know announcements don't mean delivery, but there is correlation between if you start four years ahead of somebody that other company is going to have to put just, I mean they're gonna have to turn that ship and many of its competitors really big ships to be able to get there. So I think what Antonio needs to do is run like hell, right, Because it, it, I think it is in the lead and as a service holistically doesn't mean they're going to be there forever, but they have to stay ahead. They have to add more horizontal solutions. They have to add more vertical solutions. And I believe that at some point it does need to invest in some Capex at somebody like ANna Quinn x play credit card swiper on top of that. And Dave, you have the public, you have the public cloud, you don't have all the availability zones, but you have a public cloud. >>Yeah, that's going to happen. I think you're right on. So we see this notion of cloud expanding. It's no longer just remote set of services. Somewhere out in the cloud. It's as you said, outpost was the sort of signal. Okay, We're coming on prem clearly the on prem, uh, guys are connecting to the cloud. Multi cloud exists, we know this and then there's the edge but but but that brings me to that sort of vision and everybody's laying out of this this this seamless integration hiding the complexity log into my cloud and then life will be good. But the edge is different. Right? It's not just, you know, retail store or a race track. I mean there's the far edge, there's the Tesla car, there's gonna be compute everywhere. And that sort of ties into the data. The data flows, you know the real time influencing at the edge ai new semiconductor models. You you came out of the semiconductor industry, you know it inside and out arm is exploding is dominating in the edge with with with apple and amazon Alexa and things like that. That's really where the action is. So this is a really interesting cocktail and soup that we have going on. How do you >>say? Well, you know, Dave if the data most data, I think one thing most everybody agrees on is that most of the data will be created on the edge. Whether that's a moving edge a car, a smartphone or what I call an edge data center without tile flooring. Like that server that's bolted to the wall of Mcdonald's. When you drive through, you can see it versus the walmart. Every walmart has a raised tile floor. It's the edge to economically and performance wise, it doesn't make any sense to send all that data to the mother ships. Okay. And whether that's unproven data center or the giant public cloud, more efficient way is to do the compute at the closest way possible. But what it does, it does bring up challenges. The first challenge is security. If I wanted to, I could walk in and I could take that server off the Mcdonald's or the Shell gas station wall. So I can't do that in a big data center. Okay, so security, Physical security is a challenge. The second is you don't have the people to go in there and fix stuff that are qualified. If you have a networking problem that goes wrong and Mcdonald's, there's nobody there that can help uh, they can they can help you fix that. So this notion of autonomy and management and not keeping hyper critical data sitting out there and it becomes it becomes a security issue becomes a management issue. Let me talk about the benefits though. The benefits are lower latency. You want you want answers more quickly when that car is driving down the road and it has a five G V two X communication cameras can't see around corners, but that car communicating ahead, that ran into the stop sign, can I through vi to X. Talk to the car behind it and say, hey, something is going on there, you can't go to, you can't go to the big data center in the sky to make that happen, that is to be in near real time and that computer has to happen on the edge. So I think this is a tremendous opportunity and ironically the classic on prem guys, they own this, they own this space aside from smartphones of course, but if you look at compute on a light pole, companies like Intel have built Complete architectures to do that, putting compute into 5G base stations. Heck, I just, there was an announcement this week of google cloud in its gaming solution putting compute in a carrier edge to give lower latency to deliver a better experience. >>Yeah, so there, of course there is no one edge, it's highly fragmented, but I'm interested in your thoughts on kind of who's stack actually can play at the edge. And I've been sort of poking uh H P E about this. And the one thing that comes back consistently is Aruba, we we can take a room but not only to the, to the near edge, but to the far edge. And and that, do you see that as a competitive advantage? >>Oh gosh, yes. I mean, I would say the best acquisition That hp has made in 10 years has been aruba it's fantastic. And they also managed it in the right way. I mean, it was part of HB but it was it was managed a lot more loosely then, you know, a company that might get sucked into the board. And I think that paid off tremendously. They're giving Cisco on the edge a absolute run for their money, their first with new technologies. But it's about the solution. What I love about what a ruble looks at is it's looking at entertainment solutions inside of a stadium, um a information solution inside of an airport as opposed to just pushing the technology forward. And then when you integrate compute with with with Aruba, I think