>> Narrator: Silicon Angle Media presents TheCUBE! Covering Alibaba Cloud's annual conference. Brought to you by Intel. Now, here's John Furrier.... >> Hi, I'm John Furrier of Silicon Angle Media based in the United States in Silicon Valley in Palo Alto, California. I'm also co-host of TheCUBE where we go out through the event and extract the signal from the noise. We're here in China, we are here with a business development director of America's for Alibaba Cloud International, Karen Lu. Thanks for taking the time. >> Karen: Sure, absolutely. >> So, it's exciting for us from the US to come to China to hear the (mumbles), but I'm blown away by the culture. It's not a B-to-B tech conference. It's not boring. It's exciting. Talk about the Alibaba Cloud. What's so special about Alibaba Cloud? >> Sure. Alibaba Cloud is actually the encumbered cloud provider in China, and further more we extend our reach into global market since two years ago, and our strategy for globalize our cloud services is really to bridge up the business communities from overseas to China, from US to China, from US to Asia-Pacific, and to connect the rest of the world as well. Our goal is set up the platform to enable our enterprise customers, our SMEs, small and medium customer base be able to utilize our platform to develop their applications, their vertical solutions to benefit their end users. >> Alibaba Cloud has come such a long way since 2009. So much has happened, Alibaba grew up as a company. It's not just e-commerce. It's intersecting e-commerce, entertainment and web services, which is the magical formula that consumers want. They don't want just a business solution or just do e-commerce. You guys have weaved that formula together. What's special about that formula, and why is Alibaba important to the folks in the United States? >> I think it's all about the ecosystem and what makes the people, the people's community, and business community benefit from the services we provided to the world, right? Not just the e-commerce platform that have been running for the past 18 years, but also entertaining, to the map services, location services, the data services like Ali Cloud is providing, and be able to put out those elements together, and benefit people's lives, and help to improve users' experience from globally. >> It's been impressive here in China. Now as you go outside of China in the globalization plan, what's the strategy, what's the tactics? What are you going to do? >> I think our value is to, as I mentioned earlier, bridge up the business communities, especially to enable the outside world benefit a huge market from Mainland China and rest of the world as well, so I think I think our key value is to enable the business communities and be able to help them reach out outside the world. That being said, one of our key globalization strategy is to be able to help the SME's, small and medium companies to benefit the new technologies to the level that they won't be able to get in the past. It's the old technologies. >> John: What's some of the statistics or facts, fun facts, or Alibaba stats in the US, North America, your presence there, can you share what the current situation is? >> Sure. I think things about two years ago, when we extend our reach in two your market, we now have more than two thousand customers from individual to startup, to medium enterprises, and to some very large enterprises in the world as well. People are from the communities get to know Alibaba Cloud and get to know Alibaba not only provide to the e-commerce services, the EWTP platform to the world. We're also brought the data technologies. We also provided the technologies to the world that benefit their reach to the world. >> Everyone talks about data-driven. You guys have a very specific data formula, data fueling, not just getting the data from engagement data and user data, but fueling data in for user experience. The question is as you go outside of China into the US, certainly you have a developer ecosystem, you have a business ecosystem. >> Correct. >> How do the folks benefit locally in the US, to our business, do they have have access to China? Is it the services, is it the technology? Can you share the benefits to the developers and to the businesses? >> Sure absolutely. We ran a program called the China Connect, and that's the program we help the business communities you have, from the IVs, the independent after vendors, from the sales providers and developers' opportunity of communities to be able to develop their applications and software, and bring those benefits to China market. Through this process, it's hard to navigate a brand new market, especially in China, without knowing the people, the communities, the culture, the business practices here, right? We actually provide a platform, a program to help them to get to know the market, and help them to land their business in China through this program, and help them, of course, expertise their business roles in China. >> A lot of people want to know what's inside their cloud. It's one of those things where this mysterious cloud. The security's a concern, but partnerships are critical. Talk about what's inside your cloud. Intel's a big partner. What's the Alibaba-Intel partnership like? >> It's a fantastic partnership. We have been established over the past years, and Intel is one of our strategic alliance in the marketplace. They provide us a lot from hardware to technology, in terms of helping us to establish the platform with the business communities, not only China, but globally, so we really appreciate Intel's partnership, and moving forward we are looking for more reciprocal partnership with Intel to be able to form more strategic partnership to be able to benefit the business communities, and people's communities as well. >> For the folks in the US, I'll say that this is an amazing conference. It's got a million people here. I don't even know the numbers. I'm sure you have the numbers handy, but it's a mix of developers. You have a crowded house here with developers, but you also have some business people. You have key partners. I saw some US companies here. What's the vibe at the event? What's the feeling here? You got a music festival three nights. It's not a boring tech conference. Is that by design? Share the stats, how many people are here? >> I guess this is the excitement of this, the conference, annually, we actually invite a lot of our customers from US, and the rest of the world to join us to share the excitement from China, to share the experience from Alibaba. Just like Jack said, the vision for us is to make people's lives more healthier and happier. The 2H strategy from us, right, is not just the hardworking. It's also the fun. It's also the the excitement for us to share these technologies, to share this platform, and to enable people to enjoy this technology. >> The scene I see here is interesting. I've seen at Apple, in the late 90's when Steve Jobs transformed that company, he had the vision of technology meeting liberal arts. That became their calling card. You guys have art and science come in together. It's not just scientists and developers. You have artists here because user experience is super important >> exactly. >> Is that part of the culture as science and art comes together because Jack is a charismatic leader. He's a culptive personality. Young Company. >> Karen: It is. >> Share the culture. >> It is. Just like Jack and other topic executives has been sharing with the community, we want to make sure technology is inclusive elements to everyone in the community, not just for the programmers or developers, or the very high-tech companies, right? It should benefit the entire society, and fun, of course, always as part of it to make people's life happier, and to make users' experience more satisfied. >> You had a career in international technology industry for a while. You see how it's played out in the past. We're in a different now. It's a global world. The internet has opened up a lot of good things, and sometimes not so good things. The US have the selection in fake news, but as the culture starts connecting, a new kind of normal is evolving. How does Alibaba see themselves in this new world order? >> I think we see ourselves as the enabler and platform to bring the technology, and bring the people, and bring the happiness together to benefit everyone in the world, not just the tech sectors, or just the e-commerce sectors, or just one of the single verticals. We are trying to bring the technologies, and the enablement, the platform that everybody can enjoy. That's the core value for us as the inclusive technology provider. >> For the folks in the United States that will see this video, share something that they may not know about Alibaba. Might be the first time in getting to see some of the culture and some of the commentary, what should they know about Alibaba as you guys move in and become global? They're going to see some services. Is it the services, is it the people, the culture, what should they engage with Alibaba at cloud? How should they see Alibaba Cloud? >> First of all, we are one of the top three cloud providers in the world. If you look at the latest (speaks in foreign language) released a couple of weeks ago, and that's why globalization is critical for us, and we want to be able to reach out to the overseas communities, and we want to build up the trust and the confidence with the local business communities, like the rating, where in US market for instance. For us, become the global family is critical for us, and this is our vision to bring the values to them as well. >> That's fantastic, spectacular culture, and the ecosystem is just now growing, open-source software is growing exponentially, global fabric of communities developing. It is opportunities for US companies and developers to access China. Talk a little bit more about the potential that entrepreneurs and businesses could have in this global framework. >> Sure. The beauty of cloud is actually the ecosystem. It's not just one company or one vertical. For us, for instance, we try to enable the small business, especially those startup business by offering them the free resources from our infrastructure at global level, be able to enable those young peoples, especially, to create their own ideas, to be innovative, and to utilize our resources, be able to access the technologies like the way the big companies has been invested into. This is, I think, as an example for us to commit to this global market. I think for us to be part of that family, especially in Silicon Valley is critical because of the technologies, because of innovations, and because of the mindset in Silicon Valley. That's why we set up our R&D centers, we set up our frontend back office in Silicon Valley as well be able to part of that reach in, and not only to learn the technologies, but sense the mindset in our reach in. I think that's critical for us as well as the Chinese headquarter of the company, but with a global vision. >> And where in Silicon Valley is your office? >> We're headquartered in San Mateo, California for US operations. >> And entrepreneurship is changing, and it's global. It's exciting. What's the benefit to entrepreneurship? Certainly, ventured capitalists are highly interested in the China market. They've been in here for a while. Is it coming together? >> Yes, it is indeed. Actually, not only we funding a lot of the new tech companies, we also been able to help them to find their partners to build up a extended ecosystem. In Silicon Valley, in West Coast reach ins, as well as extend from the inner US, in mid-western reach in, Chicago for instance, to New York coastal areas as well. >> I noticed on the sponsorship list and partner list in your ecosystem, a logo that is new, but it's super important in the US. It's growing like crazy. The Cloud Native Compute Foundation's here, and that's the Linux Foundation. They're partnering with you. The cloud native developer market is evolving very, very quickly. They're different than the old classic IT developers. A new generation, it's not IT anymore. It's data that's driving it, and it's open-source. How do you guys engage with that community because, clearly, they win with you. >> Yes. We're actually working with a lot of open-source partners like Docker, (mumbles), and others, be able to help them to bring the communities to bring their customers onto our infrastructures and create this platform to help the developer communities to develop their applications. It's a lot of vertical focus, the solution department tasks right now. >> Excuse me, you mentioned small, medium size enterprises and business, but the big enterprises are transforming as well. How do you see Alibaba helping them because they're going cloud native? They're going private cloud on premise. You have quantum computing. You even have IOT. You have a lot of things. How's the digital transformation message for enterprises and for small businesses that don't want to pay the technology tax. >> I think for large enterprises, the most strategy you have been seeing from the marketplace, one is multi-cloud strategy. People need redundancy. People want to reduce the dependencies for one or two cloud providers, and we work with other cloud providers in the community to provide interval qualities to support this multi-cloud strategies. On the other side, couple years back, people didn't know what's in a cloud. And then, people rush to cloud for everything. And now, people come back and review the strategies and find out hybrid-cloud strategy is more suitable for large enterprises. They have their on-prem architect and infrastructure. Meanwhile, they move some of their applications to cloud. It's a good combination of on-prem physical infrastructure cloud topology. We have been seeing a trend for both for large enterprise clients. For small business, especially for small business, they don't have the upfront huge investment paying to the infrastructure, and we provide them the instant access to the infrastructure, not only from computing storage network and the database perspective, more importantly from security perspective. >> The Alibaba Infrastructure services, I saw a part of the display here, very prominent in that equation. You guys have the scale. What can you share about the under-the-hood? What's the technology look like? What's the engine of Alibaba Cloud? How mature is it? What's to do? Where's the strategic direction? Block-chain is important, but now, that's changing everything It's all this new wave's coming. >> Just like the (speaks in foreign language) indicated two months ago, if you look at the overall qualifications to be a world lead cloud provider, we're number four, after AWS, Microsoft Azure, and Google Cloud, but if you look at market share and revenue, we're number three. That being said, we actually provide a very comprehensive technology, and the infrastructure to the business communities, and people's communities. For instance, from the global footprint perspective, right now, we have 14 reach ins, pretty much cover all the major market in the world. By end of this year into beginning of next year, we're going to activate two to three reach ins, make it 16 to 17 reach ins globally, that we can offer the global cloud solutions for the big and small businesses. >> That's exciting, and Silicon Valley certainly import our home base. Are you guys hiring, is there expanding? Share a little bit of a public service announcement on what's going on in the Silicon Valley area. You guys hiring, looking for engineers, what kind of people are you looking for? >> Yes, (laughs) great question. Actually, we are hiring, and we're looking for talented professionals join us from those marketing, business development, to cloud architect, to technical account management, to marketing premises, so we want to build up a business that we can truly build up the trust towards the local business communities. That's why we hire a lot of local talented young professionals, and to help them to be able to fit in to the culture, the unique culture of Alibaba, and also be able to contribute to this journey, very exciting journey... >> China has always been big. Everyone in the United States knows. The numbers are big here in terms of mobile deployment, app size. A lot of the people in the US look at China and say, "Wow, we can collaborate with China." It's a very nice distribution system, but they got to take care of their needs at home. >> Exactly. >> This is a big part of the undercurrent we're hearing. How do you guys help? >> Globalization is always critical for any business, even for some small business. Just like Jack Ma said this morning at his speech, even for small business, they need to globalize. They need to reach out to more business communities, and more customers. For us, because of the huge market in China, because of the EWTP platform we set up globally, because Alibaba Cloud Infrastructure and our global footprint, we're actually being able to help our customers, not only access the infrastructure from cloud perspective, but also help them to leverage our ecosystem from different business unit, and more partnership, to be able to help them to expertise their business in China and globally. >> That's exciting. Finally, developers are a big hot button. Everyone always says, I hear comments like, "We have to own the developer community," not that you could own the developer. No one wants to be owned, but what they mean is they want to win over the hearts and minds of developers. A lot of competition, and developers want programmable infrastructure. In dev ops world, that's called dev ops. That is really the new normal in developer community. How do you guys attack that developer market? >> We actually want to enable the developers community, not own or just win over. We want constantly enable them with the new platform, the new business models, the new programs that we can bring them together. That's our mission, enablement. >> Congratulations on a spectacular formula. Thanks for having us here, TheCUBE and Silicon Angle, and thanks for your time. >> Thank you so much for the opportunity. >> Karen Lu here in China with TheCUBE. Exclusive coverage in China, bringing the stories of the most important trends and tech in Alibaba Cloud. Really changing the game with their formula of e-commerce, entertainment, and entertainment. This is not B-to-B, boring to boring. It's exciting, in a music festival. 60 thousand people are here at this conference. Developers in the world watching, I'm John Furrier with Silicon Angle. Thanks for watching. (techno music)

>> Announcer: SiliconANGLE Media presents theCUBE! covering Alibaba Cloud's annual conference, brought to you by Intel. Now here's John Furrier.... >> Hi I'm John Furrier, with SiliconANGLE, Wikibon and theCUBE. I'm the co-founder based in Silicon Valley, California, Palo Alto, California, and I am here in Hangzhou, China for the Alibaba Cloud conference in Cloud City, it's the biggest cloud computing conference here in China. I'm excited to be here with Dr. Min Wanli, who's the Chief Data Scientist and General Manager of Big Data division at Alibaba Cloud. Dr. Wanli, thank you for spending time. >> Thank you for having me. >> We have seen a lot of data in the conversation here at the show, data technology's a big part of this new revolution, it's an industrial revolution that we've never seen before, a whole 'nother generation of technology. What does data technology mean to Alibaba? >> Okay, it means everything. So first off, our internal technical speaking, it's technology handling massive real-time data and streaming data, and that's of different variety. For instance the app for the mobile app, for system knock, the customer behavior, they click, and they click browsing of the digital image of each merchant and asking for the price and compare against another similar product. All these behaviors are translated as data, and this data will be further merged with the archived data and try to update the profile of this customer's interests, and then try to detect whether there's a good match of they current merchant with the customer intent. If the match is good, then will flash this to the top priority, the top spot. So that try to increase the conversion rate. So if the conversion rate is high, then our sales is high. So DT, data technology means everything to Alibaba. >> It's interesting, I find my observation here, it's so fascinating because in the old days, applications produced data, that was stored on drives. They'd go to data warehouses, and they'd analyze them. You guys, in Alibaba Cloud are doing something fundamentally different, that's exciting in the sense that you have data, people call it data exhaust or data in general, but you're reusing the data in the development in real-time. So it's not just data exhaust, or data from an application. You're using the data to make a better user experience and make the systems smarter and more intelligent. Did I get that right? >> Exactly, exactly. This is a positive feedback loop, in a way, so in the old-fashioned way, you archived the data for offline analysis and for post-event analysis, and trying to identify whether there's any room for improvement. But that's fine. But now people cannot wait, and we cannot wait. Offline is not enough. So we have to do this in real time, online, in a feedback version, in search of a way that we could capture exactly at the right moment, understand the intent of the customer, and then try to deliver the right content to the customer on the fly. >> Jackie Ma, or Jack Ma, your boss, and also Dr. Wong who I spoke with yesterday, talk about two things. Jack Ma talks about a new revolution, a new kind of industrial revolution, a smarter world, a better society. Dr. Wong talks about data flowing like a river, and you hear Hangzhou as an example, but it highlights something that's happening across the world. We're moving from a batch, slow world with data to one that's in motion and always real time. They're not necessarily mutually exclusive, but they're different. A data lake or a data river, whatever word you want, I don't really like the word data lake personally, I think it means, it's batch to me. But batch has been around for a while. Real time mixed streaming. This is something that's happening, and it's impacting the architecture and the value proposition of applications, and it's highlighted in Internet of Things, it's highlighted in examples that we're seeing that's exciting like the ET Brains. Can you share your view in your project around ET Brains, because that is not just one one vertical. It's healthcare, it's industrial, it's transportation, it's consumer, it's everything. >> Yeah, good question, so first of all I concur with you that data lake already exists, will continue to exist, because it's got its own value because our ET Brain for example, actually emerged from data lake, because it has to learn all the benchmark, the baseline model, the basic knowledge from the existing archive data, which is a data lake. However, that's not enough. Once you have the knowledge, you have the capability but you need to put that in action. So we are talking about data in motion, data in action. How do we do that? So once you have the training example, all the training data from data lake, and you train the brain, the brain is mature enough and in the next step you want to push the brain coupled with real-time streaming data, and then to generate real-time action in real-time manner in preemptive way, rather than posting in a reactive way. So for example, in transportation and travel, T and T, travel and transportation, and traffic management. So currently, all the authorities, they have access to real-time information, and then they do a post-event analysis if there's a traffic jam, and then they want to do some mitigation. However, the best scenario is, if you can prevent the traffic jam from happening in the first place, right, how can you foresee there will be, there would be, there could be traffic jam happen in 10 minutes from now, and then you take a preemptive strike, and then try to prevent that from happening. That's the goal ET Brain, in traffic management want to achieve. Like for example, you see the ambulance case, and once the ET Brain receives the message say the ambulance is going to go to Point A, pick up a patient, and carry that patient, rush them to Hospital B, and then it immediately calculates the right routing, the driving direction, and the calculate the ETA to every intermediate intersection and then try to coordinate with the traffic lights, traffic signal. All this systematic integration will create on demand a green wave for ambulance, but in the past ambulance is just by the siren, right. >> Yeah, this is fascinating, and also I'd like to get your thoughts, because you bring us something that's important, and that is, and I'd like to connect the dots for the audience, and that is, real time matters. If you're crossing the street, you can't be near real time, because you could get hit by a car. But also latency's important, also the quality of the data is good. I was talking to an executive who's laying out an architecture for a smart city, and he said, "I want the data in real time," and the IT department said, "Here it is, "it's in real time", and he says, "No, that's last year's data." And so the data has to be real time and the latency has to be low. >> Exactly. I completely agree. The latency has to be low. Unfortunately, in the current IT infrastructure, very often the latency exist. You cannot eliminate that, right? And then you have to live with that, so the ET Brain acknowledge the fact, in fact we have our own algorithm designed in a way that it can make a shortened prediction. So based on five minutes ago data, the data collected five minutes ago, and then it can project the next five minutes, next 10 minutes, what would be the data, and then use that to mitigate, or to conquer, to offset the latency. So we find that to be a good strategy, because it's relatively easy to implement, and it is fast and efficient. >> Dr. Wanli, fascinating conversation. I'd like to get your thoughts on connecting that big data conversation or data conversation to this event. This is a cloud computing event. We at theCUBE and SiliconANGLE and our Wikibon research team we go to all the events. But sometimes the big data events are about big data, Hadoop, whatever, and then you have cloud, talking about DevOPs, and virtual machines. This conference is not just a siloed topic. You have cloud computing, which is the compute, it's the energy, it's the unlimited compute potential, but it's also got a lot of data. You guys are blending it in. >> Exactly. >> Is that by design, and why is that important? >> It's by design. Actually, you cannot separate cloud from data, big data. Or you cannot talk big data without referring to cloud, because once the data is big, you need a huge computation power. Where does that come from? Cloud computing. So that means that data intelligence, all the value has to require a good technological tool to unleash the value. What's the tool? Cloud computing. For example, the first time IBM come up with a smart plan, a smart city, that's 2005 or 2006, around that time, there's no cloud computing yet, at the earliest emerging stage. And then we see what happens. And the smarter city and then gradually become IT infrastructure construction. But it's not DT, data technology. So they invested billions of dollars in the infrastructure level, and they collect so much data, but all the data become a burden to the government, to save, to archive the data or protect the data from hacking, right. Now, these days, if you have the cloud computing available, you can do real-time analytics to unleash the value in the first place, at the first moment you receive the data and then later on you know which data is more valuable, which data is of less value, and then you know how much you want to archive. >> Our Wikibon research team put out research this past year that said IT is no longer a department, it's everywhere, >> It's everywhere >> it supports your DT, data technology, it's a fabric. But one thing that's interesting going back to 2005 to now is not only the possibility for unlimited compute, is that now you're seeing wireless technologies significantly exploding in a good way, it's really happening. That's also going to be a catalyst for change. >> Definitely. >> What's your thoughts on how wireless connectivity, 'cause you have all these networks, you have to move data around, it has to be addressable, you have to manage security. That's a heavy load.