that's where the real magic happens. Most of the data on a permanent basis is actually video data. And a lot of it's for security uh for surveillance. And quite frankly, people taking videos off, they're off their smartphones and downloading video. I I just interviewed the chief network officer of T mobile and their number one bit of data is video, video uploaded, video download. But that's where the magic happens when you put that connectivity and the compute together and you can manage it in a, in an orderly and secure fashion >>while I have you, we have a ton of time here, but I I don't pick your brain about intel, the future of intel. I know you've been following it quite closely, you always have Intel's fighting a forefront war. You got there, battling A. M. D. There, battling your arm slash and video. They're they're taking on TSMC now and in foundry and, and I'll add china for the looming threat there. So what's your prognosis for for intel? >>Yeah, I liked bob the previous Ceo and I think he was doing a lot of of the right things, but I really think that customers and investors and even their ecosystem wanted somebody leading the company with a high degree of technical aptitude and Pat coming, I mean, Pat had a great job at VM or, I mean, he had a great run there and I think it is a very positive move. I've never seen the energy At Intel probably in the last 10 years that I've seen today. I actually got a chance to talk with pat. I visited pat uhh last month and and talk to him about pretty much everything and where he wanted to take the company the way you looked at technology, what was important, what's not important. But I think first off in the world of semiconductors, there are no quick fixes. Okay. Intel has a another two years Before we see what the results are. And I think 2023 for them is gonna be a huge year. But even with all this competition though, Dave they still have close to 85% market share in servers and revenue share for client computing around 90%. Okay. So and they've built out there networking business, they build out a storage business um with with obtain they have the leading Aid as provider with Mobileye. And and listen I was I was one of Intel's biggest, I was into one of Intel's biggest, I was Intel's biggest customer when I was a compact. I was their biggest competitor at AMG. So um I'm not obviously not overly pushing or there's just got to wait and see. They're doing the right things. They have the right strategy. They need to execute. One of the most important things That Intel did is extend their alliance with TSMC. So in 2023 we're going to see Intel compute units these tiles, they integrate into the larger chips called S. O. C S B. Manufactured by TSMC. Not exclusively, but we could see that. So literally we could have AMG three nanometer on TSMC CPU blocks, competing with intel chips with TSMC three nanometer CPU blocks and it's on with regard to video. I mean in video is one of these companies that just keeps going charging, charging hard and I'm actually meeting with Jensen wang this week and Arms Ceo Simon Segers to talk about this opportunity and that's a company that keeps on moving interestingly enough in video. If the arm deal does go through will be the largest chip license, see CPU licensee and have the largest CPU footprint on the planet. So here we have AMG who's CPU and Gpu and buying an F. P. G. A company called Xilinx, you have Intel, Cpus, Gpus machine learning accelerators and F. P. G. S. And then you've got arms slashing video bit with everything as well. We have three massive ecosystems. They're gonna be colliding here and I think it's gonna be great for competition. Date. Competition is great. You know, when there's not competition in CPUs and Gpus, we know what happens right. Uh, the beach just does not go on and we start to stagnate. And I did, I do feel like the industry on CPU started to stagnate when intel had no competition. So bring it on. This is gonna be great for for enterprises then customers to and then, oh, by the way, you have the custom Chip providers. WS has created no less than 15 custom semiconductors started with networking and nitro and building out an edge that surrounded the general computer. And then it moved to Inferential for inference trainee um, is about to come out for training Graviton and Gravitas to for general purpose CPU and then you've got apple. So innovation is huge and I love to always make fun of the software is eating the world. I always say yeah but has to run on something. And so I think the combination of semiconductors software and cloud is just really a magical combination. >>Real quick handicap the video arm acquisition. What what are the odds that that they will be successful? They say it's on track. You got a 2 to 13 to 1 10 to 1. >>I say 75%. Yes 25%. No China is always the has been the odd odd man out for the last three years. They scuttled the Qualcomm NXp deal. You just don't know what china is going to do. I think the EU with some conditions is going to let this fly. I think the U. S. Is absolutely going to let this fly. And even though the I. P. Will still stay over in the UK, I think the U. S. Wants to see wants to see this happen, Japan and Korea I think we'll allow this china is the odd man out. >>In a word, the future of h p. E is blank >>as a service >>patrick Moorehead. Always a pleasure. My friend. Great to see you. Thanks so much for coming back in the cube. >>Yeah, Thanks for having me on. I appreciate that. >>Everybody stay tuned for more great coverage from HP discover 21 this is day Volonte for the cube. The leader and enterprise tech coverage. We'll be right back.

(upbeat music) >> Narrator: From around the globe, it's theCUBE. Presenting Future Cloud. One event, a world of opportunities. Brought to you by Cisco. >> Okay. We're here with Thomas Scheibe, who's the vice president of Product Management, aka VP of all things Data Center Networking, STN, cloud, you name it in that category. Welcome Thomas, good to see you again. >> Hey, same here. Thanks for having me on. >> Yeah, it's our pleasure. Okay. Let's get right into observability. When you think about observability, visibility, infrastructure monitoring, problem resolution across the network, how does cloud change things? In other words, what are the challenges that networking teams are currently facing as they're moving to the cloud and trying to implement hybrid cloud? >> Yeah. (scoffs) Yeah. Visibility as always is very, very important and it's quite frankly, it's not just, it's not just the networking team, it's actually the application team too, right? And as you pointed out, the the underlying impetus to what's going on here is the, the data center is wherever the data is, and I think we said this a couple years back. And really what happens the, the applications are going to be deployed in different locations, right? Whether it's in a public cloud, whether it's on-prem and they're built differently, right? They're built as micro servers, so they might actually be distributed as well at the same application. And so what that really means is you need, as an operator as well as actually a user, a better visibility, "where are my pieces?", and you need to be able to correlate between where the app is and what the underlying network is, that is in place in these different locations. So you have actually a good knowledge why the app is running so fantastic or sometimes not. So I think that's, that's really the problem statement. What, what we're trying to go after with observability. >> Okay. Let's, let's double click on that. So, so a lot of customers tell me that you got to stare at log files until your eyes bleed, then you've got to bring in guys with lab coats who have PhDs to figure all this stuff out. >> Thomas: Yeah. >> So you just described, it's getting more complex, but at the same time, you have to simplify things. So how, how are you doing that? >> Correct. So what we basically have done is we have this fantastic product that is called ThousandEyes. And so what this does is basically (chuckles) as the name which I think is a fantastic, fantastic name. You have these sensors everywhere and you can have a good correlation on links between if I run a from a site to a site, from a site to a cloud, from the cloud to cloud. And you basic can measure what is the performance of these links? And so what we're, what we're doing here is we're actually extending the footprint of the ThousandEyes agent, right? Instead of just having a, an inversion machine of clouds we are now embedding them with the Cisco network devices, right? We announced this was the Catalyst 9000. And we're extending this now to our 8000 Catalyst product line for the for the SD-WAN products, as well as to the data center products, in Nexus line. And so what you see is, is you know, a half a thing, you have ThousandEyes. You get a million insights and you get a billion dollar off improvements for how your applications run. And this is really the, the power of tying together the footprint of what a network is with the visibility, what is going on. So you actually know the application behavior that is attached to this network. >> I see. So, okay. So as the cloud evolves, it expands, it connects, you're actually enabling ThousandEyes to go further, not just confined within a single data center location but out to the network across clouds, et cetera. >> Thomas: Correct. >> Wherever the network is you're going to have a ThousandEyes sensor and you can bring this together and you can quite frankly pick, if you want to say, Hey I have my application in public cloud provider A domain one, and I have another one in domain two I can do monitor that link. I can also monitor, I have a user that has a campus location or a branch location. I kind of put an agent there and then I can monitor the connectivity from that branch location all the way to the, let's say, corporation's data center or headquarter or to the cloud. And I can have these probes and just the, have visibility in saying, Hey, if there's a performance I know where the issue is. And then I obviously can use all the other tools that we have to address those. >> All right, let's talk about the cloud operating model. Everybody tells us that, you know, it's really the change in the model that drives big numbers in terms of ROI. And I want you to maybe address how you're bringing automation and DevOps to this world of hybrid and specifically, how is Cisco enabling IT organizations to move to a cloud operating model as that cloud definition expands? >> Yeah, no, that's that's another interesting topic beyond the observability. So it really, really what we're seeing, and this is going on for, I want to say couple of years now it's really this transition from operating infrastructure as a networking team, more like a service like what you would expect from a cloud provider, right? This is really around the networking team offering