\ what do you do, how are you guys doing that? >> Okay, very good question. We faced this challenge a couple of years ago, we realized that, because in Chinese domestic market, the users they are migrating from PC to mobile, and this create the mobile phone has wi-fi, right, so interacts with another AP, Access Point, right. So then how do we recognize our tracking, and recognizes ID identification, all this stuff, create huge headache to us, and this time, in this conference, we announce our solution for mobile, for mobile cloud. So what does that mean? So essentially, we have a cloud infrastructure product designed in order to do a real-time integration and do a data cleansing of the mobile data. I mean by mobile, and wireless as well. Wireless means even bluetooth, or even IoT, IoT solution also supported there. So this is a evolving process in the way. The first solution probably is less than perfect, but gradually, as we are expanding into more and more application scenario, and then we will amalgamate the solution and try to make it more robust. >> You guys have a good opportunity, and Alibaba Cloud certainly met with Karen Liu about the opportunity in North America and United States where I'm from. But Alibaba Cloud, and Alibaba Group, in the Alibaba Cloud has had a great opportunity, almost a green field, almost a clean sheet of paper, but you have a very demanding consumer base here in China. They're heavily on mobile as you pointed out, but they love applications. So the question I want to ask you is, and I'd love your thoughts on this. How do you bring that consumerization, its velocity, the acceleration of the changing landscape of the consumer expectation and their experience to small businesses and to enterprises? >> Ok, very good question. So user not just customer base, and the demanding customers in China trying to help us to harden our product, harden our solution, and to reduce the cost, the overall cost, and the economy of mass scale, economy of scale, and then once we reach that critical point, and then our service is inexpensive enough, and then the small and medium, SMB, small and medium business they could afford that. And in old days, SMB, they want to have access to high performance computing, but they do not have enough budget to afford the supercomputer. But these days now, because our product, our computation product, cloud product, big data product is efficient enough, so the total cost is affordable. And then you see that 80% of our customers of Alibaba, at least 80%, are actually SMB. So we believe the same practice can be applied to overseas market as well. >> You bring the best practices of the consumer and the scale of Alibaba Cloud to the small and medium-sized enterprises, and they buy as they grow. >> Exactly. >> They don't buy a lot upfront. >> Yeah, yeah, they buy on demand, as they need. >> That's the cloud, the benefit of the cloud. >> Exactly. >> Okay, the compute is great, you've got greatness with the compute power, it's going to create a renaissance of big data applications where you see that. What is your relationship with Intel and the ecosystem, because we see, you guys have the same playbook as a lot of successful companies in this open source era, you need horsepower and you need open source, what is Alibaba's strategy around the ecosystem, relationship with Intel, and how are you guys going to deal with partners? >> Yeah, first of all, so we really happy that we have Intel as our partner. In our most recent big data hackathon for the medical AI competition, and we just closed that competition, that data hackathon. Okay, very fascinating event, okay. Intel provided a lot of support. All the participants of this data hackathon, they do their computing leveraging on the Intel's products, because they do their image process. And then we provided the overall computing platform. Okay, this is a perfect example of how we collaborated with our technology partners. Beyond Intel, in terms of the ecosystem, first of all, we are open. We are building our ecosystem. We need partners. We need partners from pure technology perspective, and we also need partners from the traditional vertical sectors as well, because they provide us domain knowhow. Once we couple our cloud computing and big data technology with the domain knowhow, the subject matter expertise, well together the marriage will generate a huge value. >> That's fantastic, and believe me, open source is going to grow exponentially, and by 2025 we predict that it's going to look like a hockey stick. From the Linux foundation that's doing amazing work, you're seeing the Cloud Native Foundation. I want to get your thoughts on the future generation. >> Yeah, you mean open source? >> The future generation that's using open source, they're younger, you guys have tracked, you know the demographics in your employee base, you have a cloud native developer now emerging. They want to program the infrastructure as they go. They don't want to provision servers, they want the street lights to just work, whatever the project, the brains have to be in the infrastructure, but they want to be creative. You're bringing two cultures together. And you've got AI, it's a wonderful trend, machine learning is doing very well. How do you guys train the younger generation, what's your advice to people looking at Alibaba Cloud, that want to play with all the good toys? You got machine learning, you got AI, they don't want to necessarily baby, they don't want to program either. They don't want to configure switches. >> Yeah, very good question. Actually this is related to our product strategy. So in a way, like today we announce our ET Brain, so we are going to release this and share this as a platform to nurture all the creative mind, creative brains, okay, people, trying to leverage on this brain and then do the creative job, rather than worry about the underlying infrastructure, the basic stuff. So this is that part which we want to share with the young generation, tell them that unleash your creativity, unleash your imagination, don't worry about the hard coding part, and we already build the infrastructure, the backbone for you. And then image anything you think possible and then try to use ET Brain, try to explore that. And we provide the necessary tool and building blocks. >> And the APIs. >> And the APIs as well, yes. >> Okay, so I want to get your thoughts on something important to our audience, and that is machine learning, the gateway to AI. AI, what is AI? AI software, using cloud. Some will argue that AI hasn't really yet come on the scene but it's coming. We love AI, but machine learning is really where the action is right now, and they want to learn about how to get involved in machine learning. So what's your view on the role of machine learning, because now you have the opportunity for a new kind of software development, a lot of math involved, that's something that you know a lot about. So is there going to be more libraries? What's your vision on how machine learning moves from a bounded use case to more unbounded opportunities, because, I'm a developer, I want the horizontally scalable resource of the cloud, but I'm going to have domain expertise in a vertical application. So I need to have a little bit of specialism, and I want the scalability. So data's got to move this way and it's got to be up this way. >> Yes, yeah, okay, let me put it this way. So first off, for people who are really interested in AI, or they want to work on AI, my recommendation first of all, you got to learn some mathematics. Why, because all the AIs and machine learnings is talking about algorithms, and those algorithms are actually all about math, mathematics, the formula, and also the optimization, how to speed up the convergence of the algorithms, right. So all this maths is important, okay. And then if you have that math background, and then you have the capability to judge or to see next, which algorithm, or which machine software is suitable to solve the vertical problems. Very often the most popular algorithm may not be the right one to solve the specific vertical problems. So you're going to the way, capability to differentiate and to see that and make the right choice. That's the first recommendation. The second recommendation, try to do as many type of examples as possible, try to get your hands on, don't stop at looking at the function specification and oh, this is a function and input, output, da da da, but you need to get your hands dirty, get your hands on the real problem, the real data. So that you can have a feeling about how powerful it is or how bad or how good it is. Once you have this kind of experience, and then you do have capability, you gradually build up a cumulative capability to make a right choice. >> This is fascinating, Dr. Wanli, this is fantastic. I want to follow up on that because you're bringing up, in my mind I can almost see all these tools. There's an artisan culture coming on. You're seeing that. Dr. Wong discussed that with me yesterday. Artisans meeting technologists, scientists and creatives. UI, we're seeing evolutions in user experience that's more art. And so culture's important. But the machine learners of the algorithms, sometimes you have to have a lot of tools. If you have one tool, you shouldn't try to use tools for other jobs. So bring this up. How should a company who's architecting their business or their application look at tooling, because on one hand, there's the right tool for the right job, but you don't want to use a tool for a job that it's not designed for. To your point. Tools, what's your advice and philosophy on the kinds of toolings and when to engage platforms, relationship between platforms and tools. >> Okay, then put it this way. So, this is a decision based on a mixture of different criteria together. So first of all, from technology perspective, and secondly from the business perspective. From technology perspective I would say if your company's critical competence is technical stuff, and then you've got to have your own tool, your own version. If you only rely on some existing tool from other companies, your whole business actually is dependent on that, and this is the weakest link, the most dangerous link. But however, very often to develop your own version of the tool takes forever, and market wouldn't give you so much time. And then you need too strike a balance, how much I want to get involved for self development and how much for in-house development, and it's how much I want to buy in. >> And time. >> And time as well, yes. And another one is that you've got to look at the competitive landscape. If this tool actually has already existed for many years and many similar product in the market, and the problem is not a good idea to reproduce or reinvent, and then you're going to why not buy it, you take that for granted. And it think that's a fact, and then you build a new fact, right. So this is another in terms of the maturity of the tool, and then you need to strike a balance. And in the end, in the extreme case, if your business, your company is doing a extremely new, innovative, first of a kind study or service, you probably need some differentiate, and that differentiator probably is a new tool. >> Final question for you. For the audience in America, in Silicon Valley, what would you like to share from your personal perspective about Alibaba Cloud that they should know about? Or they might not know about and should know about. >> Okay, 'cause I worked in the US for 16 years. To be frank, I knew nothing about Alibaba until I came back. So as a Chinese overseas, I'm so ignorance about Alibaba until I came back. So I can predict, I can guess, more or less, in the overseas market, in US customers, they probably know not that much about Alibaba or Alibaba Cloud. So my advice and from my personal experience, I say, first of all, Alibaba is a global company, and Alibaba Cloud is a global company. We are going to go global. It's not only a Chinese company, for example. We are going to serve customers overseas market in Europe and North America and Southeast Asia. So we want to go global first. And second, we are not only doing the cloud. We are doing blending of cloud and big data and vertical solutions. I call this VIP. V for vertical, I for innovation. P for product. So VIP is our strategy. And the innovation is based upon our cloud product and big data product. >> And data's at the center of it. >> Data is the center of this, and we already got our data technique, our data practice from our own business, which is e-commerce. >> And you're solving some hard problems, the ET Brain's a great playground of AI opportunity. You must be super-excited. >> Yeah, yeah, right, right, okay. >> Are you having fun? >> Yes, a lot of fun. Very rewarding experience. A lot of dreams really come true. >> Well, certainly when you come to Silicon Valley, I know you have a San Mateo office, we're in Palo Alto, and this is theCUBE coverage of Alibaba Cloud. I'm John Furrier, co-founder of SiliconANGLE, Wikibon research and theCUBE, here in China covering the Alibaba Cloud, with Dr. Wanli, thanks for watching.

>> SiliconANGLE Media presents ... theCUBE! Covering AlibabaCloud's annual conference. Brought to you by Intel. Now, here's John Furrier... >> Hello everyone, I'm John Furrier, the co-founder of SiliconANGLE, Wikibon, and theCUBE. We are here for an exclusive Cube conversations at the Alibaba Cloud conference here in Hangzhou, China. We're here with Dr. Wang, who's the chairman of the Alibaba Group Technology Committee as well as the founder of Alibaba Cloud, here in the new Museum of Inspiration at the event. Thanks for spending the time with me. >> Thank you for coming. >> So before we talk about Alibaba Cloud and all the goodness going on here at the conference, talk about this Museum of Inspiration. It is new, and it has kind of a display theme. You kind of walk through time. What was the motivation and the inspiration for the museum? >> Yeah, I think the keyword for the museum, inspiration, is really the inspiration that started the museum. I would say that there's two, really the artists thinking about that. The first thing is really about when people, people take a lot of things for granted. One of the goals for this museum, it just shows the people they probably see every day. But just let them, just, wow, okay, that's different from what I thought. I think a lot of people take for granted, but it's really a great invention, a great human contribution to the whole society. I think that one thing is really about that people understand why we got here today. So that's the first thing. The other thing is really about science and technology. When people are talking about science and technology, people often will say, whether we can combine science and technology. But I don't think that's the right way to describe the relationship between science and technology. I would say science and technology, really the two sides of the coin. I really want to see, let people to see two sides instead of mixing together and got one thing. So that's two things that's parallel, just like zero and one. They are two things. When they're put together in a computer, amazing things happen. If you mix the zero and the one, like half something, then it's just not that fun. So I really want to make sure it's the museum of science and art instead of the mixture of science and arts. So that's the one thing. The other thing is really about the inspiration of future. Most of the museum is really about the past, to show how we have in the past, and with less on the inspiration to help people to think about the future. This museum is really, when we think about everything over here, we did talk about the past, but we want to make sure people think about the future. That's the whole idea about the museum. >> And the computer industry is fairly young, if you go back to modern computing. But you kind of have a take here about how technology really is embedded in life. Talk more about that impact 'cause that seems to translate to the conference here at Alibaba, that technology isn't just about the speeds and the feeds, it's about the integration into life. >> Yeah, and I think that from this museum we can see actually I trace back the origin of all the technology. When people are talking about the computer technology, I really want to talk about the computing technology. And then we can trace back, see actually the human is the first signal computing device. Our Mother Nature created for us. If you look at the same things differently, you really can see the origin of that. I think in this museum we talk about two really original things. The first is about the nature origin of the Internet. When talking about Internet, people talk about our current technological infrastructure of Internet. When you look at the human history, how is when people walk, you create an Internet for Earth? You can see a lot of things can trace back. Then, with this kind of trace back, you can help us to think about what's going to happen next. The trace of the original idea is actually very important if you're thinking about technology. >> Talk about the story of Alibaba Cloud. That is not, It's new, Amazon has had it for around, early 2000's. But you guys came right after Amazon, 2009. Still young and growing. How does the Alibaba Cloud take the culture of this inspiration? What are some of the design principles of the Alibaba Cloud? >> Actually I would say the Alibaba Cloud is different from the Amazon Cloud. In the sense we have different vision about the future. Unfortunately though, we are put under the same umbrella called cloud computing by media, I will say that. So we are different, in the sense when the Amazon, actually I show great respect to Amazon. When Amazon started cloud computing, they are really talking about the utility. They're talking about how to cut the cost down. So basically, they start with the low cost of IT infrastructure. That's what I understand. When I started Alibaba Cloud, we know that actually cost is important for sure. But we know that actually the computing part is more important than the cost if you're thinking about the big data era. We started with thinking it's the acentric cloud computing. When you look at our first brochure and we put those words over there. That's almost nine years ago. We called it acentric cloud computing. Instead of the IT-centric cloud computing. This actually, it's not just an idea difference. It's actually, eventually, influenced of the underlying technology infrastructure. Our whole underlying technological infrastructure is designed for the data, instead of just for the IT deployment. >> Jack Ma was talking about this industrial revolution, this digital transformation. What strikes me is you guys have that same art and scientist dynamic, art and science coming together, reminds me of the Steve Jobs technology liberal arts thinking that spawns new creativity. Certainly the iPhone is a great example of that as one of the many things. But now the new generation is coming together. You have a big artist focus here at the event. Music festival, not just technology. How is that part of the focus at the event here? What does that mean for new developers? >> I think it's really the crossing behind that. If you're thinking about technology and now e-commerce, what's really the one thing behind that that's really changed the way of peoples' lives? Computing in that sense, computing is not just technology. It's really something that changes the way of life of every people. I think the e-commerce change the way of life of every people. In that sense, they are the same. If you look at the peoples' lives, they won't just live on technology. They won't just live on the arts. They need a life, love means everything. By nature, we have to make sure as consumers, they need something more than just one thing. I think we are very lucky we understand that. If you're thinking about the young people, I will give you a few numbers about this conference about young people. In China, we have a very specific word talking about the young people a couple of years ago. We call the 'badiho'. It basically means the generation born of the '80s. When people talk about 'jodiho', that basically means people born after '90s. And then people talking about the 'leniho' it's basically people born after 2000. I think that most of the visitors for this conference are 'leniho', 'jodiho', and 'badiho'. These are all young, all young people. >> The digital culture. >> It's a digital culture. I would rather use my own word in the book I would say instead of digital. For me, digital generation is already an old generation I would say. I would like to call this the online generation. They do everything online. Even the last generation do a lot of things digital because digital is everywhere. But I want to emphasize it's an online generation. They do everything online. >> Dr. Wang, talk about data. You mentioned that's the key ingredient, the fuel for innovation. That's impacting the city brain project you guys are doing. Talk about the city brain and the role of data and how that's impacting the societal users out there certainly here in China, the traffic is crowded. This is just an example of what else is out there. >> Okay. City brain actually it's, again it means different things based on the perspective. One thing that's probably important is the data. This is first time actually I think instead of using the big data, it's better to using what I call the data results. It's a better word than big data. I think the one fundamental thinking for the city brain is we find a human army. Humans finally realize actually that data results is the most precious resource for the city, instead of land and water supply. Because we already know that the land is limited. The water supply is limited. This is very important. It doesn't view data as a non-essential thing. It's just a part of your IT system. We finally realize that data is part of the city instead of part of your city IT system. I think it's a leap frog thinking, at least for me. When it got to that, and you realize that today all the existing IT systems cannot actually really embrace the data. IT system is just to support the people doing the work they used to do. And then you realize we need an infrastructure to really make the value from the data. Just like we have water supply for the city, then you can use the reservoir. Otherwise, the reservoir is useless for the city. I think city brain is just like a water supply system for the data. The city eventually can consume that. We start thinking it's a new infrastructure for the city just like water supply system, just like power grid, just like any way system. That's how we're thinking about it. This is the first thing. The reason we got to the traffic system is this is the problem every city has around the world. From my yesterday's presentation, I just joked about we build two roads for the city, which is too many. I was thinking a lot of people realize it. That's why Boston had the project. They want to get all the roads under the surface. Under surface. But it's still a road. It's still expensive. You know how much money they spend just to move all the roads. >> The big dig, I remember, that was the-- >> Yes, that's a big dig. I don't think that's, that's good for the transportation system, but I don't think that's the number one way for the growth of the city. I think probably most of the city don't have the money to do that. What the data city brain wants to do whether we can take the resource of data and we can optimize every aspect of the city so we can use less resource to support city growth. When we start with the traffic, it's just to make sure, you know that when we use the data to optimize the traffic lights, the idea behind that actually we use the data to optimize the time. How to just read the time. It's not just lights. And then if you're thinking, when we show the eventually, if you have enough data, then we can have less roads in the city but still got the same. >> So the Internet of Things is the hottest trend. 