services like a cloud provided us. And that's really what the meaning is of cloud operating model, right? Where this is infrastructure running your own data center where that's linking that infrastructure was whatever runs on the public cloud is operating it like a cloud service. And so we are on this journey for a while. So one of the examples um that we have, we're moving some of the control software assets that customers today can deploy on-prem to an instance that they can deploy in a, in a cloud provider and just basically instantiate things there and then just run it that way. Right? And so the latest example for this is what we have, our Identity Service Engine that is now unlimited availability, available on AWS and will become available mid this year, both on AWS and Azure, as a service. You can just go to Marketplace, you can load it there and now increase. You can start running your policy control in the cloud managing your access infrastructure in your data center, in your campus, wherever you want to do it. And so that's just one example of how we see our Customers Network Operations team taking advantage of a cloud operating model and basically deploying their, their tools where they need them and when they need them. >> Dave: So >> What's the scope of I, I hope I'm saying it right, ISE, right? I.S.E, I think it's um, you call it ISE. What's the scope of that? Like for instance, to an effect my, or even, you know address, simplify my security approach? >> Absolutely. That's now coming to what is the beauty of the product itself? Yes. What you can do is really is, a lot of people talking about is, how do I get to a Zero Trust approach to networking? How do I get to a much more dynamic, flexible segmentation in my infrastructure, again, whether this was only campus access as well as the data center and ISE helps you there. You can use it as a pawn to define your policies and then inter-connect from there, right. In this particular case, we would, instead of ISE in a cloud as a software, alone, you now can connect and say, Hey, I want to manage and program my network infrastructure and my data center or my campus going to the respective controller, whether it's DNA Center for campus or whether it's the, the ACI policy controller. And so yes, what you get as an effect out of this is a very elegant way to automatically manage ,in one place, "what is my policy", and then drive the right segmentation in your network infrastructure. >> Yeah. Zero Trust. It was..Pre pandemic it was kind of a buzzword, now it's become a mandate. I, I wonder if we could talk about- >> Thomas: - Yes >> Yeah, right. I mean, so- >> Thomas: -Pretty much. >> I wondered if we could talk about cloud native apps. You got all these developers that are working inside organizations, they're maintaining legacy apps they're connecting their data to systems in the cloud. They're sharing that data. These developers, they're rapidly advancing their skillsets. How is Cisco enabling its infrastructure to support this world of cloud native, making infrastructure more responsive and agile for application developers? >> Yeah. So you were going to the talk we saw was the visibility. We talked about the operating model how our network operates actually want to use tools going forward. Now the next step to this is, it's not just the operator. How do they actually, where do they want to put these tools? Or how they interact with this tools? As well as quite frankly, as how let's say, a DevOps team, or application team or a cloud team also wants to take advantage of the programmability of the underlying network. And this is where we're moving into this whole cloud native discussion, right. Which has really two angles. So it's the cloud native way, how applications are being built. And then there is the cloud native way, how you interact with infrastructure, right? And so what we have done is we're A, putting in place the on-ramps between clouds, and then on top of it, we're exposing for all these tools APIs that can be used and leveraged by standard cloud tools or cloud-native tools, right? And one example or two examples we always have. And again, we're on this journey for a while, is both Ansible script capabilities that access from RedHat as well as Hashi Terraform capabilities that you can orchestrate across infrastructure to drive infrastructure automation. And what, what really stands behind it is what either the networking operations team wants to do or even the app team. They want to be able to describe the application as a code and then drive automatically or programmatically instantiation of infrastructure needed for that application. And so what you see us doing is providing all these capability as an interface for all our network tools, right. Whether this is ISE, what I just mentioned, whether this is our DCN controllers in the data center whether these are the controllers in the, in the campus for all of those, we have cloud-native interfaces. So operator or a DevOps team can actually interact directly with that infrastructure the way they would do today with everything that lives on the cloud or with everything how they built the application. >> Yeah, this is key. You can't even have the conversation of of Op cloud operating model that includes and comprises on-prem without programmable infrastructure. So that's, that's very important. Last question, Thomas, are customers actually using this? You made the announcement today. Are there, are there any examples of customers out there doing this? >> We do have a lot of customers out there that are moving down the path and using the Cisco High-performance Infrastructure both on the compute side, as well as on the Nexus side. One of the costumers, and this is like an interesting case, is Rakuten. Rakuten is a large telco provider, a mobile 5G operator in Japan and expanding, and as in different countries. And so people, some think, "Oh cloud" "You must be talking about the public cloud provider" "the big three or four". But if you look at it, there's a lot of the telco service providers are actually cloud providers as well and expanding very rapidly. And so we're actually very proud to work together with Rakuten and help them build high performance data center infrastructure based on HANA Gig and actually for a gig to drive their deployment to its 5G mobile cloud infrastructure, which is which is where the whole the whole world, which frankly is going. And so it's really exciting to see this development and see the power of automation visibility together with the High-performance infrastructure becoming a reality on delivering actually, services. >> Yeah, some great points you're making there. Yes, you have the big four clouds, they're enormous but then you have a lot of actually quite large clouds telcos that are either proximate to those clouds or they're in places where those hyper-scalers may not have a presence and building out their own infrastructure. So, so that's a great case study. Thomas.Hey, great having you on. Thanks much for spending some time with us. >> Yeah, same here. I appreciate it. Thanks a lot. >> All right. And thank you for watching everybody. This is Dave Vellante for theCUBE, the leader in tech event coverage. (upbeat music)

>>from around the globe. It's the >>cube with digital >>coverage of IBM >>Think 2021 brought to you >>by IBM. Welcome back everyone to the cube coverage of IBM Think 2021 virtual um john for your host of the cube. Our next guest taylor Holloway. Chief technology officer at advent one. Tyler welcome to the cube from down under in Australia and we're in Palo alto California. How are you? >>Well thanks john thanks very much. Glad to be glad to be on here. >>Love love the virtual cube of the virtual events. We can get to talk to people really quickly with click um great conversation here around hybrid cloud, multi cloud and all things software enterprise before we get started. I wanna take a minute to explain what you guys do at advent one. What's the main focus? >>Yeah. So look we have a lot of customers in different verticals. Um so you know generally what we provide depends on the particular industry the customers in. But generally speaking we see a lot of demand for operational efficiency, helping our clients tackle cyber security risks, adopt cloud and set them up to modernize the applications. >>And this is this has been a big wave coming in for sure with you know, cloud and scale. So I gotta ask you, what are the main challenges that you guys are solvent for your customers um and how are you helping them overcome come that way and transformative innovative way? >>Yeah, look, I think helping our clients um improve their security posture is a big one. We're finding as well that our customers are gaining a lot of operational efficiency by adopting sort of open source technology red huts an important partner of ours as his IBM um and we're seeing them sort of move away from some more proprietary solutions. Automation is a big focus for us as well. We've had some great outcomes with our clients or helping them automate um and you know, to live up um you know the stand up and data operations of environments a lot quickly a lot more easily and uh and to be able to sort of apply some standards across multiple sort of areas of their I. T. Estate. >>What are some of the solutions that you guys are doing with IBM's portfolio on the infrastructure side, you got red hat, you've got a lot of open source stuff to meet the needs of clients. What do you mean? What's the mean? >>Uh Yeah I think on the storage side will probably help our clients sort of tackle the expanding data in structured and particularly unstructured data they're trying to take control of so you know, looking at spectrum scale and those type of products from an audio perspective for unstructured data is a good example. And so they're flush systems for more block storage and more run of the mill sort of sort of environments. We have helped our clients consolidate and modernize on IBM power systems. Having Red Hat is both a Lynx operating system and having open shift as a container platform. Um really helps there. And Red Hat also provides management overlay, which has been great on what we do with IBM power systems. We've been working on a few different sort of use cases on power in particular. More recently, SAP Hana is a big one where we've had some success with our clients migrating Muhanna on to onto IBM power systems. And we've also helped our customers, you know, improve some um some environments on the other end of the side, such as IBM I, we still have a large number of customers with, with IBM I and and you know how do we help them? You know some of them are moving to cloud in one way or another others are consuming some kind of IRS and we can sort of wrap around a managed service to to help them through. >>So I gotta ask you the question, you know U C T. Oh you played a lot of technologies kubernetes