0bviously machine learning and artificial intelligence are part of that, and the cloud powers this new edge of the network, and the data has to flow. So the question that a lot of technologists who are architecting these solutions ask is how do you make the data go at a very low latency? That takes compute power. That takes a lot of technology. How does Alibaba Cloud think about the architecture? Obviously you have a strategic partner like Intel, Obviously with a lot of compute power. You got to think differently around making the data move. If it's like water, it needs to flow. So real time is really important, but self-driving cars, real time is down to the millisecond, nanosecond. How do you think about that as a technologist? >> I think the, if you go back to the Internet of things, I think it's still the Internet. I would say eventually, if you're thinking about the word cloud computing and people use edge computing and people talking about Internet of things. For me, it's just the computing of the Internet. Cloud computing is the computing of the Internet and edge computing is computing on the Internet. Even the IoT is the computing of the Internet. If you're talking about the data, I think eventually it's really about the data on the Internet. It's not data on the sensor. It's not data on the cloud. Basically it's data on the Internet. I would expect eventually the Internet infrastructure will be improved significantly. It's not an improved cloud. It's not improved edge computing. Or it's improvement of the IoT. But it's really, >> Together. >> it's together. >> So Intel, I was covering them, Mobile World Congress earlier in the year. And obviously five G. You need the mobile overlay, that's super important. You also have the end-to-end inside the cloud. Obviously Intel is a strategic partner. Can you talk about the relationship you have with Intel? And also your philosophy, technically speaking, with the ecosystem? Because it's not just Intel, it's everybody. There's a lot of people here at this event. American companies as well as international companies who are now going to be part of your ecosystem. >> Actually the, we certainly have a very good relationship with Intel. I think we share in some sense the same vision. I think that the number one thing is really about people learning about how important the computing is. For me, the Intel is not that, a chip selling company. Intel is really the provider of computing power. That's what I understand. And we can expect eventually the whole ecosystem is really about who is going to provide the computing power. Who is going to provide the infrastructure to make the data? Instead of just equipment supply, eventually the need for computing, and the need for data, will be the challenge for every company, including Alibaba Cloud. We are not, we are not immune from these challenges. We will feel the same challenge. What we want to do is really make sure that with all these partners, provide enough computing for the next 10 or 20 years. We want to make sure that there's enough data flow for the next 10 years. In that sense, it's not the traditional ecosystem as like you do this and you do that. It's basically how we can work together to really make sure we have the challenge for the data and computing in the next 10 years. >> Yesterday we covered the news that you guys announced 15, building and R&D over the next three years, which is a lot of money. Also it has a very international and global view. Academics with younger folks. Alibaba Cloud is going to be a part of that, I'm assuming. I'd love to get your thoughts on how you see that intersecting. But the question for you is the cloud world today is moving at very, very fast speed. We're seeing Amazon, for instance, has been the best in terms of new announcements every year. Not one or two, like a ton of announcements, a lot. How are you guys going to continue to keep the pace? To move faster because the city brain is a great project, but it's going to have more evolution. It's going to move fast. How are you guys keeping up with the pace? >> I think the only way, that's not just for the next 10 years. Actually when I started Alibaba Cloud, we take the same philosophy. Actually the user moves very fast than us. If you look at the users in China they move very fast probably than anywhere else around the world. If you use the city brain project, I would say city brain project is basically tell the people, we need the computing power more than any other task. You really can see that. People want you. If you can't satisfy their demand, then somebody else is going to do that. It's not something we want to move fast but >> You have to move fast. >> You have to move fast. That's why the China is special. I want to say China is not just a place for the market. China is the place that pushes you to move faster. That's more important than market size. >> You mentioned data technology and information technology kind of transferring to a new world. Software is also a big part of it. Software you have to compute, obviously with Intel and the relationships you have. But software is growing exponentially. Certainly in open source, we see Cloud Native Foundation here. They'll probably have Linux foundation. Open source is going to grow exponentially. Most of the code will be shipping. But you have more data growing exponentially. Software is eating the world, but data is eating software. That means data is greater than software. If you look at it that way, that's super important. As the new architects, you and I were just talking about how we've in the industry for a while. You certainly have an amazing career from Microsoft now at Alibaba. A new generation of architects and developers are going to create new innovations around this dynamic of data. What's your advice and how do you view that if you are 21 years old again right now and you were going to jump into studies and academic and or field. It's a whole new world. >> I think there's probably two suggestions. Not necessarily for the young generation, but I would say it's just a suggestion for the young generation to push that habit. The first thing you mentioned about the data eats software. Well, I would put it in a different perspective. I would say for the last generation, the last two or three generations, I would say the computer era, we are really talking about the computer software. That's pretty much in everything. For this generation, I would say we are talking about computing plus the data. That box is not important, but the computing power is more important. For the computing era, the box is important. >> There's no box. It's the world, it's the cloud. >> That's one thing. The implication for this, I want the young generation to push is, then we need the new infrastructure. Thinking about the build as a great vision, got to have the computer in every home. That's infrastructure. Today when you are in the computing process data era, the infrastructure is not there. I think the vision for the Alibaba Cloud is make sure that we have this infrastructure for the next 10 or 20 years so the young generation can take advantage of that and to do that innovation and inventions, just like computing in every home. >> That's very important. I think that also speaks to businesses, how enterprises, I remember my first start up, I had to buy all this equipment and put it into the telephone closet. Now, start ups and small businesses don't need IT departments. This has been a big growth area certainly for Alibaba Cloud. But now all businesses might have a small closet, not a big data center. This is going to change the nature of business. So work and play are coming together. This speaks to the Museum of Inspiration theme here where you can have work and play kind of integrate but yet still be separate in that analog digital world. What's your vision on this new dimension of everything doesn't have to be just digital? You can have an analog life and mix it with digital. >> Actually I was always sad. It's not, the world never has just one side. It always has two sides. The difference is which side is important at a particular time. Just like when people talk about digital and analog, the analog will exist forever. It's hard for you to kill. The question is whether you can find the most beauty from the digital at the same time you can most beautiful part of the analog. I would say that the people, just like when talking about software, people still loved the hardware. And people still loved the touch. The digital has to make sure it looks good. Will it work versus it looks good? I would say we want to make sure people live in a world with two sides, instead of just giving them one side of the world. >> You mentioned people still love hardware. I always say, a car drives but there's still an engine, and people like to understand the engine. There's a maker culture in the United States that's been growing over the past two decades. And now even more accelerated is the maker culture because of the edge and how technology has become part of the fabric of life. How do you see that maker culture being enabled by more cloud services? Because anyone can make a skateboard or motorcycle or a computer or a device now. Powering that with the cloud is an opportunity. How do you view that? >> I would say that eventually, if we have the broad definition of a cloud, I would say eventually, everything the maker makes will be part of the cloud. When talking about clouds, we're really talking about Internet, so every hardware, every piece of hardware will be part of Internet. I would say, if you look at the evolution of the Internet, Internet, it's just a backbone at the very beginning. Actually the first revolution the Internet made is really to make sure that every piece of software is a part of Internet. That's how we got the world wide web. I would say when talking about the maker culture, I would say eventually that every piece of hardware will be part of Internet. So Internet won't be complete without the hardware. In that sense, the cloud is a really essential part of that. >> There's some really interesting things happening here in China that I'm excited about. One of them is the nature of the user base and how close you guys are to that. In the US a similar scale but it's kind of spread over a bunch of other cloud providers. But the interesting phenomenon as data grows exponentially, as software grows exponentially in open source, things are becoming more decentralized. Without talking about the whole initial coin offerings, I know China has banned it and Russia's going to ban it. Other countries are putting a clamp down on crypto currency. Putting that aside, there's still blockchain as a potential disruptive enabler. You're seeing decentralization becoming a new architecture dynamic because you have to support the growth of these devices at the edge. Distributive computing has been around for a while, but now a decentralized architecture dynamic exists. How do you steer that technology direction? >> You have to separate from the the distributive architecture versus its physical location. I would say I like the blockchain idea very much. I think eventually it would be part of the Internet. It's not just something that sits on top of the Internet. It would be very fundamental, just like TCP and IP. This is low level, so this would be part of the Internet instead of standing on top of the Internet. Eventually, in that sense, Internet would be very distributed. By thinking that it's nothing, there's no decentralization exists. You still need, even though physically, it's in one place. >> It's almost decentralized, not 100 percent. >> Yeah, yeah. Obviously this would be different. Without Internet, without new software, that basically, just like PC. PC is really in a single box, and we use all software in a box. We distribute architecture. We could have decentralized, but everything actually is distributed. You still cannot trace that. You put like a meeting. A service in a data center. It's actually distributed over this one meeting service. In that sense, it's completely distributed. >> That server list too is a big trend where if you talk about the edge of the network, you got to move compute to the data sometimes. Or have compute on the edge. So this is going to be continued growth, you see that as well right? >> Yes, but I still think, if you use Silicon as a measure for this computing power, I would say if you can see there's more silicon on the edge, but I would say when we put one silicon on the edge, you probably have to put 100 silicons on the cloud. It's still kind of-- >> It's a relationship. >> It's a relationship, just like our body is very important but the brain consumes the most oxygen. >> It's important what's in the cloud then. You got to have the computing, have those ratios. It depends on the architecture. >> Yes, yes. >> Final question for you is as the folks in Silicon Valley, where we're based, and Palo Alto want to know is Alibaba, what it means to them? If you have a chance to say a few things about what Alibaba Cloud is to America, what would you like to say? >> I would say that actually they would just put the cloud computing aside. Just look at what it really means behind that. I think the cloud, we do have an understanding of what the cloud computing really means. At the very beginning actually, I wouldn't call the company a cloud computing company. I would call it a general computing company. It's really a fraction of what's thinking in China. Again, my comment is not just to view China as the market to sell your product. To view China as the place to inspire having a new product. >> And it's a global world now, the world is flat. >> Yes, just like United States, it's not, it's a place inspired. All the people around the world together to have a new idea. I think the people in China just love new things. They love to try new things. It really can shoot your size of your innovation. >> And it's a global collaboration, it's interesting. That phenomenon is going to continue. You've done amazing work here. Congratulations on the Museum of Inspiration and the projects you're working on. Personal question for you. What are you excited about now? We kind of joke about how old we are now, but the young people certainly have a great future ahead of them. But you have a lot of experience and you're steering Alibaba's technology committee across the group as well as being the founder of the cloud. What are you excited about right now, technically speaking? What's the big, or just impact? What's the big wave that you like? >> I think it's very exciting in a couple of things, three things I would say. The first is really about just look at technology itself. Just like when I described my book, it's really, really exciting in your life if you can see the Internet plus the computing and plus data, cause they're together. Just like you have this engine, you have the airplane, a couple of things, they're together wherever. This is a very, very exciting era. This is not just about a technology era. It's an era that all things happen at the same time, so that's very exciting. That's one thing. The second thing as you read about the city around over here, I think the the Alibaba the Hanzo, it's just a very special for Alibaba, but I think it's special for the other company as well. So this place is very special. Just to give you an idea where you are, this area has the most networked river in the past. If you look at the map, it's like Internet. I would say, all the people over here, just their mindset. It's just on an Internet mindset. Even goes back 100, 200 years ago because the river is the only way for them to travel, for the communications-- >> That's the data back then. >> That's exactly my point, see. If you look at the map, so this is very exciting. The other thing about that the Alibaba, for me, the Alibaba you know Alibaba, we have a very broad opinions. You can feel that. From a technology point of view, that basically means it's the place you can touch every aspect of technology. You have a very slight, very-- >> You have a great surface area aperture to look at impact of life. >> So you think about these three things together. It's hard to say the, you better get excited. >> It's a great time to be in technology, isn't it? Entertainment, e-commerce, web services. >> For me, when I work on the city brain project, it's just the beginning of machine learning. A lot of people, they are fighting for like, when people talk about speech recognition, they are fighting for the last one meter for the speech recognition. But if you're talking about city brain, it's the world. The most big AI project. And it's just the beginning. We just start with the one percent. >> It must be a lot of fun. You got a lot of data to work with. You have real life integration. It's super exciting. When are we going to see you in Silicon Valley? >> I appear regularly to Silicon Valley two or three times every year. We'll probably see sometime early next year. >> Thank you very much for the time, appreciate it. >> Thank you for coming to the conference and coming to the museum. >> Thank you very much for your inspiration. >> Thank you. >> Thank you.

>> SiliconANGLE Media presents ... theCUBE! Covering AlibabaCloud's annual conference. Brought to you by Intel. Now, here's John Furrier... >> Hello everyone, I'm John Furrier, the co-founder of SiliconANGLE, Wikibon, and theCUBE. We are here for an exclusive Cube conversations at the Alibaba Cloud conference here in Hangzhou, China. We're here with Dr. Wang, who's the chairman of the Alibaba Group Technology Committee as well as the founder of Alibaba Cloud, here in the new Museum of Inspiration at the event. Thanks for spending the time with me. >> Thank you for coming. >> So before we talk about Alibaba Cloud and all the goodness going on here at the conference, talk about this Museum of Inspiration. It is new, and it has kind of a display theme. You kind of walk through time. What was the motivation and the inspiration for the museum? >> Yeah, I think the keyword for the museum, inspiration, is really the inspiration that started the museum. I would say that there's two, really the artists thinking about that. The first thing is really about when people, people take a lot of things for granted. One of the goals for this museum, it just shows the people they probably see every day. But just let them, just, wow, okay, that's different from what I thought. I think a lot of people take for granted, but it's really a great invention, a great human contribution to the whole society. I think that one thing is really about that people understand why we got here today. So that's the first thing. The other thing is really about science and technology. When people are talking about science and technology, people often will say, whether we can combine science and technology. But I don't think that's the right way to describe the relationship between science and technology. I would say science and technology, really the two sides of the coin. I really want to see, let people to see two sides instead of mixing together and got one thing. So that's two things that's parallel, just like zero and one. They are two things. When they're put together in a computer, amazing things happen. If you mix the zero and the one, like half something, then it's just not that fun. So I really want to make sure it's the museum of science and art instead of the mixture of science and arts. So that's the one thing. The other thing is really about the inspiration of future. Most of the museum is really about the past, to show how we have in the past, and with less on the inspiration to help people to think about the future. This museum is really, when we think about everything over here, we did talk about the past, but we want to make sure people think about the future. That's the whole idea about the museum. >> And the computer industry is fairly young, if you go back to modern computing. But you kind of have a take here about how technology really is embedded in life. Talk more about that impact 'cause that seems to translate to the conference here at Alibaba, that technology isn't just about the speeds and the feeds, it's about the integration into life. >> Yeah, and I think that from this museum we can see actually I trace back the origin of all the technology. When people are talking about the computer technology, I really want to talk about the computing technology. And then we can trace back, see actually the human is the first signal computing device. Our Mother Nature created for us. If you look at the same things differently, you really can see the origin of that. I think in this museum we talk about two really original things. The first is about the nature origin of the Internet. When talking about Internet, people talk about our current technological infrastructure of Internet. When you look at the human history, how is when people walk, you create an Internet for Earth? You can see a lot of things can trace back. Then, with this kind of trace back, you can help us to think about what's going to happen next. The trace of the original idea is actually very important if you're thinking about technology. >> Talk about the story of Alibaba Cloud. That is not, It's new, Amazon has had it for around, early 2000's. But you guys came right after Amazon, 2009. Still young and growing. How does the Alibaba Cloud take the culture of this inspiration? What are some of the design principles of the Alibaba Cloud? >> Actually I would say the Alibaba Cloud is different from the Amazon Cloud. In the sense we have different vision about the future. Unfortunately though, we are put under the same umbrella called cloud computing by media, I will say that. So we are different, in the sense when the Amazon, actually I show great respect to Amazon. When Amazon started cloud computing, they are really talking about the utility. They're talking about how to cut the cost down. So basically, they start with the low cost of IT infrastructure. That's what I understand. When I started Alibaba Cloud, we know that actually cost is important for sure. But we know that actually the computing part is more important than the cost if you're thinking about the big data era. We started with thinking it's the acentric cloud computing. When you look at our first brochure and we put those words over there. That's almost nine years ago. We called it acentric cloud computing. Instead of the IT-centric cloud computing. This actually, it's not just an idea difference. It's actually, eventually, influenced of the underlying technology infrastructure. Our whole underlying technological infrastructure is designed for the data, instead of just for the IT deployment. >> Jack Ma was talking about this industrial revolution, this digital transformation. What strikes me is you guys have that same art and scientist dynamic, art and science coming together, reminds me of the Steve Jobs technology liberal arts thinking that spawns new creativity. Certainly the iPhone is a great example of that as one of the many things. But now the new generation is coming together. You have a big artist focus here at the event. Music festival, not just technology. How is that part of the focus at the event here? What does that mean for new developers? >> I think it's really the crossing behind that. If you're thinking about technology and now e-commerce, what's really the one thing behind that that's really changed the way of peoples' lives? Computing in that sense, computing is not just technology. It's really something that changes the way of life of every people. I think the e-commerce change the way of life of every people. In that sense, they are the same. If you look at the peoples' lives, they won't just live on technology. They won't just live on the arts. They need a life, love means everything. By nature, we have to make sure as consumers, they need something more than just one thing. I think we are very lucky we understand that. If you're thinking about the young people, I will give you a few numbers about this conference about young people. In China, we have a very specific word talking about the young people a couple of years ago. We call the 'badiho'. It basically means the generation born of the '80s. When people talk about 'jodiho', that basically means people born after '90s. And then people talking about the 'leniho' it's basically people born after 2000. I think that most of the visitors for this conference are 'leniho', 'jodiho', and 'badiho'. These are all young, all young people. >> The digital culture. >> It's a digital culture. I would rather use my own word in the book I would say instead of digital. For me, digital generation is already an old generation I would say. I would like to call this the online generation. They do everything online. Even the last generation do a lot of things digital because digital is everywhere. But I want to emphasize it's an online generation. They do everything online. >> Dr. Wang, talk about data. You mentioned that's the key ingredient, the fuel for innovation. That's impacting the city brain project you guys are doing. Talk about the city brain and the role of data and how that's impacting the societal users out there certainly here in China, the traffic is crowded. This is just an example of what else is out there. >> Okay. City brain actually it's, again it means different things based on the perspective. One thing that's probably important is the data. This is first time actually I think instead of using the big data, it's better to using what I call the data results. It's a better word than big data. I think the one fundamental thinking for the city brain is we find a human army. Humans finally realize actually that data results is the most precious resource for the city, instead of land and water supply. Because we already know that the land is limited. The water supply is limited. This is very important. It doesn't view data as a non-essential thing. It's just a part of your IT system. We finally realize that data is part of the city instead of part of your city IT system. I think it's a leap frog thinking, at least for me. When it got to that, and you realize that today all the existing IT systems cannot actually really embrace the data. IT system is just to support the people doing the work they used to do. And then you realize we need an infrastructure to really make the value from the data. Just like we have water supply for the city, then you can use the reservoir. Otherwise, the reservoir is useless for the city. I think city brain is just like a water supply system for the data. The city eventually can consume that. We start thinking it's a new infrastructure for the city just like water supply system, just like power grid, just like any way system. That's how we're thinking about it. This is the first thing. The reason we got to the traffic system is this is the problem every city has around the world. From my yesterday's presentation, I just joked about we build two roads for the city, which is too many. I was thinking a lot of people realize it. That's why Boston had the project. They want to get all the roads under the surface. Under surface. But it's still a road. It's still expensive. You know how much money they spend just to move all the roads. >> The big dig, I remember, that was the-- >> Yes, that's a big dig. I don't think that's, that's good for the transportation system, but I don't think that's the number one way for the growth of the city. I think probably most of the city don't have the money to do that. What the data city brain wants to do whether we can take the resource of data and we can optimize every aspect of the city so we can use less resource to support city growth. When we start with the traffic, it's just to make sure, you know that when we use the data to optimize the traffic lights, the idea behind that actually we use the data to optimize the time. How to just read the time. It's not just lights. And then if you're thinking, when we show the eventually, if you have enough data, then we can have less roads in the city but still got the same. >> So the Internet of Things is the hottest trend. 