just become this lingua franca for this kind of like I'll call a middleware kind of orchestration layer uh containers. Also you're awesome but I gotta ask you when you walk into a client's environment you have to name names but you know usually you see kind of two pictures man, they need some serious help or they got their act together. So either way they're both opportunities for Hybrid cloud. How do you how do you how do you evaluate the environment when you go in, when you walk into those two scenarios? What goes through your mind? What some of the conversations that you guys have with those clients. Can you take me through a kind of day in the life of both scenarios? The ones that are like I can't get the job done, I'm so close in on the right team and the other ones, like we're grooving, we're kicking butt. >>Yeah. So look, let's start well, I supposed to start off with you try and take somewhat of a technology agnostic view and just sort of sit down and listen to what they're trying to achieve, how they're going for customers who have got it. You know, as you say, all nailed down things are going really well. Um it's just really understanding what what can we do to help. Is there an opportunity for us to help at all like there? Um, you know, generally speaking, there's always going to be something and it may be, you know, we don't try and if someone is going really well, they might just want someone to help with a bespoke use case or something very specific where they need help. On the other end of the scale where a customer is sort of pretty early on and starting to struggle. We generally try and help them not boil the ocean at once. Just try and get some winds, pick some key use cases, you know, deliver some value back and then sort of growing from there rather than trying to go into a customer and trying to do everything at once tends to be a challenge. Just understand what the priorities are and help them get going. >>What's the impact been for red hat? Um, in your customer base, a lot of overlap. Some overlap, no overlap coming together. What's the general trend that you're seeing? What's the reaction been? >>Yeah I think it's been really good. Obviously IBM have a lot of focus on cloud packs where they're bringing their software on red hat open shift that will run on multiple clouds. So I think that's one that we'll see a lot more of overtime. Um Also helping customers automate their I. T. Operations with answerable is one we do quite a lot of um and there's some really bespoke use cases we've done with that as well as some standardized one. So helping with day two operations and all that sort of thing. But there's also some really sort of out there things customers have needed to automate that's been a challenge for them and being able to use open source tools to do it has worked really well. We've had some good wins there, >>you know, I want to ask you about the architecture and I'm just some simplify it real. Just for the sake of devops, um you know, segmentation, you got hybrid clouds, take a programmable infrastructure and then you've got modern applications that need to have a I some have said I've even sit on the cube and other broadcast that if you don't have a I you're gonna be at a handicap some machine learning, some data has to be in there. You can probably see ai and mostly everything as you go in and try to architect that out for customers um and help them get to a hybrid cloud infrastructure with real modern application front end with using data. What's what's the playbook? Do you have any best practices or examples you can share or scenarios or visions that you see uh playing >>out? I think you're the first one is obviously making sure customers data is in the right place. So if they might be wanting to use um some machine learning in one particular cloud provider and they've got a lot of their applications and data in another, you know, how do we help them make it mobile and able to move data from one cloud to another or back into court data center? So there's a lot of that. I think that we spend a lot of time with customers to try and get a right architecture and also how do we make sure it's secure from end to end. So if they're moving things from into multiple one or more public clouds as well as maybe in their own data center, making sure connectivity is all set up properly. All the security requirements are met. So I think we sort of look at it from a from a high level design point of view, we look at obviously what the target state is going to be versus the current state that really take into account security, performance, connectivity or those sort of things to make sure that they're going to have a good result. >>You know, one of the things you mentioned and this comes up a lot of my interviews with partners of IBM is they always comment about their credibility and all the other than the normal stuff. But one of the things that comes out a lot pretty much consistently is their experience in verticals. Uh they have such a track record in verticals and this is where AI and machine learning data has to be very much scoped in on the vertical. You can't generalize and have a general purpose data plane inside of vertically specialized kind of focus. How how do you see that evolving, how does IBM play there with this kind of the horizontally scalable mindset of a hybrid model, both on premise in the cloud, but that's still saying provide that intimacy with the data to fuel the machine