0bviously machine learning and artificial intelligence are part of that, and the cloud powers this new edge of the network, and the data has to flow. So the question that a lot of technologists who are architecting these solutions ask is how do you make the data go at a very low latency? That takes compute power. That takes a lot of technology. How does Alibaba Cloud think about the architecture? Obviously you have a strategic partner like Intel, Obviously with a lot of compute power. You got to think differently around making the data move. If it's like water, it needs to flow. So real time is really important, but self-driving cars, real time is down to the millisecond, nanosecond. How do you think about that as a technologist? >> I think the, if you go back to the Internet of things, I think it's still the Internet. I would say eventually, if you're thinking about the word cloud computing and people use edge computing and people talking about Internet of things. For me, it's just the computing of the Internet. Cloud computing is the computing of the Internet and edge computing is computing on the Internet. Even the IoT is the computing of the Internet. If you're talking about the data, I think eventually it's really about the data on the Internet. It's not data on the sensor. It's not data on the cloud. Basically it's data on the Internet. I would expect eventually the Internet infrastructure will be improved significantly. It's not an improved cloud. It's not improved edge computing. Or it's improvement of the IoT. But it's really, >> Together. >> it's together. >> So Intel, I was covering them, Mobile World Congress earlier in the year. And obviously five G. You need the mobile overlay, that's super important. You also have the end-to-end inside the cloud. Obviously Intel is a strategic partner. Can you talk about the relationship you have with Intel? And also your philosophy, technically speaking, with the ecosystem? Because it's not just Intel, it's everybody. There's a lot of people here at this event. American companies as well as international companies who are now going to be part of your ecosystem. >> Actually the, we certainly have a very good relationship with Intel. I think we share in some sense the same vision. I think that the number one thing is really about people learning about how important the computing is. For me, the Intel is not that, a chip selling company. Intel is really the provider of computing power. That's what I understand. And we can expect eventually the whole ecosystem is really about who is going to provide the computing power. Who is going to provide the infrastructure to make the data? Instead of just equipment supply, eventually the need for computing, and the need for data, will be the challenge for every company, including Alibaba Cloud. We are not, we are not immune from these challenges. We will feel the same challenge. What we want to do is really make sure that with all these partners, provide enough computing for the next 10 or 20 years. We want to make sure that there's enough data flow for the next 10 years. In that sense, it's not the traditional ecosystem as like you do this and you do that. It's basically how we can work together to really make sure we have the challenge for the data and computing in the next 10 years. >> Yesterday we covered the news that you guys announced 15, building and R&D over the next three years, which is a lot of money. Also it has a very international and global view. Academics with younger folks. Alibaba Cloud is going to be a part of that, I'm assuming. I'd love to get your thoughts on how you see that intersecting. But the question for you is the cloud world today is moving at very, very fast speed. We're seeing Amazon, for instance, has been the best in terms of new announcements every year. Not one or two, like a ton of announcements, a lot. How are you guys going to continue to keep the pace? To move faster because the city brain is a great project, but it's going to have more evolution. It's going to move fast. How are you guys keeping up with the pace? >> I think the only way, that's not just for the next 10 years. Actually when I started Alibaba Cloud, we take the same philosophy. Actually the user moves very fast than us. If you look at the users in China they move very fast probably than anywhere else around the world. If you use the city brain project, I would say city brain project is basically tell the people, we need the computing power more than any other task. You really can see that. People want you. If you can't satisfy their demand, then somebody else is going to do that. It's not something we want to move fast but >> You have to move fast. >> You have to move fast. That's why the China is special. I want to say China is not just a place for the market. China is the place that pushes you to move faster. That's more important than market size. >> You mentioned data technology and information technology kind of transferring to a new world. Software is also a big part of it. Software you have to compute, obviously with Intel and the relationships you have. But software is growing exponentially. Certainly in open source, we see Cloud Native Foundation here. They'll probably have Linux foundation. Open source is going to grow exponentially. Most of the code will be shipping. But you have more data growing exponentially. Software is eating the world, but data is eating software. That means data is greater than software. If you look at it that way, that's super important. As the new architects, you and I were just talking about how we've in the industry for a while. You certainly have an amazing career from Microsoft now at Alibaba. A new generation of architects and developers are going to create new innovations around this dynamic of data. What's your advice and how do you view that if you are 21 years old again right now and you were going to jump into studies and academic and or field. It's a whole new world. >> I think there's probably two suggestions. Not necessarily for the young generation, but I would say it's just a suggestion for the young generation to push that habit. The first thing you mentioned about the data eats software. Well, I would put it in a different perspective. I would say for the last generation, the last two or three generations, I would say the computer era, we are really talking about the computer software. That's pretty much in everything. For this generation, I would say we are talking about computing plus the data. That box is not important, but the computing power is more important. For the computing era, the box is important. >> There's no box. It's the world, it's the cloud. >> That's one thing. The implication for this, I want the young generation to push is, then we need the new infrastructure. Thinking about the build as a great vision, got to have the computer in every home. That's infrastructure. Today when you are in the computing process data era, the infrastructure is not there. I think the vision for the Alibaba Cloud is make sure that we have this infrastructure for the next 10 or 20 years so the young generation can take advantage of that and to do that innovation and inventions, just like computing in every home. >> That's very important. I think that also speaks to businesses, how enterprises, I remember my first start up, I had to buy all this equipment and put it into the telephone closet. Now, start ups and small businesses don't need IT departments. This has been a big growth area certainly for Alibaba Cloud. But now all businesses might have a small closet, not a big data center. This is going to change the nature of business. So work and play are coming together. This speaks to the Museum of Inspiration theme here where you can have work and play kind of integrate but yet still be separate in that analog digital world. What's your vision on this new dimension of everything doesn't have to be just digital? You can have an analog life and mix it with digital. >> Actually I was always sad. It's not, the world never has just one side. It always has two sides. The difference is which side is important at a particular time. Just like when people talk about digital and analog, the analog will exist forever. It's hard for you to kill. The question is whether you can find the most beauty from the digital at the same time you can most beautiful part of the analog. I would say that the people, just like when talking about software, people still loved the hardware. And people still loved the touch. The digital has to make sure it looks good. Will it work versus it looks good? I would say we want to make sure people live in a world with two sides, instead of just giving them one side of the world. >> You mentioned people still love hardware. I always say, a car drives but there's still an engine, and people like to understand the engine. There's a maker culture in the United States that's been growing over the past two decades. And now even more accelerated is the maker culture because of the edge and how technology has become part of the fabric of life. How do you see that maker culture being enabled by more cloud services? Because anyone can make a skateboard or motorcycle or a computer or a device now. Powering that with the cloud is an opportunity. How do you view that? >> I would say that eventually, if we have the broad definition of a cloud, I would say eventually, everything the maker makes will be part of the cloud. When talking about clouds, we're really talking about Internet, so every hardware, every piece of hardware will be part of Internet. I would say, if you look at the evolution of the Internet, Internet, it's just a backbone at the very beginning. Actually the first revolution the Internet made is really to make sure that every piece of software is a part of Internet. That's how we got the world wide web. I would say when talking about the maker culture, I would say eventually that every piece of hardware will be part of Internet. So Internet won't be complete without the hardware. In that sense, the cloud is a really essential part of that. >> There's some really interesting things happening here in China that I'm excited about. One of them is the nature of the user base and how close you guys are to that. In the US a similar scale but it's kind of spread over a bunch of other cloud providers. But the interesting phenomenon as data grows exponentially, as software grows exponentially in open source, things are becoming more decentralized. Without talking about the whole initial coin offerings, I know China has banned it and Russia's going to ban it. Other countries are putting a clamp down on crypto currency. Putting that aside, there's still blockchain as a potential disruptive enabler. You're seeing decentralization becoming a new architecture dynamic because you have to support the growth of these devices at the edge. Distributive computing has been around for a while, but now a decentralized architecture dynamic exists. How do you steer that technology direction? >> You have to separate from the the distributive architecture versus its physical location. I would say I like the blockchain idea very much. I think eventually it would be part of the Internet. It's not just something that sits on top of the Internet. It would be very fundamental, just like TCP and IP. This is low level, so this would be part of the Internet instead of standing on top of the Internet. Eventually, in that sense, Internet would be very distributed. By thinking that it's nothing, there's no decentralization exists. You still need, even though physically, it's in one place. >> It's almost decentralized, not 100 percent. >> Yeah, yeah. Obviously this would be different. Without Internet, without new software, that basically, just like PC. PC is really in a single box, and we use all software in a box. We distribute architecture. We could have decentralized, but everything actually is distributed. You still cannot trace that. You put like a meeting. A service in a data center. It's actually distributed over this one meeting service. In that sense, it's completely distributed. >> That server list too is a big trend where if you talk about the edge of the network, you got to move compute to the data sometimes. Or have compute on the edge. So this is going to be continued growth, you see that as well right? >> Yes, but I still think, if you use Silicon as a measure for this computing power, I would say if you can see there's more silicon on the edge, but I would say when we put one silicon on the edge, you probably have to put 100 silicons on the cloud. It's still kind of-- >> It's a relationship. >> It's a relationship, just like our body is very important but the brain consumes the most oxygen. >> It's important what's in the cloud then. You got to have the computing, have those ratios. It depends on the architecture. >> Yes, yes. >> Final question for you is as the folks in Silicon Valley, where we're based, and Palo Alto want to know is Alibaba, what it means to them? If you have a chance to say a few things about what Alibaba Cloud is to America, what would you like to say? >> I would say that actually they would just put the cloud computing aside. Just look at what it really means behind that. I think the cloud, we do have an understanding of what the cloud computing really means. At the very beginning actually, I wouldn't call the company a cloud computing company. I would call it a general computing company. It's really a fraction of what's thinking in China. Again, my comment is not just to view China as the market to sell your product. To view China as the place to inspire having a new product. >> And it's a global world now, the world is flat. >> Yes, just like United States, it's not, it's a place inspired. All the people around the world together to have a new idea. I think the people in China just love new things. They love to try new things. It really can shoot your size of your innovation. >> And it's a global collaboration, it's interesting. That phenomenon is going to continue. You've done amazing work here. Congratulations on the Museum of Inspiration and the projects you're working on. Personal question for you. What are you excited about now? We kind of joke about how old we are now, but the young people certainly have a great future ahead of them. But you have a lot of experience and you're steering Alibaba's technology committee across the group as well as being the founder of the cloud. What are you excited about right now, technically speaking? What's the big, or just impact? What's the big wave that you like? >> I think it's very exciting in a couple of things, three things I would say. The first is really about just look at technology itself. Just like when I described my book, it's really, really exciting in your life if you can see the Internet plus the computing and plus data, cause they're together. Just like you have this engine, you have the airplane, a couple of things, they're together wherever. This is a very, very exciting era. This is not just about a technology era. It's an era that all things happen at the same time, so that's very exciting. That's one thing. The second thing as you read about the city around over here, I think the the Alibaba the Hanzo, it's just a very special for Alibaba, but I think it's special for the other company as well. So this place is very special. Just to give you an idea where you are, this area has the most networked river in the past. If you look at the map, it's like Internet. I would say, all the people over here, just their mindset. It's just on an Internet mindset. Even goes back 100, 200 years ago because the river is the only way for them to travel, for the communications-- >> That's the data back then. >> That's exactly my point, see. If you look at the map, so this is very exciting. The other thing about that the Alibaba, for me, the Alibaba you know Alibaba, we have a very broad opinions. You can feel that. From a technology point of view, that basically means it's the place you can touch every aspect of technology. You have a very slight, very-- >> You have a great surface area aperture to look at impact of life. >> So you think about these three things together. It's hard to say the, you better get excited. >> It's a great time to be in technology, isn't it? Entertainment, e-commerce, web services. >> For me, when I work on the city brain project, it's just the beginning of machine learning. A lot of people, they are fighting for like, when people talk about speech recognition, they are fighting for the last one meter for the speech recognition. But if you're talking about city brain, it's the world. The most big AI project. And it's just the beginning. We just start with the one percent. >> It must be a lot of fun. You got a lot of data to work with. You have real life integration. It's super exciting. When are we going to see you in Silicon Valley? >> I appear regularly to Silicon Valley two or three times every year. We'll probably see sometime early next year. >> Thank you very much for the time, appreciate it. >> Thank you for coming to the conference and coming to the museum. >> Thank you very much for your inspiration. >> Thank you. >> Thank you.

(soothing music) >> Hey everyone, welcome to this event, "Build Your Cloud Center of Excellence." I'm your host, Lisa Martin. In the next 15 minutes or so my guest and I are going to be talking about redefining cloud operations, an application modernization for customers, and specifically how partners are helping to speed up that process. As you saw on our first two segments, we talked about problems enterprises are facing with cloud operations. We talked about redefining cloud operations as well to solve these problems. This segment is going to be focusing on how Hitachi Vantara's partners are really helping to speed up that process. We've got Johnson Controls here to talk about their partnership with Hitachi Vantara. Please welcome both of my guests, Prem Balasubramanian is with us, SVP and CTO Digital Solutions at Hitachi Vantara. And Suresh Mothikuru, SVP Customer Success Platform Engineering and Reliability Engineering from Johnson Controls. Gentlemen, welcome to the program, great to have you. >> Thank. >> Thank you, Lisa. >> First question is to both of you and Suresh, we'll start with you. We want to understand, you know, the cloud operations landscape is increasingly complex. We've talked a lot about that in this program. Talk to us, Suresh, about some of the biggest challenges and pin points that you faced with respect to that. >> Thank you. I think it's a great question. I mean, cloud has evolved a lot in the last 10 years. You know, when we were talking about a single cloud whether it's Azure or AWS and GCP, and that was complex enough. Now we are talking about multi-cloud and hybrid and you look at Johnson Controls, we have Azure we have AWS, we have GCP, we have Alibaba and we also support on-prem. So the architecture has become very, very complex and the complexity has grown so much that we are now thinking about whether we should be cloud native or cloud agnostic. So I think, I mean, sometimes it's hard to even explain the complexity because people think, oh, "When you go to cloud, everything is simplified." Cloud does give you a lot of simplicity, but it also really brings a lot more complexity along with it. So, and then next one is pretty important is, you know, generally when you look at cloud services, you have plenty of services that are offered within a cloud, 100, 150 services, 200 services. Even within those companies, you take AWS they might not know, an individual resource might not know about all the services we see. That's a big challenge for us as a customer to really understand each of the service that is provided in these, you know, clouds, well, doesn't matter which one that is. And the third one is pretty big, at least at the CTO the CIO, and the senior leadership level, is cost. Cost is a major factor because cloud, you know, will eat you up if you cannot manage it. If you don't have a good cloud governance process it because every minute you are in it, it's burning cash. So I think if you ask me, these are the three major things that I am facing day to day and that's where I use my partners, which I'll touch base down the line. >> Perfect, we'll talk about that. So Prem, I imagine that these problems are not unique to Johnson Controls or JCI, as you may hear us refer to it. Talk to me Prem about some of the other challenges that you're seeing within the customer landscape. >> So, yeah, I agree, Lisa, these are not very specific to JCI, but there are specific issues in JCI, right? So the way we think about these are, there is a common issue when people go to the cloud and there are very specific and unique issues for businesses, right? So JCI, and we will talk about this in the episode as we move forward. I think Suresh and his team have done some phenomenal step around how to manage this complexity. But there are customers who have a lesser complex cloud which is, they don't go to Alibaba, they don't have footprint in all three clouds. So their multi-cloud footprint could be a bit more manageable, but still struggle with a lot of the same problems around cost, around security, around talent. Talent is a big thing, right? And in Suresh's case I think it's slightly more exasperated because every cloud provider Be it AWS, JCP, or Azure brings in hundreds of services and there is nobody, including many of us, right? We learn every day, nowadays, right? It's not that there is one service integrator who knows all, while technically people can claim as a part of sales. But in reality all of us are continuing to learn in this landscape. And if you put all of this equation together with multiple clouds the complexity just starts to exponentially grow. And that's exactly what I think JCI is experiencing and Suresh's team has been experiencing, and we've been working together. But the common problems are around security talent and cost management of this, right? Those are my three things. And one last thing that I would love to say before we move away from this question is, if you think about cloud operations as a concept that's evolving over the last few years, and I have touched upon this in the previous episode as well, Lisa, right? If you take architectures, we've gone into microservices, we've gone into all these server-less architectures all the fancy things that we want. That helps us go to market faster, be more competent to as a business. But that's not simplified stuff, right? That's complicated stuff. It's a lot more distributed. Second, again, we've advanced and created more modern infrastructure because all of what we are talking is platform as a service, services on the cloud that we are consuming, right? In the same case with development we've moved into a DevOps model. We kind of click a button put some code in a repository, the code starts to run in production within a minute, everything else is automated. But then when we get to operations we are still stuck in a very old way of looking at cloud as an infrastructure, right? So you've got an infra team, you've got an app team, you've got an incident management team, you've got a soft knock, everything. But again, so Suresh can talk about this more because they are making significant strides in thinking about this as a single workload, and how do I apply engineering to go manage this? Because a lot of it is codified, right? So automation. Anyway, so that's kind of where the complexity is and how we are thinking, including JCI as a partner thinking about taming that complexity as we move forward. >> Suresh, let's talk about that taming the complexity. You guys have both done a great job of articulating the ostensible challenges that are there with cloud, especially multi-cloud environments that you're living in. But Suresh, talk about the partnership with Hitachi Vantara. How is it helping to dial down some of those inherent complexities? >> I mean, I always, you know, I think I've said this to Prem multiple times. I treat my partners as my internal, you know, employees. I look at Prem as my coworker or my peers. So the reason for that is I want Prem to have the same vested interest as a partner in my success or JCI success and vice versa, isn't it? I think that's how we operate and that's how we have been operating. And I think I would like to thank Prem and Hitachi Vantara for that really been an amazing partnership. And as he was saying, we have taken a completely holistic approach to how we want to really be in the market and play in the market to our customers. So if you look at my jacket it talks about OpenBlue platform. This is what JCI is building, that we are building this OpenBlue digital platform. And within that, my team, along with Prem's or Hitachi's, we have built what we call as Polaris. It's a technical platform where our apps can run. And this platform is automated end-to-end from a platform engineering standpoint. We stood up a platform engineering organization, a reliability engineering organization, as well as a support organization where Hitachi played a role. As I said previously, you know, for me to scale I'm not going to really have the talent and the knowledge of every function that I'm looking at. And Hitachi, not only they brought the talent but they also brought what he was talking about, Harc. You know, they have set up a lot and now we can leverage it. And they also came up with some really interesting concepts. I went and met them in India. They came up with this concept called IPL. Okay, what is that? They really challenged all their employees that's working for GCI to come up with innovative ideas to solve problems proactively, which is self-healing. You know, how you do that? So I think partners, you know, if they become really vested in your interests, they can do wonders for you. And I think in this case Hitachi is really working very well for us and in many aspects. And I'm leveraging them... You started with support, now I'm leveraging them in the automation, the platform engineering, as well as in the reliability engineering and then in even in the engineering spaces. And that like, they are my end-to-end partner right now? >> So you're really taking that holistic approach that you talked about and it sounds like it's a very collaborative two-way street partnership. Prem, I want to go back to, Suresh mentioned Harc. Talk a little bit about what Harc is and then how partners fit into Hitachi's Harc strategy. >> Great, so let me spend like a few seconds on what Harc is. Lisa, again, I know we've been using the term. Harc stands for Hitachi application reliability sectors. Now the reason we thought about Harc was, like I said in the beginning of this segment, there is an illusion from an architecture standpoint to be more modern, microservices, server-less, reactive architecture, so on and so forth. There is an illusion in your development methodology from Waterfall to agile, to DevOps to lean, agile to path program, whatever, right? Extreme program, so on and so forth. There is an evolution in the space of infrastructure from a point where you were buying these huge humongous servers and putting it in your data center to a point where people don't even see servers anymore, right? You buy it, by a click of a button you don't know the size of it. All you know is a, it's (indistinct) whatever that name means. Let's go provision it on the fly, get go, get your work done, right? When all of this is advanced when you think about operations people have been solving the problem the way they've been solving it 20 years back, right? That's the issue. And Harc was conceived exactly to fix that particular problem, to think about a modern way of operating a modern workload, right? That's exactly what Harc. So it brings together finest engineering talent. So the teams are trained in specific ways of working. We've invested and implemented some of the IP, we work with the best of the breed partner ecosystem, and I'll talk about that in a minute. And we've got these facilities in Dallas and I am talking from my office in Dallas, which is a Harc facility in the US from where we deliver for our customers. And then back in Hyderabad, we've got one more that we opened and these are facilities from where we deliver Harc services for our customers as well, right? And then we are expanding it in Japan and Portugal as we move into 23. That's kind of the plan that we are thinking through. However, that's what Harc is, Lisa, right? That's our solution to this cloud complexity problem. Right? >> Got it, and it sounds like it's going quite global, which is fantastic. So Suresh, I want to have you expand a bit on the partnership, the partner ecosystem and the role that it plays. You talked about it a little bit but what role does the partner ecosystem play in really helping JCI to dial down some of those challenges and the inherent complexities that we talked about? >> Yeah, sure. I think partners play a major role and JCI is very, very good at it. I mean, I've joined JCI 18 months ago, JCI leverages partners pretty extensively. As I said, I leverage Hitachi for my, you know, A group and the (indistinct) space and the cloud operations space, and they're my primary partner. But at the same time, we leverage many other partners. Well, you know, Accenture, SCL, and even on the tooling side we use Datadog and (indistinct). All these guys are major partners of our because the way we like to pick partners is based on our vision and where we want to go. And pick the right partner who's going to really, you know make you successful by investing their resources in you. And what I mean by that is when you have a partner, partner knows exactly what kind of skillset is needed for this customer, for them to really be successful. As I said earlier, we cannot really get all the skillset that we need, we rely on the partners and partners bring the the right skillset, they can scale. I can tell Prem tomorrow, "Hey, I need two parts by next week", and I guarantee it he's going to bring two parts to me. So they let you scale, they let you move fast. And I'm a big believer, in today's day and age, to get things done fast and be more agile. I'm not worried about failure, but for me moving fast is very, very important. And partners really do a very good job bringing that. But I think then they also really make you think, isn't it? Because one thing I like about partners they make you innovate whether they know it or not but they do because, you know, they will come and ask you questions about, "Hey, tell me why you are doing this. Can I review your architecture?" You know, and then they will try to really say I don't think this is going to work. Because they work with so many different clients, not JCI, they bring all that expertise and that's what I look from them, you know, just not, you know, do a T&M job for me. I ask you to do this go... They just bring more than that. That's how I pick my partners. And that's how, you know, Hitachi's Vantara is definitely one of a good partner from that sense because they bring a lot more innovation to the table and I appreciate about that. >> It sounds like, it sounds like a flywheel of innovation. >> Yeah. >> I love that. Last question for both of you, which we're almost out of time here, Prem, I want to go back to you. So I'm a partner, I'm planning on redefining CloudOps at my company. What are the two things you want me to remember from Hitachi Vantara's perspective? >> So before I get to that question, Lisa, the partners that we work with are slightly different from from the partners that, again, there are some similar partners. There are some different partners, right? For example, we pick and choose especially in the Harc space, we pick and choose partners that are more future focused, right? We don't care if they are huge companies or small companies. We go after companies that are future focused that are really, really nimble and can change for our customers need because it's not our need, right? When I pick partners for Harc my ultimate endeavor is to ensure, in this case because we've got (indistinct) GCI on, we are able to operate (indistinct) with the level of satisfaction above and beyond that they're expecting from us. And whatever I don't have I need to get from my partners so that I bring this solution to Suresh. As opposed to bringing a whole lot of people and making them stand in front of Suresh. So that's how I think about partners. What do I want them to do from, and we've always done this so we do workshops with our partners. We just don't go by tools. When we say we are partnering with X, Y, Z, we do workshops with them and we say, this is how we are thinking. Either you build it in your roadmap that helps us leverage you, continue to leverage you. And we do have minimal investments where we fix gaps. We're building some utilities for us to deliver the best service to our customers. And our intention is not to build a product to compete with our partner. Our intention is to just fill the wide space until they go build it into their product suite that we can then leverage it for our customers. So always think about end customers and how can we make it easy for them? Because for all the tool vendors out there seeing this and wanting to partner with Hitachi the biggest thing is tools sprawl, especially on the cloud is very real. For every problem on the cloud. I have a billion tools that are being thrown at me as Suresh if I'm putting my installation and it's not easy at all. It's so confusing. >> Yeah. >> So that's what we want. We want people to simplify that landscape for our end customers, and we are looking at partners that are thinking through the simplification not just making money. >> That makes perfect sense. There really is a very strong symbiosis it sounds like, in the partner ecosystem. And there's a lot of enablement that goes on back and forth it sounds like as well, which is really, to your point it's all about the end customers and what they're expecting. Suresh, last question for you is which is the same one, if I'm a partner what are the things that you want me to consider as I'm planning to redefine CloudOps at my company? >> I'll keep it simple. In my view, I mean, we've touched upon it in multiple facets in this interview about that, the three things. First and foremost, reliability. You know, in today's day and age my products has to be reliable, available and, you know, make sure that the customer's happy with what they're really dealing with, number one. Number two, my product has to be secure. Security is super, super important, okay? And number three, I need to really make sure my customers are getting the value so I keep my cost low. So these three is what I would focus and what I expect from my partners. >> Great advice, guys. Thank you so much for talking through this with me and really showing the audience how strong the partnership is between Hitachi Vantara and JCI. What you're doing together, we'll have to talk to you again to see where things go but we really appreciate your insights and your perspectives. Thank you. >> Thank you, Lisa. >> Thanks Lisa, thanks for having us. >> My pleasure. For my guests, I'm Lisa Martin. Thank you so much for watching. (soothing music)

(soothing music) >> Hey everyone, welcome to this event, "Build Your Cloud Center of Excellence." I'm your host, Lisa Martin. In the next 15 minutes or so my guest and I are going to be talking about redefining cloud operations, an application modernization for customers, and specifically how partners are helping to speed up that process. As you saw on our first two segments, we talked about problems enterprises are facing with cloud operations. We talked about redefining cloud operations as well to solve these problems. This segment is going to be focusing on how Hitachi Vantara's partners are really helping to speed up that process. We've got Johnson Controls here to talk about their partnership with Hitachi Vantara. Please welcome both of my guests, Prem Balasubramanian is with us, SVP and CTO Digital Solutions at Hitachi Vantara. And Suresh Mothikuru, SVP Customer Success Platform Engineering and Reliability Engineering from Johnson Controls. Gentlemen, welcome to the program, great to have you. >> Thank. >> Thank you, Lisa. >> First question is to both of you and Suresh, we'll start with you. We want to understand, you know, the cloud operations landscape is increasingly complex. We've talked a lot about that in this program. Talk to us, Suresh, about some of the biggest challenges and pin points that you faced with respect to that. >> Thank you. I think it's a great question. I mean, cloud has evolved a lot in the last 10 years. You know, when we were talking about a single cloud whether it's Azure or AWS and GCP, and that was complex enough. Now we are talking about multi-cloud and hybrid and you look at Johnson Controls, we have Azure we have AWS, we have GCP, we have Alibaba and we also support on-prem. So the architecture has become very, very complex and the complexity has grown so much that we are now thinking about whether we should be cloud native or cloud agnostic. So I think, I mean, sometimes it's hard to even explain the complexity because people think, oh, "When you go to cloud, everything is simplified." Cloud does give you a lot of simplicity, but it also really brings a lot more complexity along with it. So, and then next one is pretty important is, you know, generally when you look at cloud services, you have plenty of services that are offered within a cloud, 100, 150 services, 200 services. Even within those companies, you take AWS they might not know, an individual resource might not know about all the services we see. That's a big challenge for us as a customer to really understand each of the service that is provided in these, you know, clouds, well, doesn't matter which one that is. And the third one is pretty big, at least at the CTO the CIO, and the senior leadership level, is cost. Cost is a major factor because cloud, you know, will eat you up if you cannot manage it. If you don't have a good cloud governance process it because every minute you are in it, it's burning cash. So I think if you ask me, these are the three major things that I am facing day to day and that's where I use my partners, which I'll touch base down the line. >> Perfect, we'll talk about that. So Prem, I imagine that these problems are not unique to Johnson Controls or JCI, as you may hear us refer to it. Talk to me Prem about some of the other challenges that you're seeing within the customer landscape. >> So, yeah, I agree, Lisa, these are not very specific to JCI, but there are specific issues in JCI, right? So the way we think about these are, there is a common issue when people go to the cloud and there are very specific and unique issues for businesses, right? So JCI, and we will talk about this in the episode as we move forward. I think Suresh and his team have done some phenomenal step around how to manage this complexity. But there are customers who have a lesser complex cloud which is, they don't go to Alibaba, they don't have footprint in all three clouds. So their multi-cloud footprint could be a bit more manageable, but still struggle with a lot of the same problems around cost, around security, around talent. Talent is a big thing, right? And in Suresh's case I think it's slightly more exasperated because every cloud provider Be it AWS, JCP, or Azure brings in hundreds of services and there is nobody, including many of us, right? We learn every day, nowadays, right? It's not that there is one service integrator who knows all, while technically people can claim as a part of sales. But in reality all of us are continuing to learn in this landscape. And if you put all of this equation together with multiple clouds the complexity just starts to exponentially grow. And that's exactly what I think JCI is experiencing and Suresh's team has been experiencing, and we've been working together. But the common problems are around security talent and cost management of this, right? Those are my three things. And one last thing that I would love to say before we move away from this question is, if you think about cloud operations as a concept that's evolving over the last few years, and I have touched upon this in the previous episode as well, Lisa, right? If you take architectures, we've gone into microservices, we've gone into all these server-less architectures all the fancy things that we want. That helps us go to market faster, be more competent to as a business. But that's not simplified stuff, right? That's complicated stuff. It's a lot more distributed. Second, again, we've advanced and created more modern infrastructure because all of what we are talking is platform as a service, services on the cloud that we are consuming, right? In the same case with development we've moved into a DevOps model. We kind of click a button put some code in a repository, the code starts to run in production within a minute, everything else is automated. But then when we get to operations we are still stuck in a very old way of looking at cloud as an infrastructure, right? So you've got an infra team, you've got an app team, you've got an incident management team, you've got a soft knock, everything. But again, so Suresh can talk about this more because they are making significant strides in thinking about this as a single workload, and how do I apply engineering to go manage this? Because a lot of it is codified, right? So automation. Anyway, so that's kind of where the complexity is and how we are thinking, including JCI as a partner thinking about taming that complexity as we move forward. >> Suresh, let's talk about that taming the complexity. You guys have both done a great job of articulating the ostensible challenges that are there with cloud, especially multi-cloud environments that you're living in. But Suresh, talk about the partnership with Hitachi Vantara. How is it helping to dial down some of those inherent complexities? >> I mean, I always, you know, I think I've said this to Prem multiple times. I treat my partners as my internal, you know, employees. I look at Prem as my coworker or my peers. So the reason for that is I want Prem to have the same vested interest as a partner in my success or JCI success and vice versa, isn't it? I think that's how we operate and that's how we have been operating. And I think I would like to thank Prem and Hitachi Vantara for that really been an amazing partnership. And as he was saying, we have taken a completely holistic approach to how we want to really be in the market and play in the market to our customers. So if you look at my jacket it talks about OpenBlue platform. This is what JCI is building, that we are building this OpenBlue digital platform. And within that, my team, along with Prem's or Hitachi's, we have built what we call as Polaris. It's a technical platform where our apps can run. And this platform is automated end-to-end from a platform engineering standpoint. We stood up a platform engineering organization, a reliability engineering organization, as well as a support organization where Hitachi played a role. As I said previously, you know, for me to scale I'm not going to really have the talent and the knowledge of every function that I'm looking at. And Hitachi, not only they brought the talent but they also brought what he was talking about, Harc. You know, they have set up a lot and now we can leverage it. And they also came up with some really interesting concepts. I went and met them in India. They came up with this concept called IPL. Okay, what is that? They really challenged all their employees that's working for GCI to come up with innovative ideas to solve problems proactively, which is self-healing. You know, how you do that? So I think partners, you know, if they become really vested in your interests, they can do wonders for you. And I think in this case Hitachi is really working very well for us and in many aspects. And I'm leveraging them... You started with support, now I'm leveraging them in the automation, the platform engineering, as well as in the reliability engineering and then in even in the engineering spaces. And that like, they are my end-to-end partner right now? >> So you're really taking that holistic approach that you talked about and it sounds like it's a very collaborative two-way street partnership. Prem, I want to go back to, Suresh mentioned Harc. Talk a little bit about what Harc is and then how partners fit into Hitachi's Harc strategy. >> Great, so let me spend like a few seconds on what Harc is. Lisa, again, I know we've been using the term. Harc stands for Hitachi application reliability sectors. Now the reason we thought about Harc was, like I said in the beginning of this segment, there is an illusion from an architecture standpoint to be more modern, microservices, server-less, reactive architecture, so on and so forth. There is an illusion in your development methodology from Waterfall to agile, to DevOps to lean, agile to path program, whatever, right? Extreme program, so on and so forth. There is an evolution in the space of infrastructure from a point where you were buying these huge humongous servers and putting it in your data center to a point where people don't even see servers anymore, right? You buy it, by a click of a button you don't know the size of it. All you know is a, it's (indistinct) whatever that name means. Let's go provision it on the fly, get go, get your work done, right? When all of this is advanced when you think about operations people have been solving the problem the way they've been solving it 20 years back, right? That's the issue. And Harc was conceived exactly to fix that particular problem, to think about a modern way of operating a modern workload, right? That's exactly what Harc. So it brings together finest engineering talent. So the teams are trained in specific ways of working. We've invested and implemented some of the IP, we work with the best of the breed partner ecosystem, and I'll talk about that in a minute. And we've got these facilities in Dallas and I am talking from my office in Dallas, which is a Harc facility in the US from where we deliver for our customers. And then back in Hyderabad, we've got one more that we opened and these are facilities from where we deliver Harc services for our customers as well, right? And then we are expanding it in Japan and Portugal as we move into 23. That's kind of the plan that we are thinking through. However, that's what Harc is, Lisa, right? That's our solution to this cloud complexity problem. Right? >> Got it, and it sounds like it's going quite global, which is fantastic. So Suresh, I want to have you expand a bit on the partnership, the partner ecosystem and the role that it plays. You talked about it a little bit but what role does the partner ecosystem play in really helping JCI to dial down some of those challenges and the inherent complexities that we talked about? >> Yeah, sure. I think partners play a major role and JCI is very, very good at it. I mean, I've joined JCI 18 months ago, JCI leverages partners pretty extensively. As I said, I leverage Hitachi for my, you know, A group and the (indistinct) space and the cloud operations space, and they're my primary partner. But at the same time, we leverage many other partners. Well, you know, Accenture, SCL, and even on the tooling side we use Datadog and (indistinct). All these guys are major partners of our because the way we like to pick partners is based on our vision and where we want to go. And pick the right partner who's going to really, you know make you successful by investing their resources in you. And what I mean by that is when you have a partner, partner knows exactly what kind of skillset is needed for this customer, for them to really be successful. As I said earlier, we cannot really get all the skillset that we need, we rely on the partners and partners bring the the right skillset, they can scale. I can tell Prem tomorrow, "Hey, I need two parts by next week", and I guarantee it he's going to bring two parts to me. So they let you scale, they let you move fast. And I'm a big believer, in today's day and age, to get things done fast and be more agile. I'm not worried about failure, but for me moving fast is very, very important. And partners really do a very good job bringing that. But I think then they also really make you think, isn't it? Because one thing I like about partners they make you innovate whether they know it or not but they do because, you know, they will come and ask you questions about, "Hey, tell me why you are doing this. Can I review your architecture?" You know, and then they will try to really say I don't think this is going to work. Because they work with so many different clients, not JCI, they bring all that expertise and that's what I look from them, you know, just not, you know, do a T&M job for me. I ask you to do this go... They just bring more than that. That's how I pick my partners. And that's how, you know, Hitachi's Vantara is definitely one of a good partner from that sense because they bring a lot more innovation to the table and I appreciate about that. >> It sounds like, it sounds like a flywheel of innovation. >> Yeah. >> I love that. Last question for both of you, which we're almost out of time here, Prem, I want to go back to you. So I'm a partner, I'm planning on redefining CloudOps at my company. What are the two things you want me to remember from Hitachi Vantara's perspective? >> So before I get to that question, Lisa, the partners that we work with are slightly different from from the partners that, again, there are some similar partners. There are some different partners, right? For example, we pick and choose especially in the Harc space, we pick and choose partners that are more future focused, right? We don't care if they are huge companies or small companies. We go after companies that are future focused that are really, really nimble and can change for our customers need because it's not our need, right? When I pick partners for Harc my ultimate endeavor is to ensure, in this case because we've got (indistinct) GCI on, we are able to operate (indistinct) with the level of satisfaction above and beyond that they're expecting from us. And whatever I don't have I need to get from my partners so that I bring this solution to Suresh. As opposed to bringing a whole lot of people and making them stand in front of Suresh. So that's how I think about partners. What do I want them to do from, and we've always done this so we do workshops with our partners. We just don't go by tools. When we say we are partnering with X, Y, Z, we do workshops with them and we say, this is how we are thinking. Either you build it in your roadmap that helps us leverage you, continue to leverage you. And we do have minimal investments where we fix gaps. We're building some utilities for us to deliver the best service to our customers. And our intention is not to build a product to compete with our partner. Our intention is to just fill the wide space until they go build it into their product suite that we can then leverage it for our customers. So always think about end customers and how can we make it easy for them? Because for all the tool vendors out there seeing this and wanting to partner with Hitachi the biggest thing is tools sprawl, especially on the cloud is very real. For every problem on the cloud. I have a billion tools that are being thrown at me as Suresh if I'm putting my installation and it's not easy at all. It's so confusing. >> Yeah. >> So that's what we want. We want people to simplify that landscape for our end customers, and we are looking at partners that are thinking through the simplification not just making money. >> That makes perfect sense. There really is a very strong symbiosis it sounds like, in the partner ecosystem. And there's a lot of enablement that goes on back and forth it sounds like as well, which is really, to your point it's all about the end customers and what they're expecting. Suresh, last question for you is which is the same one, if I'm a partner what are the things that you want me to consider as I'm planning to redefine CloudOps at my company? >> I'll keep it simple. In my view, I mean, we've touched upon it in multiple facets in this interview about that, the three things. First and foremost, reliability. You know, in today's day and age my products has to be reliable, available and, you know, make sure that the customer's happy with what they're really dealing with, number one. Number two, my product has to be secure. Security is super, super important, okay? And number three, I need to really make sure my customers are getting the value so I keep my cost low. So these three is what I would focus and what I expect from my partners. >> Great advice, guys. Thank you so much for talking through this with me and really showing the audience how strong the partnership is between Hitachi Vantara and JCI. What you're doing together, we'll have to talk to you again to see where things go but we really appreciate your insights and your perspectives. Thank you. >> Thank you, Lisa. >> Thanks Lisa, thanks for having us. >> My pleasure. For my guests, I'm Lisa Martin. Thank you so much for watching. (soothing music)

(soothing music) >> Hey everyone, welcome to this event, "Build Your Cloud Center of Excellence." I'm your host, Lisa Martin. In the next 15 minutes or so my guest and I are going to be talking about redefining cloud operations, an application modernization for customers, and specifically how partners are helping to speed up that process. As you saw on our first two segments, we talked about problems enterprises are facing with cloud operations. We talked about redefining cloud operations as well to solve these problems. This segment is going to be focusing on how Hitachi Vantara's partners are really helping to speed up that process. We've got Johnson Controls here to talk about their partnership with Hitachi Vantara. Please welcome both of my guests, Prem Balasubramanian is with us, SVP and CTO Digital Solutions at Hitachi Vantara. And Suresh Mothikuru, SVP Customer Success Platform Engineering and Reliability Engineering from Johnson Controls. Gentlemen, welcome to the program, great to have you. >> Thank. >> Thank you, Lisa. >> First question is to both of you and Suresh, we'll start with you. We want to understand, you know, the cloud operations landscape is increasingly complex. We've talked a lot about that in this program. Talk to us, Suresh, about some of the biggest challenges and pin points that you faced with respect to that. >> Thank you. I think it's a great question. I mean, cloud has evolved a lot in the last 10 years. You know, when we were talking about a single cloud whether it's Azure or AWS and GCP, and that was complex enough. Now we are talking about multi-cloud and hybrid and you look at Johnson Controls, we have Azure we have AWS, we have GCP, we have Alibaba and we also support on-prem. So the architecture has become very, very complex and the complexity has grown so much that we are now thinking about whether we should be cloud native or cloud agnostic. So I think, I mean, sometimes it's hard to even explain the complexity because people think, oh, "When you go to cloud, everything is simplified." Cloud does give you a lot of simplicity, but it also really brings a lot more complexity along with it. So, and then next one is pretty important is, you know, generally when you look at cloud services, you have plenty of services that are offered within a cloud, 100, 150 services, 200 services. Even within those companies, you take AWS they might not know, an individual resource might not know about all the services we see. That's a big challenge for us as a customer to really understand each of the service that is provided in these, you know, clouds, well, doesn't matter which one that is. And the third one is pretty big, at least at the CTO the CIO, and the senior leadership level, is cost. Cost is a major factor because cloud, you know, will eat you up if you cannot manage it. If you don't have a good cloud governance process it because every minute you are in it, it's burning cash. So I think if you ask me, these are the three major things that I am facing day to day and that's where I use my partners, which I'll touch base down the line. >> Perfect, we'll talk about that. So Prem, I imagine that these problems are not unique to Johnson Controls or JCI, as you may hear us refer to it. Talk to me Prem about some of the other challenges that you're seeing within the customer landscape. >> So, yeah, I agree, Lisa, these are not very specific to JCI, but there are specific issues in JCI, right? So the way we think about these are, there is a common issue when people go to the cloud and there are very specific and unique issues for businesses, right? So JCI, and we will talk about this in the episode as we move forward. I think Suresh and his team have done some phenomenal step around how to manage this complexity. But there are customers who have a lesser complex cloud which is, they don't go to Alibaba, they don't have footprint in all three clouds. So their multi-cloud footprint could be a bit more manageable, but still struggle with a lot of the same problems around cost, around security, around talent. Talent is a big thing, right? And in Suresh's case I think it's slightly more exasperated because every cloud provider Be it AWS, JCP, or Azure brings in hundreds of services and there is nobody, including many of us, right? We learn every day, nowadays, right? It's not that there is one service integrator who knows all, while technically people can claim as a part of sales. But in reality all of us are continuing to learn in this landscape. And if you put all of this equation together with multiple clouds the complexity just starts to exponentially grow. And that's exactly what I think JCI is experiencing and Suresh's team has been experiencing, and we've been working together. But the common problems are around security talent and cost management of this, right? Those are my three things. And one last thing that I would love to say before we move away from this question is, if you think about cloud operations as a concept that's evolving over the last few years, and I have touched upon this in the previous episode as well, Lisa, right? If you take architectures, we've gone into microservices, we've gone into all these server-less architectures all the fancy things that we want. That helps us go to market faster, be more competent to as a business. But that's not simplified stuff, right? That's complicated stuff. It's a lot more distributed. Second, again, we've advanced and created more modern infrastructure because all of what we are talking is platform as a service, services on the cloud that we are consuming, right? In the same case with development we've moved into a DevOps model. We kind of click a button put some code in a repository, the code starts to run in production within a minute, everything else is automated. But then when we get to operations we are still stuck in a very old way of looking at cloud as an infrastructure, right? So you've got an infra team, you've got an app team, you've got an incident management team, you've got a soft knock, everything. But again, so Suresh can talk about this more because they are making significant strides in thinking about this as a single workload, and how do I apply engineering to go manage this? Because a lot of it is codified, right? So automation. Anyway, so that's kind of where the complexity is and how we are thinking, including JCI as a partner thinking about taming that complexity as we move forward. >> Suresh, let's talk about that taming the complexity. You guys have both done a great job of articulating the ostensible challenges that are there with cloud, especially multi-cloud environments that you're living in. But Suresh, talk about the partnership with Hitachi Vantara. How is it helping to dial down some of those inherent complexities? >> I mean, I always, you know, I think I've said this to Prem multiple times. I treat my partners as my internal, you know, employees. I look at Prem as my coworker or my peers. So the reason for that is I want Prem to have the same vested interest