learning or NLP or power that ai which seems to be critical. >>Yeah, I think there's a lot of services where you know, public cloud providers are bringing out new services all the time and some of it is pre can and easy to consume. I think what IBM from what I've observed, being really good at is handling some of those really bespoke use cases. So if you have a particular vertical with a challenge, um you know, there's going to be sort of things that are pre can that you can go and consume. But if you need to do something custom that could be quite challenging. How do they sort of build something that could be quite specific for a particular industry and then obviously being able to repeat that afterwards for us, that's obviously something we're very interested in. >>Yeah, tell I love chatting whether you love getting the low down also, people might not know your co author of a book performance guy with IBM Power Systems, So I gotta ask you, since I got you here and I don't mean to put you on the spot, but if you can just share your vision or any kind of anecdotal observation as people start to put together their architecture and again, you know, Beauty's in the eye of the beholder, every environment is different. But still, hybrid, distributed concept is distributed computing. Is there a KPI is there a best practice on as a manager or systems architect to kind of keep an eye on what what good is and how how good becomes better because the day to operations becomes a super important concept. We're seeing some called Ai ops where okay, I'm provisioning stuff out on a hybrid Cloud operational environment. But now day two hits are things happen as more stuff entered into the equation. What's your vision on KPs and management? What to keep tracking? >>Yeah, I think obviously attention to detail is really important to be able to build things properly. A good KPI particularly managed service area that I'm curious that understanding is how often do you actually have to log into the systems that you're managing? So if you're logging in and recitation into servers and all this sort of stuff all the time, all of your automation and configuration management is not set up properly. So, really a good KPI an interesting one is how often do you log into things all the time? If something went wrong, would you sooner go and build another one and shoot the one that failed or go and restore from backup? So thinking about how well things are automated. If things are immutable using infrastructure as code, those are things that I think are really important when you look at, how is something going to be scalable and easy to manage going forward. What I hate to see is where, you know, someone build something and automates it all in the first place and they're too scared to run it again afterwards in case it breaks something. >>It's funny the next generation of leaders probably won't even know like, hey, yeah, taylor and john they had to log into systems back in the day. You know, I mean, I could be like a story they tell their kids. Uh but no, that's a good Metro. This is this automation. So it's on the next level. Let's go the next level automation. Um what's the low hanging fruit for automation? Because you're getting at really the kind of the killer app there, which is, you know, self healing systems, good networks that are programmable but automation will define more value. What's your take? >>I think the main thing is where you start to move from a model of being able to start small and automate individual things which could be patching or system provisioning or anything like that. But what you really want to get to is to be able to drive everything through, get So instead of having a written up paper, change request, I'm going to change your system and all the rest of it. It really should be driven through a pull request and have things through it and and build pipelines to go and go and make a change running in development, make sure it's successful and then it goes and gets pushed into production. That's really where I think you want to get to and you can start to have a lot of people collaborating really well on this particular project or a customer that also have some sort of guard rails around what happens in some level of governance rather than being a free for all. >>Okay, final question. Where do you see event one headed? What's your future plans to continue to be a leader? I. T. Service leader for this guy? BMS Infrastructure portfolio? >>I think it comes down to people in the end, so really making sure that we partner with our clients and to be well positioned to understand what they want to achieve and and have the expertise in our team to bring to the table to help them do it. I think open source is a key enabler to help our clients adopt a hybrid cloud model to sort of touched on earlier uh as well as be able to make use of multiple clouds where it makes sense from a managed service perspective. I think everyone is really considering themselves and next year managed service provider. But what that means for us is to provide a different, differentiated managed service and also have the strong technical expertise to back it up. >>Taylor Holloway, chief technology officer advent one remote videoing in from down under in Australia. I'm john ferrier and Palo alto with cube coverage of IBM thing. Taylor, thanks for joining me today from the cube. >>Thank you very much. >>Okay, cube coverage. Thanks for watching ever. Mhm mm