as a partner in my success or JCI success and vice versa, isn't it? I think that's how we operate and that's how we have been operating. And I think I would like to thank Prem and Hitachi Vantara for that really been an amazing partnership. And as he was saying, we have taken a completely holistic approach to how we want to really be in the market and play in the market to our customers. So if you look at my jacket it talks about OpenBlue platform. This is what JCI is building, that we are building this OpenBlue digital platform. And within that, my team, along with Prem's or Hitachi's, we have built what we call as Polaris. It's a technical platform where our apps can run. And this platform is automated end-to-end from a platform engineering standpoint. We stood up a platform engineering organization, a reliability engineering organization, as well as a support organization where Hitachi played a role. As I said previously, you know, for me to scale I'm not going to really have the talent and the knowledge of every function that I'm looking at. And Hitachi, not only they brought the talent but they also brought what he was talking about, Harc. You know, they have set up a lot and now we can leverage it. And they also came up with some really interesting concepts. I went and met them in India. They came up with this concept called IPL. Okay, what is that? They really challenged all their employees that's working for GCI to come up with innovative ideas to solve problems proactively, which is self-healing. You know, how you do that? So I think partners, you know, if they become really vested in your interests, they can do wonders for you. And I think in this case Hitachi is really working very well for us and in many aspects. And I'm leveraging them... You started with support, now I'm leveraging them in the automation, the platform engineering, as well as in the reliability engineering and then in even in the engineering spaces. And that like, they are my end-to-end partner right now? >> So you're really taking that holistic approach that you talked about and it sounds like it's a very collaborative two-way street partnership. Prem, I want to go back to, Suresh mentioned Harc. Talk a little bit about what Harc is and then how partners fit into Hitachi's Harc strategy. >> Great, so let me spend like a few seconds on what Harc is. Lisa, again, I know we've been using the term. Harc stands for Hitachi application reliability sectors. Now the reason we thought about Harc was, like I said in the beginning of this segment, there is an illusion from an architecture standpoint to be more modern, microservices, server-less, reactive architecture, so on and so forth. There is an illusion in your development methodology from Waterfall to agile, to DevOps to lean, agile to path program, whatever, right? Extreme program, so on and so forth. There is an evolution in the space of infrastructure from a point where you were buying these huge humongous servers and putting it in your data center to a point where people don't even see servers anymore, right? You buy it, by a click of a button you don't know the size of it. All you know is a, it's (indistinct) whatever that name means. Let's go provision it on the fly, get go, get your work done, right? When all of this is advanced when you think about operations people have been solving the problem the way they've been solving it 20 years back, right? That's the issue. And Harc was conceived exactly to fix that particular problem, to think about a modern way of operating a modern workload, right? That's exactly what Harc. So it brings together finest engineering talent. So the teams are trained in specific ways of working. We've invested and implemented some of the IP, we work with the best of the breed partner ecosystem, and I'll talk about that in a minute. And we've got these facilities in Dallas and I am talking from my office in Dallas, which is a Harc facility in the US from where we deliver for our customers. And then back in Hyderabad, we've got one more that we opened and these are facilities from where we deliver Harc services for our customers as well, right? And then we are expanding it in Japan and Portugal as we move into 23. That's kind of the plan that we are thinking through. However, that's what Harc is, Lisa, right? That's our solution to this cloud complexity problem. Right? >> Got it, and it sounds like it's going quite global, which is fantastic. So Suresh, I want to have you expand a bit on the partnership, the partner ecosystem and the role that it plays. You talked about it a little bit but what role does the partner ecosystem play in really helping JCI to dial down some of those challenges and the inherent complexities that we talked about? >> Yeah, sure. I think partners play a major role and JCI is very, very good at it. I mean, I've joined JCI 18 months ago, JCI leverages partners pretty extensively. As I said, I leverage Hitachi for my, you know, A group and the (indistinct) space and the cloud operations space, and they're my primary partner. But at the same time, we leverage many other partners. Well, you know, Accenture, SCL, and even on the tooling side we use Datadog and (indistinct). All these guys are major partners of our because the way we like to pick partners is based on our vision and where we want to go. And pick the right partner who's going to really, you know make you successful by investing their resources in you. And what I mean by that is when you have a partner, partner knows exactly what kind of skillset is needed for this customer, for them to really be successful. As I said earlier, we cannot really get all the skillset that we need, we rely on the partners and partners bring the the right skillset, they can scale. I can tell Prem tomorrow, "Hey, I need two parts by next week", and I guarantee it he's going to bring two parts to me. So they let you scale, they let you move fast. And I'm a big believer, in today's day and age, to get things done fast and be more agile. I'm not worried about failure, but for me moving fast is very, very important. And partners really do a very good job bringing that. But I think then they also really make you think, isn't it? Because one thing I like about partners they make you innovate whether they know it or not but they do because, you know, they will come and ask you questions about, "Hey, tell me why you are doing this. Can I review your architecture?" You know, and then they will try to really say I don't think this is going to work. Because they work with so many different clients, not JCI, they bring all that expertise and that's what I look from them, you know, just not, you know, do a T&M job for me. I ask you to do this go... They just bring more than that. That's how I pick my partners. And that's how, you know, Hitachi's Vantara is definitely one of a good partner from that sense because they bring a lot more innovation to the table and I appreciate about that. >> It sounds like, it sounds like a flywheel of innovation. >> Yeah. >> I love that. Last question for both of you, which we're almost out of time here, Prem, I want to go back to you. So I'm a partner, I'm planning on redefining CloudOps at my company. What are the two things you want me to remember from Hitachi Vantara's perspective? >> So before I get to that question, Lisa, the partners that we work with are slightly different from from the partners that, again, there are some similar partners. There are some different partners, right? For example, we pick and choose especially in the Harc space, we pick and choose partners that are more future focused, right? We don't care if they are huge companies or small companies. We go after companies that are future focused that are really, really nimble and can change for our customers need because it's not our need, right? When I pick partners for Harc my ultimate endeavor is to ensure, in this case because we've got (indistinct) GCI on, we are able to operate (indistinct) with the level of satisfaction above and beyond that they're expecting from us. And whatever I don't have I need to get from my partners so that I bring this solution to Suresh. As opposed to bringing a whole lot of people and making them stand in front of Suresh. So that's how I think about partners. What do I want them to do from, and we've always done this so we do workshops with our partners. We just don't go by tools. When we say we are partnering with X, Y, Z, we do workshops with them and we say, this is how we are thinking. Either you build it in your roadmap that helps us leverage you, continue to leverage you. And we do have minimal investments where we fix gaps. We're building some utilities for us to deliver the best service to our customers. And our intention is not to build a product to compete with our partner. Our intention is to just fill the wide space until they go build it into their product suite that we can then leverage it for our customers. So always think about end customers and how can we make it easy for them? Because for all the tool vendors out there seeing this and wanting to partner with Hitachi the biggest thing is tools sprawl, especially on the cloud is very real. For every problem on the cloud. I have a billion tools that are being thrown at me as Suresh if I'm putting my installation and it's not easy at all. It's so confusing. >> Yeah. >> So that's what we want. We want people to simplify that landscape for our end customers, and we are looking at partners that are thinking through the simplification not just making money. >> That makes perfect sense. There really is a very strong symbiosis it sounds like, in the partner ecosystem. And there's a lot of enablement that goes on back and forth it sounds like as well, which is really, to your point it's all about the end customers and what they're expecting. Suresh, last question for you is which is the same one, if I'm a partner what are the things that you want me to consider as I'm planning to redefine CloudOps at my company? >> I'll keep it simple. In my view, I mean, we've touched upon it in multiple facets in this interview about that, the three things. First and foremost, reliability. You know, in today's day and age my products has to be reliable, available and, you know, make sure that the customer's happy with what they're really dealing with, number one. Number two, my product has to be secure. Security is super, super important, okay? And number three, I need to really make sure my customers are getting the value so I keep my cost low. So these three is what I would focus and what I expect from my partners. >> Great advice, guys. Thank you so much for talking through this with me and really showing the audience how strong the partnership is between Hitachi Vantara and JCI. What you're doing together, we'll have to talk to you again to see where things go but we really appreciate your insights and your perspectives. Thank you. >> Thank you, Lisa. >> Thanks Lisa, thanks for having us. >> My pleasure. For my guests, I'm Lisa Martin. Thank you so much for watching. (soothing music)

(bright upbeat melody) >> Hello everyone, welcome back to Supercloud2. I'm John Furrier, my co-host Dave Vellante, here at theCUBE in Palo Alto, California, for our live stage performance all day for Supercloud2. Unpacking this next generation movement in cloud computing. Dave, Supercloud1 was in August. We had great response and acceleration of that momentum. We had some haters too. We had some folks out there throwing shade on this. But at the same time, a lot of leaders came out of the woodwork, a lot of practitioners. And this Supercloud2 event I think will expose and illustrate some of the examples of what's happening in the industry and more importantly, kind of where it's going. >> Well it's great to be back in our studios in Palo Alto, John. Seems like just yesterday was August 9th, where the community was really refining the definition of Super Cloud. We were identifying the essential characteristics, with some of the leading technologists in Silicon Valley. We were digging into the deployment models. Whereas this Supercloud, Supercloud2 is really taking a practitioner view. We're going to hear from Walmart today. They've built a Supercloud. They called it the Walmart Cloud native platform. We're going to hear from other data practitioners, like Saks. We're going to hear from Western Union. They've got 200 locations around the world, how they're dealing with data sovereignty. And of course we've got some local technologists and practitioners coming in, analysts, consultants, theCUBE community. I'm really excited to be here. >> And we've got some great keynotes from executives at VMware. We're going to expose some of the things that they're working on around cross cloud services, which leads into multicloud. I think the practitioner angle highlights my favorite part of this program, 'cause you're starting to see the builders, a term coined by Andy Jassy, early days of AWS. That builder movement has been continuing to go. And you're seeing the enterprise, global enterprises adopt this builder mentality with Cloud Native. This is going to power the next generation global economy. And I think the role of the cloud computing vendors like AWS, Azure, Google, Alibaba are going to be the source engine of innovation. And what gets built on top of and with the clouds will be a big significant market value for all businesses and their business models. So I think the market wants the supercloud, the business models are pointing to Supercloud. The technology needs supercloud. And society, from an economic standpoint and from a use case standpoint, needs supercloud. You're seeing it today. Everyone's talking about chat GPT. This is an example of what will come out of this next generation and it's just getting started. So to me, you're either on the supercloud side of the camp or you're on the old school, hugging onto the old school mentality of wait a minute, that's cloud computing. So I think if you're not on the super cloud wave, you're going to be driftwood. And that's a term coined by Pat Gelsinger. And this is really the reality. Are you on the super cloud side? Or are you on the old huggin' the old model? And that's going to be a determinant. And you're going to see who's going to be the players on that, Dave. This is going to be a real big year. >> Everybody's heard the phrase follow the money. Well, my philosophy is follow the data. And that's a big part of what Supercloud2 is, because the data is where the money is across the clouds. And people want more simplicity, or greater simplicity across the clouds. So it's really, there's two forces here. You've got the ecosystem that's saying, hey the hyperscalers, they've done a great job but there's problems that they're not solving. So we're going to lean in and solve those problems. At the same time, you have the practitioners saying we have multicloud, we have to deal with this, help us. It's got to be simpler. Because we want to share data across clouds. We want to build data products, we want to monetize and drive revenue and cut costs. >> This is the key thing. The builder movement is hitting a wall, and that wall will be broken down because the business models of the companies themselves are demanding that the value from the data with security has to be embedded. So I think you're going to see a big year this next year or so where the builders will accelerate through this next generation, supercloud wave, will be a builder's wave for business. And I think that's going to be the nuance here. And all the people that are on the side of Supercloud are all pro-business, pro-technology. The ones that aren't are like, wait a minute I used to do things differently. They're stuck. And so I think this is going to be a question of are we stuck? Are builders accelerating? Will the business models develop around it? That's digital transformation. At the end of the day, the market's speaking, Dave. The market wants more. Chat GPT, you're seeing AI starting to flourish, powered by data. It's unstoppable, supercloud's unstoppable. >> One of our headliners today is Zhamak Dehghani, the creator of Data Mesh. We've got some news around her. She's going to be live in studio. Super excited about that. Kit Colbert in Supercloud, the first Supercloud in last August, laid out an initial architecture for Supercloud. He's going to advance that today, tell us what's changed, and really dig into and really talk about the meat on the bone, if you will. And we've got some other technologists that are coming in saying, Hey, is it a platform? Is it an architecture? What's the right model here? So we're going to debate that a little bit today. >> And before we close, I'll just say look at the guests, look at the talk tracks. You're seeing a diversity of startups doing cloud networking, you're seeing big practitioners building their own thing, being builders for business value and business model advantages. And you got companies like VMware, who have been on the wave of virtualization. So the, everyone who's involved in super cloud, they're seeing it, they're on the front lines. They're seeing the trend. They are riding that wave. And they have, they're bringing data to the table. So to me, you look at who's involved and you judge it that way. To me, that's the way I look at this. And because we're making it open, Supercloud is going to continue to be debated. But more importantly, the results are going to come in. The market supports it, the business needs it, tech's there, and will it happen? So I think the builders movement, Dave, is going to be big to watch. And then ultimately how that business transformation kicks in, and I think those are the two variables that I would watch on Supercloud. >> Our mission has always been around free content, giving back to the community. So I really want to thank our sponsors today. We've had a great partnership with VMware, who's not only contributed some financial support, but also great content. Alkira, ChaosSearch, prosimo, all phenomenal, allowing us to achieve our mission of serving our audiences and really trying to give more than we take from. >> Free content, that's our mission. Dave, great to kick it off. Kickin' off Supercloud2 all day, we've got some great programs here. We've got VMware coming up next. We have Victoria Viering, who's been on before. He's got a great vision for cross cloud service. We're getting also a keynote with Kit Colbert, who's going to lay out the fragmentation and the benefits that that solves, from solvent fragmentation and silos, breaking down the silos and bringing multicloud future to the table via Super Cloud. So stay with us. We'll be right back after this short break. (bright upbeat music) (music fades)

>> 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. >> The unraveling of market enthusiasm continued in Q4 of 2022 with the earnings reports from the US hyperscalers, the big three now all in. As we said earlier this year, even the cloud is an immune from the macro headwinds and the cracks in the armor that we saw from the data that we shared last summer, they're playing out into 2023. For the most part actuals are disappointing beyond expectations including our own. It turns out that our estimates for the big three hyperscaler's revenue missed by 1.2 billion or 2.7% lower than we had forecast from even our most recent November estimates. And we expect continued decelerating growth rates for the hyperscalers through the summer of 2023 and we don't think that's going to abate until comparisons get easier. Hello and welcome to this week's Wikibon Cube Insights powered by ETR. In this Breaking Analysis, we share our view of what's happening in cloud markets not just for the hyperscalers but other firms that have hitched a ride on the cloud. And we'll share new ETR data that shows why these trends are playing out tactics that customers are employing to deal with their cost challenges and how long the pain is likely to last. You know, riding the cloud wave, it's a two-edged sword. Let's look at the players that have gone all in on or are exposed to both the positive and negative trends of cloud. Look the cloud has been a huge tailwind for so many companies like Snowflake and Databricks, Workday, Salesforce, Mongo's move with Atlas, Red Hats Cloud strategy with OpenShift and so forth. And you know, the flip side is because cloud is elastic what comes up can also go down very easily. Here's an XY graphic from ETR that shows spending momentum or net score on the vertical axis and market presence in the dataset on the horizontal axis provision or called overlap. This is data from the January 2023 survey and that the red dotted lines show the positions of several companies that we've highlighted going back to January 2021. So let's unpack this for a bit starting with the big three hyperscalers. The first point is AWS and Azure continue to solidify their moat relative to Google Cloud platform. And we're going to get into this in a moment, but Azure and AWS revenues are five to six times that of GCP for IaaS. And at those deltas, Google should be gaining ground much faster than the big two. The second point on Google is notice the red line on GCP relative to its starting point. While it appears to be gaining ground on the horizontal axis, its net score is now below that of AWS and Azure in the survey. So despite its significantly smaller size it's just not keeping pace with the leaders in terms of market momentum. Now looking at AWS and Microsoft, what we see is basically AWS is holding serve. As we know both Google and Microsoft benefit from including SaaS in their cloud numbers. So the fact that AWS hasn't seen a huge downward momentum relative to a January 2021 position is one positive in the data. And both companies are well above that magic 40% line on the Y-axis, anything above 40% we consider to be highly elevated. But the fact remains that they're down as are most of the names on this chart. So let's take a closer look. I want to start with Snowflake and Databricks. Snowflake, as we reported from several quarters back came down to Earth, it was up in the 80% range in the Y-axis here. And it's still highly elevated in the 60% range and it continues to move to the right, which is positive but as we'll address in a moment it's customers can dial down consumption just as in any cloud. Now, Databricks is really interesting. It's not a public company, it never made it to IPO during the sort of tech bubble. So we don't have the same level of transparency that we do with other companies that did make it through. But look at how much more prominent it is on the X-axis relative to January 2021. And it's net score is basically held up over that period of time. So that's a real positive for Databricks. Next, look at Workday and Salesforce. They've held up relatively well, both inching to the right and generally holding their net scores. Same from Mongo, which is the brown dot above its name that says Elastic, it says a little gets a little crowded which Elastic's actually the blue dot above it. But generally, SaaS is harder to dial down, Workday, Salesforce, Oracles, SaaS and others. So it's harder to dial down because commitments have been made in advance, they're kind of locked in. Now, one of the discussions from last summer was as Mongo, less discretionary than analytics i.e. Snowflake. And it's an interesting debate but maybe Snowflake customers, you know, they're also generally committed to a dollar amount. So over time the spending is going to be there. But in the short term, yeah maybe Snowflake customers can dial down. Now that highlighted dotted red line, that bolded one is Datadog and you can see it's made major strides on the X-axis but its net score has decelerated quite dramatically. Openshift's momentum in the survey has dropped although IBM just announced that OpenShift has a a billion dollar ARR and I suspect what's happening there is IBM consulting is bundling OpenShift into its modernization projects. It's got a, that sort of captive base if you will. And as such it's probably not as top of mind to the respondents but I'll bet you the developers are certainly aware of it. Now the other really notable call out here is CloudFlare, We've reported on them earlier. Cloudflare's net score has held up really well since January of 2021. It really hasn't seen the downdraft of some of these others, but it's making major major moves to the right gaining market presence. We really like how CloudFlare is performing. And the last comment is on Oracle which as you can see, despite its much, much lower net score continues to gain ground in the market and thrive from a profitability standpoint. But the data pretty clearly shows that there's a downdraft in the market. Okay, so what's happening here? Let's dig deeper into this data. Here's a graphic from the most recent ETR drill down asking customers that said they were going to cut spending what technique they're using to do so. Now, as we've previously reported, consolidating redundant vendors is by far the most cited approach but there's two key points we want to make here. One is reducing excess cloud resources. As you can see in the bars is the second most cited technique and it's up from the previous polling period. The second we're not showing, you know directly but we've got some red call outs there. Reducing cloud costs jumps to 29% and 28% respectively in financial services and tech telco. And it's much closer to second. It's basically neck and neck with consolidating redundant vendors in those two industries. So they're being really aggressive about optimizing cloud cost. Okay, so as we said, cloud is great 'cause you can dial it up but it's just as easy to dial down. We've identified six factors that customers tell us are affecting their cloud consumption and there are probably more, if you got more we'd love to hear them but these are the ones that are fairly prominent that have hit our radar. First, rising mortgage rates mean banks are processing fewer loans means less cloud. The crypto crash means less trading activity and that means less cloud resources. Third lower ad spend has led companies to reduce not only you know, their ad buying but also their frequency of running their analytics and their calculations. And they're also often using less data, maybe compressing the timeframe of the corpus down to a shorter time period. Also very prominent is down to the bottom left, using lower cost compute instances. For example, Graviton from AWS or AMD chips and tiering storage to cheaper S3 or deep archived tiers. And finally, optimizing based on better pricing plans. So customers are moving from, you know, smaller companies in particular moving maybe from on demand or other larger companies that are experimenting using on demand or they're moving to spot pricing or reserved instances or optimized savings plans. That all lowers cost and that means less cloud resource consumption and less cloud revenue. Now in the days when everything was on prem CFOs, what would they do? They would freeze CapEx and IT Pros would have to try to do more with less and often that meant a lot of manual tasks. With the cloud it's much easier to move things around. It still takes some thinking and some effort but it's dramatically simpler to do so. So you can get those savings a lot faster. Now of course the other huge factor is you can cut or you can freeze. And this graphic shows data from a recent ETR survey with 159 respondents and you can see the meaningful uptick in hiring freezes, freezing new IT deployments and layoffs. And as we've been reporting, this has been trending up since earlier last year. And note the call out, this is especially prominent in retail sectors, all three of these techniques jump up in retail and that's a bit of a concern because oftentimes consumer spending helps the economy make a softer landing out of a pullback. But this is a potential canary in the coal mine. If retail firms are pulling back it's because consumers aren't spending as much. And so we're keeping a close eye on that. So let's boil this down to the market data and what this all means. So in this graphic we show our estimates for Q4 IaaS revenues compared to the "actual" IaaS revenues. And we say quote because AWS is the only one that reports, you know clean revenue and IaaS, Azure and GCP don't report actuals. Why would they? Because it would make them look even, you know smaller relative to AWS. Rather, they bury the figures in overall cloud which includes their, you know G-Suite for Google and all the Microsoft SaaS. And then they give us little tidbits about in Microsoft's case, Azure, they give growth rates. Google gives kind of relative growth of GCP. So, and we use survey data and you know, other data to try to really pinpoint and we've been covering this for, I don't know, five or six years ever since the cloud really became a thing. But looking at the data, we had AWS growing at 25% this quarter and it came in at 20%. So a significant decline relative to our expectations. AWS announced that it exited December, actually, sorry it's January data showed about a 15% mid-teens growth rate. So that's, you know, something we're watching. Azure was two points off our forecast coming in at 38% growth. It said it exited December in the 35% growth range and it said that it's expecting five points of deceleration off of that. So think 30% for Azure. GCP came in three points off our expectation coming in 35% and Alibaba has yet to report but we've shaved a bid off that forecast based on some survey data and you know what maybe 9% is even still not enough. Now for the year, the big four hyperscalers generated almost 160 billion of revenue, but that was 7 billion lower than what what we expected coming into 2022. For 2023, we're expecting 21% growth for a total of 193.3 billion. And while it's, you know, lower, you know, significantly lower than historical expectations it's still four to five times the overall spending forecast that we just shared with you in our predictions post of between 4 and 5% for the overall market. We think AWS is going to come in in around 93 billion this year with Azure closing in at over 71 billion. This is, again, we're talking IaaS here. Now, despite Amazon focusing investors on the fact that AWS's absolute dollar growth is still larger than its competitors. By our estimates Azure will come in at more than 75% of AWS's forecasted revenue. That's a significant milestone. AWS is operating margins by the way declined significantly this past quarter, dropping from 30% of revenue to 24%, 30% the year earlier to 24%. Now that's still extremely healthy and we've seen wild fluctuations like this before so I don't get too freaked out about that. But I'll say this, Microsoft has a marginal cost advantage relative to AWS because one, it has a captive cloud on which to run its massive software estate. So it can just throw software at its own cloud and two software marginal costs. Marginal economics despite AWS's awesomeness in high degrees of automation, software is just a better business. Now the upshot for AWS is the ecosystem. AWS is essentially in our view positioning very smartly as a platform for data partners like Snowflake and Databricks, security partners like CrowdStrike and Okta and Palo Alto and many others and SaaS companies. You know, Microsoft is more competitive even though AWS does have competitive products. Now of course Amazon's competitive to retail companies so that's another factor but generally speaking for tech players, Amazon is a really thriving ecosystem that is a secret weapon in our view. AWS happy to spin the meter with its partners even though it sells competitive products, you know, more so in our view than other cloud players. Microsoft, of course is, don't forget is hyping now, we're hearing a lot OpenAI and ChatGPT we reported last week in our predictions post. How OpenAI is shot up in terms of market sentiment in ETR's emerging technology company surveys and people are moving to Azure to get OpenAI and get ChatGPT that is a an interesting lever. Amazon in our view has to have a response. They have lots of AI and they're going to have to make some moves there. Meanwhile, Google is emphasizing itself as an AI first company. In fact, Google spent at least five minutes of continuous dialogue, nonstop on its AI chops during its latest earnings call. So that's an area that we're watching very closely as the buzz around large language models continues. All right, let's wrap up with some assumptions for 2023. We think SaaS players are going to continue to be sticky. They're going to be somewhat insulated from all these downdrafts because they're so tied in and customers, you know they make the commitment up front, you've got the lock in. Now having said that, we do expect some backlash over time on the onerous and generally customer unfriendly pricing models of most large SaaS companies. But that's going to play out over a longer period of time. Now for cloud generally and the hyperscalers specifically we do expect accelerating growth rates into Q3 but the amplitude of the demand swings from this rubber band economy, we expect to continue to compress and become more predictable throughout the year. Estimates are coming down, CEOs we think are going to be more cautious when the market snaps back more cautious about hiring and spending and as such a perhaps we expect a more orderly return to growth which we think will slightly accelerate in Q4 as comps get easier. Now of course the big risk to these scenarios is of course the economy, the FED, consumer spending, inflation, supply chain, energy prices, wars, geopolitics, China relations, you know, all the usual stuff. But as always with our partners at ETR and the Cube community, we're here for you. We have the data and we'll be the first to report when we see a change at the margin. Okay, that's a wrap for today. I want to thank Alex Morrison who's on production and manages the podcast, Ken Schiffman as well out of our Boston studio getting this up on LinkedIn Live. Thank you for that. Kristen Martin also and Cheryl Knight help get the word out on social media and in our newsletters. And Rob Hof is our Editor-in-Chief over at siliconangle.com. He does some great editing for us. Thank you all. Remember all these episodes are available as podcast. Wherever you listen, just search Breaking Analysis podcast. I publish each week on wikibon.com, at siliconangle.com where you can see all the data and you want to get in touch. Just all you can do is email me david.vellante@siliconangle.com or DM me @dvellante if you if you got something interesting, I'll respond. If you don't, it's either 'cause I'm swamped or it's just not tickling me. You can comment on our LinkedIn post as well. And please check out ETR.ai for the best survey data in the enterprise tech business. This is Dave Vellante for the Cube Insights powered by ETR. Thanks for watching and we'll see you next time on Breaking Analysis. (gentle upbeat music)

>>From the Cube Studios in Palo Alto in Boston, bringing you data-driven insights from the cube and E T R. This is breaking analysis with Dave Valante. >>Making technology predictions in 2022 was tricky business, especially if you were projecting the performance of markets or identifying I P O prospects and making binary forecast on data AI and the macro spending climate and other related topics in enterprise tech 2022, of course was characterized by a seesaw economy where central banks were restructuring their balance sheets. The war on Ukraine fueled inflation supply chains were a mess. And the unintended consequences of of forced march to digital and the acceleration still being sorted out. Hello and welcome to this week's weekly on Cube Insights powered by E T R. In this breaking analysis, we continue our annual tradition of transparently grading last year's enterprise tech predictions. And you may or may not agree with our self grading system, but look, we're gonna give you the data and you can draw your own conclusions and tell you what, tell us what you think. >>All right, let's get right to it. So our first prediction was tech spending increases by 8% in 2022. And as we exited 2021 CIOs, they were optimistic about their digital transformation plans. You know, they rushed to make changes to their business and were eager to sharpen their focus and continue to iterate on their digital business models and plug the holes that they, the, in the learnings that they had. And so we predicted that 8% rise in enterprise tech spending, which looked pretty good until Ukraine and the Fed decided that, you know, had to rush and make up for lost time. We kind of nailed the momentum in the energy sector, but we can't give ourselves too much credit for that layup. And as of October, Gartner had it spending growing at just over 5%. I think it was 5.1%. So we're gonna take a C plus on this one and, and move on. >>Our next prediction was basically kind of a slow ground ball. The second base, if I have to be honest, but we felt it was important to highlight that security would remain front and center as the number one priority for organizations in 2022. As is our tradition, you know, we try to up the degree of difficulty by specifically identifying companies that are gonna benefit from these trends. So we highlighted some possible I P O candidates, which of course didn't pan out. S NQ was on our radar. The company had just had to do another raise and they recently took a valuation hit and it was a down round. They raised 196 million. So good chunk of cash, but, but not the i p O that we had predicted Aqua Securities focus on containers and cloud native. That was a trendy call and we thought maybe an M SS P or multiple managed security service providers like Arctic Wolf would I p o, but no way that was happening in the crummy market. >>Nonetheless, we think these types of companies, they're still faring well as the talent shortage in security remains really acute, particularly in the sort of mid-size and small businesses that often don't have a sock Lacework laid off 20% of its workforce in 2022. And CO C e o Dave Hatfield left the company. So that I p o didn't, didn't happen. It was probably too early for Lacework. Anyway, meanwhile you got Netscope, which we've cited as strong in the E T R data as particularly in the emerging technology survey. And then, you know, I lumia holding its own, you know, we never liked that 7 billion price tag that Okta paid for auth zero, but we loved the TAM expansion strategy to target developers beyond sort of Okta's enterprise strength. But we gotta take some points off of the failure thus far of, of Okta to really nail the integration and the go to market model with azero and build, you know, bring that into the, the, the core Okta. >>So the focus on endpoint security that was a winner in 2022 is CrowdStrike led that charge with others holding their own, not the least of which was Palo Alto Networks as it continued to expand beyond its core network security and firewall business, you know, through acquisition. So overall we're gonna give ourselves an A minus for this relatively easy call, but again, we had some specifics associated with it to make it a little tougher. And of course we're watching ve very closely this this coming year in 2023. The vendor consolidation trend. You know, according to a recent Palo Alto network survey with 1300 SecOps pros on average organizations have more than 30 tools to manage security tools. So this is a logical way to optimize cost consolidating vendors and consolidating redundant vendors. The E T R data shows that's clearly a trend that's on the upswing. >>Now moving on, a big theme of 2020 and 2021 of course was remote work and hybrid work and new ways to work and return to work. So we predicted in 2022 that hybrid work models would become the dominant protocol, which clearly is the case. We predicted that about 33% of the workforce would come back to the office in 2022 in September. The E T R data showed that figure was at 29%, but organizations expected that 32% would be in the office, you know, pretty much full-time by year end. That hasn't quite happened, but we were pretty close with the projection, so we're gonna take an A minus on this one. Now, supply chain disruption was another big theme that we felt would carry through 2022. And sure that sounds like another easy one, but as is our tradition, again we try to put some binary metrics around our predictions to put some meat in the bone, so to speak, and and allow us than you to say, okay, did it come true or not? >>So we had some data that we presented last year and supply chain issues impacting hardware spend. We said at the time, you can see this on the left hand side of this chart, the PC laptop demand would remain above pre covid levels, which would reverse a decade of year on year declines, which I think started in around 2011, 2012. Now, while demand is down this year pretty substantially relative to 2021, I D C has worldwide unit shipments for PCs at just over 300 million for 22. If you go back to 2019 and you're looking at around let's say 260 million units shipped globally, you know, roughly, so, you know, pretty good call there. Definitely much higher than pre covid levels. But so what you might be asking why the B, well, we projected that 30% of customers would replace security appliances with cloud-based services and that more than a third would replace their internal data center server and storage hardware with cloud services like 30 and 40% respectively. >>And we don't have explicit survey data on exactly these metrics, but anecdotally we see this happening in earnest. And we do have some data that we're showing here on cloud adoption from ET R'S October survey where the midpoint of workloads running in the cloud is around 34% and forecast, as you can see, to grow steadily over the next three years. So this, well look, this is not, we understand it's not a one-to-one correlation with our prediction, but it's a pretty good bet that we were right, but we gotta take some points off, we think for the lack of unequivocal proof. Cause again, we always strive to make our predictions in ways that can be measured as accurate or not. Is it binary? Did it happen, did it not? Kind of like an O K R and you know, we strive to provide data as proof and in this case it's a bit fuzzy. >>We have to admit that although we're pretty comfortable that the prediction was accurate. And look, when you make an hard forecast, sometimes you gotta pay the price. All right, next, we said in 2022 that the big four cloud players would generate 167 billion in IS and PaaS revenue combining for 38% market growth. And our current forecasts are shown here with a comparison to our January, 2022 figures. So coming into this year now where we are today, so currently we expect 162 billion in total revenue and a 33% growth rate. Still very healthy, but not on our mark. So we think a w s is gonna miss our predictions by about a billion dollars, not, you know, not bad for an 80 billion company. So they're not gonna hit that expectation though of getting really close to a hundred billion run rate. We thought they'd exit the year, you know, closer to, you know, 25 billion a quarter and we don't think they're gonna get there. >>Look, we pretty much nailed Azure even though our prediction W was was correct about g Google Cloud platform surpassing Alibaba, Alibaba, we way overestimated the performance of both of those companies. So we're gonna give ourselves a C plus here and we think, yeah, you might think it's a little bit harsh, we could argue for a B minus to the professor, but the misses on GCP and Alibaba we think warrant a a self penalty on this one. All right, let's move on to our prediction about Supercloud. We said it becomes a thing in 2022 and we think by many accounts it has, despite the naysayers, we're seeing clear evidence that the concept of a layer of value add that sits above and across clouds is taking shape. And on this slide we showed just some of the pickup in the industry. I mean one of the most interesting is CloudFlare, the biggest supercloud antagonist. >>Charles Fitzgerald even predicted that no vendor would ever use the term in their marketing. And that would be proof if that happened that Supercloud was a thing and he said it would never happen. Well CloudFlare has, and they launched their version of Supercloud at their developer week. Chris Miller of the register put out a Supercloud block diagram, something else that Charles Fitzgerald was, it was was pushing us for, which is rightly so, it was a good call on his part. And Chris Miller actually came up with one that's pretty good at David Linthicum also has produced a a a A block diagram, kind of similar, David uses the term metacloud and he uses the term supercloud kind of interchangeably to describe that trend. And so we we're aligned on that front. Brian Gracely has covered the concept on the popular cloud podcast. Berkeley launched the Sky computing initiative. >>You read through that white paper and many of the concepts highlighted in the Supercloud 3.0 community developed definition align with that. Walmart launched a platform with many of the supercloud salient attributes. So did Goldman Sachs, so did Capital One, so did nasdaq. So you know, sorry you can hate the term, but very clearly the evidence is gathering for the super cloud storm. We're gonna take an a plus on this one. Sorry, haters. Alright, let's talk about data mesh in our 21 predictions posts. We said that in the 2020s, 75% of large organizations are gonna re-architect their big data platforms. So kind of a decade long prediction. We don't like to do that always, but sometimes it's warranted. And because it was a longer term prediction, we, at the time in, in coming into 22 when we were evaluating our 21 predictions, we took a grade of incomplete because the sort of decade long or majority of the decade better part of the decade prediction. >>So last year, earlier this year, we said our number seven prediction was data mesh gains momentum in 22. But it's largely confined and narrow data problems with limited scope as you can see here with some of the key bullets. So there's a lot of discussion in the data community about data mesh and while there are an increasing number of examples, JP Morgan Chase, Intuit, H S P C, HelloFresh, and others that are completely rearchitecting parts of their data platform completely rearchitecting entire data platforms is non-trivial. There are organizational challenges, there're data, data ownership, debates, technical considerations, and in particular two of the four fundamental data mesh principles that the, the need for a self-service infrastructure and federated computational governance are challenging. Look, democratizing data and facilitating data sharing creates conflicts with regulatory requirements around data privacy. As such many organizations are being really selective with their data mesh implementations and hence our prediction of narrowing the scope of data mesh initiatives. >>I think that was right on J P M C is a good example of this, where you got a single group within a, within a division narrowly implementing the data mesh architecture. They're using a w s, they're using data lakes, they're using Amazon Glue, creating a catalog and a variety of other techniques to meet their objectives. They kind of automating data quality and it was pretty well thought out and interesting approach and I think it's gonna be made easier by some of the announcements that Amazon made at the recent, you know, reinvent, particularly trying to eliminate ET t l, better connections between Aurora and Redshift and, and, and better data sharing the data clean room. So a lot of that is gonna help. Of course, snowflake has been on this for a while now. Many other companies are facing, you know, limitations as we said here and this slide with their Hadoop data platforms. They need to do new, some new thinking around that to scale. HelloFresh is a really good example of this. Look, the bottom line is that organizations want to get more value from data and having a centralized, highly specialized teams that own the data problem, it's been a barrier and a blocker to success. The data mesh starts with organizational considerations as described in great detail by Ash Nair of Warner Brothers. So take a listen to this clip. >>Yeah, so when people think of Warner Brothers, you always think of like the movie studio, but we're more than that, right? I mean, you think of H B O, you think of t n t, you think of C N N. We have 30 plus brands in our portfolio and each have their own needs. So the, the idea of a data mesh really helps us because what we can do is we can federate access across the company so that, you know, CNN can work at their own pace. You know, when there's election season, they can ingest their own data and they don't have to, you know, bump up against, as an example, HBO if Game of Thrones is going on. >>So it's often the case that data mesh is in the eyes of the implementer. And while a company's implementation may not strictly adhere to Jamma Dani's vision of data mesh, and that's okay, the goal is to use data more effectively. And despite Gartner's attempts to deposition data mesh in favor of the somewhat confusing or frankly far more confusing data fabric concept that they stole from NetApp data mesh is taking hold in organizations globally today. So we're gonna take a B on this one. The prediction is shaping up the way we envision, but as we previously reported, it's gonna take some time. The better part of a decade in our view, new standards have to emerge to make this vision become reality and they'll come in the form of both open and de facto approaches. Okay, our eighth prediction last year focused on the face off between Snowflake and Databricks. >>And we realized this popular topic, and maybe one that's getting a little overplayed, but these are two companies that initially, you know, looked like they were shaping up as partners and they, by the way, they are still partnering in the field. But you go back a couple years ago, the idea of using an AW w s infrastructure, Databricks machine intelligence and applying that on top of Snowflake as a facile data warehouse, still very viable. But both of these companies, they have much larger ambitions. They got big total available markets to chase and large valuations that they have to justify. So what's happening is, as we've previously reported, each of these companies is moving toward the other firm's core domain and they're building out an ecosystem that'll be critical for their future. So as part of that effort, we said each is gonna become aggressive investors and maybe start doing some m and a and they have in various companies. >>And on this chart that we produced last year, we studied some of the companies that were targets and we've added some recent investments of both Snowflake and Databricks. As you can see, they've both, for example, invested in elation snowflake's, put money into Lacework, the Secur security firm, ThoughtSpot, which is trying to democratize data with ai. Collibra is a governance platform and you can see Databricks investments in data transformation with D B T labs, Matillion doing simplified business intelligence hunters. So that's, you know, they're security investment and so forth. So other than our thought that we'd see Databricks I p o last year, this prediction been pretty spot on. So we'll give ourselves an A on that one. Now observability has been a hot topic and we've been covering it for a while with our friends at E T R, particularly Eric Bradley. Our number nine prediction last year was basically that if you're not cloud native and observability, you are gonna be in big trouble. >>So everything guys gotta go cloud native. And that's clearly been the case. Splunk, the big player in the space has been transitioning to the cloud, hasn't always been pretty, as we reported, Datadog real momentum, the elk stack, that's open source model. You got new entrants that we've cited before, like observe, honeycomb, chaos search and others that we've, we've reported on, they're all born in the cloud. So we're gonna take another a on this one, admittedly, yeah, it's a re reasonably easy call, but you gotta have a few of those in the mix. Okay, our last prediction, our number 10 was around events. Something the cube knows a little bit about. We said that a new category of events would emerge as hybrid and that for the most part is happened. So that's gonna be the mainstay is what we said. That pure play virtual events are gonna give way to hi hybrid. >>And the narrative is that virtual only events are, you know, they're good for quick hits, but lousy replacements for in-person events. And you know that said, organizations of all shapes and sizes, they learn how to create better virtual content and support remote audiences during the pandemic. So when we set at pure play is gonna give way to hybrid, we said we, we i we implied or specific or specified that the physical event that v i p experience is going defined. That overall experience and those v i p events would create a little fomo, fear of, of missing out in a virtual component would overlay that serves an audience 10 x the size of the physical. We saw that really two really good examples. Red Hat Summit in Boston, small event, couple thousand people served tens of thousands, you know, online. Second was Google Cloud next v i p event in, in New York City. >>Everything else was, was, was, was virtual. You know, even examples of our prediction of metaverse like immersion have popped up and, and and, and you know, other companies are doing roadshow as we predicted like a lot of companies are doing it. You're seeing that as a major trend where organizations are going with their sales teams out into the regions and doing a little belly to belly action as opposed to the big giant event. That's a definitely a, a trend that we're seeing. So in reviewing this prediction, the grade we gave ourselves is, you know, maybe a bit unfair, it should be, you could argue for a higher grade, but the, but the organization still haven't figured it out. They have hybrid experiences but they generally do a really poor job of leveraging the afterglow and of event of an event. It still tends to be one and done, let's move on to the next event or the next city. >>Let the sales team pick up the pieces if they were paying attention. So because of that, we're only taking a B plus on this one. Okay, so that's the review of last year's predictions. You know, overall if you average out our grade on the 10 predictions that come out to a b plus, I dunno why we can't seem to get that elusive a, but we're gonna keep trying our friends at E T R and we are starting to look at the data for 2023 from the surveys and all the work that we've done on the cube and our, our analysis and we're gonna put together our predictions. We've had literally hundreds of inbounds from PR pros pitching us. We've got this huge thick folder that we've started to review with our yellow highlighter. And our plan is to review it this month, take a look at all the data, get some ideas from the inbounds and then the e t R of January surveys in the field. >>It's probably got a little over a thousand responses right now. You know, they'll get up to, you know, 1400 or so. And once we've digested all that, we're gonna go back and publish our predictions for 2023 sometime in January. So stay tuned for that. All right, we're gonna leave it there for today. You wanna thank Alex Myerson who's on production and he manages the podcast, Ken Schiffman as well out of our, our Boston studio. I gotta really heartfelt thank you to Kristen Martin and Cheryl Knight and their team. They helped get the word out on social and in our newsletters. Rob Ho is our editor in chief over at Silicon Angle who does some great editing for us. Thank you all. Remember all these podcasts are available or all these episodes are available is podcasts. Wherever you listen, just all you do Search Breaking analysis podcast, really getting some great traction there. Appreciate you guys subscribing. I published each week on wikibon.com, silicon angle.com or you can email me directly at david dot valante silicon angle.com or dm me Dante, or you can comment on my LinkedIn post. And please check out ETR AI for the very best survey data in the enterprise tech business. Some awesome stuff in there. This is Dante for the Cube Insights powered by etr. Thanks for watching and we'll see you next time on breaking analysis.

>> Announcer: TheCUBE presents Ignite '22, brought to you by Palo Alto Networks. >> Welcome back to Las Vegas. It's theCUBE covering Palo Alto Networks '22, from the MGM Grand, Lisa Martin with Dave Vellante. Dave, we are going to unpack in the next few minutes what we heard and saw at day one of Palo Alto Networks, Ignite. A lot of great conversations, some great guests on the program today. >> Yeah last event, CUBE event of the year. Probably last major tech event of the year. It's kind of an interesting choice of timing, two weeks after reInvent. But you know, this crowd is it's a lot of like network engineers, SecOps pros. There's not a lot of suits here. I think they were here yesterday, all the partners. >> Yeah. >> We talked to Carl Sunderland about, Hey, these, these guys want to know how do I grow my business? You know, so it was a lot of C level executives talking about their business, and how they partner with Palo Alto to grow. The crowd today is really, you know hardcore security professionals. >> Yeah. >> So we're hearing a story of consolidation. >> Yes. >> No surprise. We've talked about that and reported on it, you know, quite extensively. The one big takeaway, and I want, I came in, as you know, wanting to understand, okay, can you through m and a maintain, you know, build a suite of great, big portfolio and at the same time maintain best of breed? And the answer was consistent. We heard it from Nikesh, we heard it from Nir Zuk. The answer was you can't be best of breed without having that large portfolio, single data lake, you know? Single version of the truth, of there is such a thing. That was interesting, that in security, you have to have that visibility. I would imagine, that's true for a lot of things. Data, see what Snowflake and Databricks are both trying to do, now AWS. So to join, we heard that last week, so that was one of the big takeaways. What were your, some of your thoughts? >> Just impressed with the level of threat intelligence that Unit 42 has done. I mean, we had Wendy Whitmer on, and she was one of the alumni, great guest. The landscape has changed so dramatically. Every business, in any industry, nobody's safe. They have such great intelligence on what's going on with malware, with ransomware, with Smishing, that they're able to get, help organizations on their way to becoming cyber resilient. You know, we've been talking a lot about cyber resiliency lately. I always want to understand, well what does it mean? How do different organizations and customers define it? Can they actually really get there? And Wendy talked about yes, it is a journey, but organizations can achieve cyber resiliency. But they need to partner with Palo Alto Networks to be able to understand the landscape and ensure that they've got security established across their organization, as it's now growingly Multicloud. >> Yeah, she's a blonde-haired Wonder Woman, superhero. I always ask security pros that question. But you know, when you talk to people like Wendy Whitmore, Kevin Mandy is somebody else. And the people at AWS, or the big cloud companies, who are on the inside, looking at the threat intelligence. They have so much data, and they have so much knowledge. They can, they analyze, they could identify the fingerprints of nation states, different, you know, criminal organizations. And the the one thing, I think it was Wendy who said, maybe it was somebody else, I think it was Wendy, that they're they're tearing down and reforming, right? >> Yes. >> After they're discovered. Okay, they pack up and leave. They're like, you know, Oceans 11. >> Yep. >> Okay. And then they recruit them and bring them back in. So that was really fascinating. Nir Zuk, we'd never had him on theCUBE before. He was tremendous founder and and CTO of Palo Alto Networks, very opinionated. You know, very clear thinker, basically saying, look you're SOC is going to be run by AI >> Yeah. >> within the next five years. And machines are going to do things that humans can't do at scale, is really what he was saying. And then they're going to get better at that, and they're going to do other things that you have done well that they haven't done well, and then they're going to do well. And so, this is an interesting discussion about you know, I remember, you know we had an event with MIT. Eric Brynjolfsson and Andy McAfee, they wrote the book "Second Machine Age." And they made the point, machines have always replaced humans. This is the first time ever that machines are replacing humans in cognitive functions. So what does that mean? That means that humans have to rely on, you know, creativity. There's got to be new training, new thinking. So it's not like you're going to be out of a job, you're just going to be doing a different job. >> Right. I thought Nir Zuk did a great job of explaining that. We often hear people that are concerned with machines taking jobs. He did a great job of, and you did a great recap, of articulating the value that both bring, and the opportunities to the humans that the machines actually deliver as well. >> Yeah so, you know, we didn't, we didn't get deep into the products today. Tomorrow we're going to have a little bit more deep dive on products. We did, we had some partners on, AWS came on, talked about their ecosystem. BJ Jenkins so, you know, BJ Jenkins again I mean super senior executive. And if I were Nikesh, he's doing exactly what I would do. Putting him on a plane and saying, go meet with customers, go make rain, right? And that's what he's doing is, he's an individual who really knows how to interact with the C-suite, has driven value, you know, over the years. So they've got that angle goin', they're driving go to market. They've got the technology piece and they've, they got to build out the ecosystem. That I think is the big opportunity for them. You know, if they're going to double as a company, this ecosystem has to quadruple. >> Yeah, yeah. >> In my opinion. And I, we saw the same thing at CrowdStrike. We said the same thing about Service Now in 2013. And so, what's happened is the GSIs, the global system integrators start to get involved. They start to partner with them and then they get to get that flywheel effect. And then there's a supercloud, I think that, you know I think Nir Zuk said, Hey, we are basically building out that, he didn't use the term supercloud. But, we're building out that cross cloud capability. You don't need another stove pipe for the edge. You know, so they got on-prem, they got AWS, Azure, you said you have to, absolutely have to run on Microsoft. 'Cause I don't believe today, right? Today they run on, I heard somebody say they run on AWS and Google. >> Yeah. >> I haven't heard much about Microsoft. >> Right. >> Both AWS and Google are here. Microsoft, the bigger competitor in security, but Nir Zuk was unequivocal. Yes, of course you have to run, you got to run it on an Alibaba cloud. He didn't say that, but if you want to secure the China cloud, you got to run on Alibaba. >> Absolutely. >> And Oracle he said. Didn't mention IBM, but no reason they can't run on IBM's cloud. But unless IBM doesn't want 'em to. >> Well they're very customer focused and customer first. So it'll be interesting to see if customers take them in that direction. >> Well it's a good point, right? If customers say, Hey we want you running in this cloud, they will. And, but he did call out Oracle, which I thought was interesting. And so, Oracle's all about mission critical data, mission critical apps. So, you know, that's a good sign. You know, I mean there's so much opportunity in cyber, but so much confusion. You know, sneak had a raise today. It was a down round, no surprise there. But you know, these companies are going to start getting tight on cash, and you've seen layoffs, right? And so, I dunno who said it, I think it was Carl at the end said in a downturn, the strongest companies come out stronger. And that's generally, generally been the case. That kind of rich get richer. We see that in the last downturn? Yes and no, to a certain extent. It's still all about execution. I mean I think about EMC coming out of the last downturn. They did come out stronger and then they started to rocket, but then look what happened. They couldn't remain independent. They were just using m and a as a technique to hide the warts. You know so, what Nir Zuk said that was most interesting to me is when we acquire, we acquire with the intent of integrating. ServiceNow has a similar philosophy. I think that's why they've been somewhat successful. And Oracle, for sure, has had a similar philosophy. So, and that idea of shifting labor into vendor R and D has always been a winning formula. >> I think we heard that today. Excited for day two tomorrow. We've got some great conversations. We're going to be able to talk with some customers, the chief product officer is on. So we have more great content coming from our last live show over the year. Dave, it's been great co-hosting day one with you. Look forward to doing it tomorrow. >> Yeah, thanks for doing this. >> All right. >> All right. For Dave Vellante, I'm Lisa Martin. You've been watching theCUBE, the leader in live enterprise and emerging tech coverage. See you tomorrow. (gentle music fades)

>> Presenter: theCUBE presents Ignite '22, brought to you by Palo Alto Networks. >> Hey guys and girls. Welcome back to theCube's live coverage at Palo Alto Ignite '22. We're live at the MGM Grand Hotel in beautiful Las Vegas. Lisa Martin here with Dave Vellante. This is day one of our coverage. We've been talking with execs from Palo Alto, Partners, but one of our most exciting things is talking with Founders day. We get to do that next. >> The thing is, it's like I wrote this weekend in my breaking analysis. Understanding the problem in cybersecurity is really easy, but figuring out how to fix it ain't so much. >> It definitely isn't. >> So I'm excited to have Nir here. >> Very excited. Nir Zuk joins us, the founder and CTO of Palo Alto Networks. Welcome, Nir. Great to have you on the program. >> Thank you. >> So Palo Alto Networks, you founded it back in 2005. It's hard to believe that's been 18 years, almost. You did something different, which I want to get into. But tell us, what was it back then? Why did you found this company? >> I thought the world needed another cybersecurity company. I thought it's because there were so many cybersecurity vendors in the world, and just didn't make any sense. This industry has evolved in a very weird way, where every time there was a new challenge, rather than existing vendors dealing with a challenge, you had new vendors dealing with it, and I thought I could put a stop to it, and I think I did. >> You did something differently back in 2005, looking at where you are now, the leader, what was different in your mind back then? >> Yeah. When you found a new company, you have really two good options. There's also a bad option, but we'll skip that. You can either disrupt an existing market, or you can create a new market. So first, I decided to disrupt an existing market, go into an existing market first, network security, then cyber security, and change it. Change the way it works. And like I said, the challenges that every problem had a new vendor, and nobody just stepped back and said, "I think I can solve it with the platform." Meaning, I think I can spend some time not solving a specific problem, but building a platform that then can be used to solve many different problems. And that's what I've done, and that's what Palo Alto Networks has done, and that's where we are today. >> So you look back, you call it now, I think you call it a next gen firewall, but nothing in 2005, can it be next gen? Do you know the Silicon Valley Show? Do you know the show Silicon Valley? >> Oh! Yeah. >> Yeah, of course. >> You got to have a box. But it was a different kind of box- >> Actually. >> Explain that. >> Actually, it's exactly the same thing. You got to have a box. So I actually wanted to call it a necessary evil. Marketing wouldn't go for that. >> No. >> And the reason I wanted to call it a necessary evil, because one of the things that we've done in order to platform our cyber security, again, first network security now, also cloud security, and security operations, is to turn it into a SaaS delivered industry. Today every cyber security professional knows that, when they buy cyber security, they buy usually a SaaS delivered service. Back then, people thought I was crazy to think that customers are going to send their data to their vendor in order to process, and they wanted everything on premise and so on, but I said, "No, customers are going to send information to us for processing, because we have much more processing power than they have." And we needed something in the infrastructure to send us the information. So that's why I wanted to call it the necessary evil. We ended up calling it next generation firewall, which was probably a better term. >> Well, even Veritas. Remember Veritas? They had the no hardware agenda. Even they have a box. So it is like you say, you got to have it. >> It's necessary. >> Okay. You did this, you started this on your own cloud, kind of like Salesforce, ServiceNow. >> Correct. >> Similar now- >> Build your own data centers. >> Build your own data center. Okay, I call it a cloud, but no. >> No, it's the same. There's no cloud, it's just someone else's computer. >> According to Larry Ellison, he was actually probably right about that. But over time, you've had this closer partnership with the public clouds. >> Correct. >> What does that bring you and your customers, and how hard was that to navigate? >> It wasn't that hard for us, because we didn't have that many services. Usually it's harder. Of course, we didn't do a lift and shift, which is their own thing to do with the cloud. We rebuild things for the cloud, and the benefits, of course, are time to market, scale, agility, and in some cases also, cost. >> Yeah, some cases. >> In some cases. >> So you have a sort of a hybrid model today. You still run your own data centers, do you not? >> Very few. >> Really? >> There are very, very few things that we have to do on hardware, like simulating malware and things that cannot be done in a virtual machine, which is pretty much the only option you have in the cloud. They provide bare metal, but doesn't serve our needs. I think that we don't view cloud, and your viewers should not be viewing cloud, as a place where they're going to save money. It's a place where they're going to make money. >> I like that. >> You make much more money, because you're more agile. >> And that's why this conversation is all about, your cost of goods sold they're going to be so high, you're going to have to come back to your own data centers. That's not on your mind right now. What's on your mind is advancing the unit, right? >> Look, my own data center would limit me in scale, would limit my agility. If you want to build something new, you don't have all the PaaS services, the platform as a service, services like database, and AI, and so on. I have to build them myself. It takes time. So yeah, it's going to be cheaper, but I'm not going to be delivering the same thing. So my revenues will be much lower. >> Less top line. What can humans do better than machines? You were talking about your keynote... I'm just going to chat a little bit. You were talking about your keynote. Basically, if you guys didn't see the keynote, that AI is going to run every soc within five years, that was a great prediction that you made. >> Correct. >> And they're going to do things that you can't do today, and then in the future, they're going to do things that you can't... Better than you can do. >> And you just have to be comfortable with that. >> So what do you think humans can do today and in the future better than machines? >> Look, humans can always do better than machines. The human mind can do things that machines cannot do. We are conscious, I don't think machines will be conscious. And you can do things... My point was not that machines can do things that humans cannot do. They can just do it better. The things that humans do today, machines can do better, once machines do that, humans will be free to do things that they don't do today, that machines cannot do. >> Like what? >> Like finding the most difficult, most covert attacks, dealing with the most difficult incidents, things that machines just can't do. Just that today, humans are consumed by finding attacks that machines can find, by dealing with incidents that machines can deal with. It's a waste of time. We leave it to the machines and go and focus on the most difficult problems, and then have the machines learn from you, so that next time or a hundred or a thousand times from now, they can do it themselves, and you focus on the even more difficult. >> Yeah, just like after 9/11, they said that we lack the creativity. That's what humans have, that machines don't, at least today. >> Machines don't. Yeah, look, every airplane has two pilots, even though airplanes have been flying themselves for 30 years now, why do you have two pilots, to do the things that machines cannot do? Like land on the Hudson, right? You always need humans to do the things that machines cannot do. But to leave the things that machines can do to the machines, they'll do it better. >> And autonomous vehicles need breaks. (indistinct) >> In your customer conversations, are customers really grappling with that, are they going, "Yeah, you're right?" >> It depends. It's hard for customers to let go of old habits. First, the habit of buying a hundred different solutions from a hundred different vendors, and you know what? Why would I trust one vendor to do everything, put all my eggs in the same basket? They have all kind of slogans as to why not to do that, even though it's been proven again and again that, doing everything in one system with one brain, versus a hundred systems with a hundred brains, work much better. So that's one thing. The second thing is, we always have the same issue that we've had, I think, since the industrial revolution, of what machines are going to take away my job. No, they're just going to make your job better. So I think that some of our customers are also grappling with that, like, "What do I do if the machines take over?" And of course, like we've said, the machines aren't taking over. They're going to do the benign work, you're going to do the interesting work. You should embrace it. >> When I think about your history as a technology pro, from Check Point, a couple of startups, one of the things that always frustrated you, is when when a larger company bought you out, you ended up getting sucked into the bureaucratic vortex. How do you avoid that at Palo Alto Networks? >> So first, you mean when we acquire company? >> Yes. >> The first thing is that, when we acquire companies, we always acquire for integration. Meaning, we don't just buy something and then leave it on the side, and try to sell it here and there. We integrate it into the core of our products. So that's very important, so that the technology lives, thrives and continues to grow as part of our bigger platform. And I think that the second thing that is very important, from past experience what we've learned, is to put the people that we acquire in key positions. Meaning, you don't buy a company and then put the leader of that company five levels below the CEO. You always put them in very senior positions. Almost always, we have the leaders of the companies that we acquire, be two levels below the CEO, so very senior in the company, so they can influence and make changes. >> So two questions related to that. One is, as you grow your team, can you be both integrated? And second part of the question, can you be both integrated and best of breed? Second part of the question is, do you even have to be? >> So I'll answer it in the third way, which is, I don't think you can be best of breed without being integrated in cybersecurity. And the reason is, again, this split brain that I've mentioned twice. When you have different products do a part of cybersecurity and they don't talk to each other, and they don't share a single brain, you always compromise. You start looking for things the wrong way. I can be a little bit technical here, but please. Take the example of, traditionally you would buy an IDS/IPS, separately from your filtering, separately from DNS security. One of the most important things we do in network security is to find combining control connections. Combining control connections where the adversaries controlling something behind your firewall and is now going around your network, is usually the key heel of the attack. That's why attacks like ransomware, that don't have a commanding control connection, are so difficult to deal with, by the way. So commanding control connections are a key seal of the attacks, and there are three different technologies that deal with it. Neural filtering for neural based commanding control, DNS security for DNS based commanding control, and IDS/IPS for general commanding control. If those are three different products, they'll be doing the wrong things. The oral filter will try to find things that it's not really good at, that the IPS really need to find, and the DN... It doesn't work. It works much better when it's one product doing everything. So I think the choice is not between best of breed and integrated. I think the only choice is integrated, because that's the only way to be best of breed. >> And behind that technology is some kind of realtime data store, I'll call it data lake, database. >> Yeah. >> Whatever. >> It's all driven by the same data. All the URLs, all the domain graph. Everything goes to one big data lake. We collect about... I think we collect about, a few petabytes per day. I don't write the exact number of data. It's all going to the same data lake, and all the intelligence is driven by that. >> So you mentioned in a cheeky comment about, why you founded the company, there weren't enough cybersecurity companies. >> Yeah. >> Clearly the term expansion strategy that Palo Alto Networks has done has been very successful. You've been, as you talked about, very focused on integration, not just from the technology perspective, but from the people perspective as well. >> Correct. >> So why are there still so many cybersecurity companies, and what are you thinking Palo Alto Networks can do to change that? >> So first, I think that there are a lot of cybersecurity companies out there, because there's a lot of money going into cybersecurity. If you look at the number of companies that have been really successful, it's a very small percentage of those cybersecurity companies. And also look, we're not going to be responsible for all the innovation in cybersecurity. We need other people to innovate. It's also... Look, always the question is, "Do you buy something or do you build it yourself?" Now we think we're the smartest people in the world. Of course, we can build everything, but it's not always true that we can build everything. Know that we're the smartest people in the world, for sure. You see, when you are a startup, you live and die by the thing that you build. Meaning if it's good, it works. If it's not good, you die. You run out of money, you shut down, and you just lost four years of your life to this, at least. >> At least. >> When you're a large company, yeah, I can go and find a hundred engineers and hire them. And especially nowadays, it becomes easier, as it became easier, and give them money, and have them go and build the same thing that the startup is building, but they're part of a bigger company, and they'll have more coffee breaks, and they'll be less incentive to go and do that, because the company will survive with or without them. So that's why startups can do things much better, sometimes than larger companies. We can do things better than startups, when it comes to being data driven because we have the data, and nobody can compete against the amount of data that we have. So we have a good combination of finding the right startups that have already built something, already proven that it works with some customers, and of course, building a lot of things internally that we cannot do outside. >> I heard you say in one of the, I dunno, dozens of videos I've listened to you talked to. The industry doesn't need or doesn't want another IoT stovepipe. Okay, I agree. So you got on-prem, AWS, Azure, Google, maybe Alibaba, IoT is going to be all over the place. So can you build, I call it the security super cloud, in other words, a consistent experience with the same policies and edicts across all my estates, irrespective of physical location? Is that technically feasible? Is it what you are trying to do? >> Certainly, what we're trying to do with Prisma Cloud, with our cloud security product, it works across all the clouds that you mentioned, and Oracle as well. It's almost entirely possible. >> Almost. >> Almost. Well, the things that... What you do is you normalize the language that the different cloud scale providers use, into one language. This cloud calls it a S3, and so, AWS calls it S3, and (indistinct) calls it GCS, and so on. So you normalize their terminology, and then build policy using a common terminology that your customers have to get used to. Of course, there are things that are different between the different cloud providers that cannot be normalized, and there, it has to be cloud specific. >> In that instance. So is that, in part, your strategy, is to actually build that? >> Of course. >> And does that necessitate running on all the major clouds? >> Of course. It's not just part of our strategy, it's a major part of our strategy. >> Compulsory. >> Look, as a standalone vendor that is not a cloud provider, we have two advantages. The first one is we're security product, security focused. So we can do much better than them when it comes to security. If you are a AWS, GCP, Azure, and so on, you're not going to put your best people on security, you're going to put them on the core business that you have. So we can do much better. Hey, that's interesting. >> Well, that's not how they talk. >> I don't care how they talk. >> Now that's interesting. >> When something is 4% of your business, you're not going to put it... You're not going to put your best people there. It's just, why would you? You put your best people on 96%. >> That's not driving their revenue. >> Look, it's simple. It's not what we- >> With all due respect. With all due respect. >> So I think we do security much better than them, and they become the good enough, and we become the premium. But certainly, the second thing that give us an advantage and the right to be a standalone security provider, is that we're multicloud, private cloud and all the major cloud providers. >> But they also have a different role. I mean, your role is not the security, the Nitro card or the Graviton chip, or is it? >> They are responsible for securing up to the operating system. We secure everything. >> They do a pretty good job of that. >> No, they do, certainly they have to. If they get bridged at that level, it's not just that one customer is going to suffer, the entire customer base. They have to spend a lot of time and money on it, and frankly, that's where they put their best security people. Securing the infrastructure, not building some cloud security feature. >> Absolutely. >> So Palo Alto Networks is, as we wrap here, on track to nearly double its revenues to nearly seven billion in FY '23, just compared to 2020, you were quoted in the press by saying, "We will be the first $100 billion cyber company." What is next for Palo Alto to achieve that? >> Yeah, so it was Nikesh, our CEO and chairman, that was quoted saying that, "We will double to a hundred billion." I don't think he gave it a timeframe, but what it takes is to double the sales, right? We're at 50 billion market cap right now, so we need to double sales. But in reality, you mentioned that we're growing the turn by doing more and more cybersecurity functions, and taking away pieces. Still, we have a relatively small, even though we're the largest cybersecurity vendor in the world, we have a very low market share that shows you how fragmented the market is. I would also like to point out something that is less known. Part of what we do with AI, is really take the part of the cybersecurity industry, which are service oriented, and that's about 50% of the cybersecurity industry services, and turn it into products. I mean, not all of it. But a good portion of what's provided today by people, and tens of billions of dollars are spent on that, can be done with products. And being one of the very, very few vendors that do that, I think we have a huge opportunity at turning those tens of billions of dollars in human services to AI. >> It's always been a good business taking human labor and translating into R and D, vendor R and D. >> Especially- >> It never fails if you do it well. >> Especially in difficult times, difficult economical times like we are probably experiencing right now around the world. We, not we, but we the world. >> Right, right. Well, congratulations. Coming up on the 18th anniversary. Tremendous amount of success. >> Thank you. >> Great vision, clear vision, STEM expansion strategy, really well underway. We are definitely going to continue to keep our eyes. >> Big company, a hundred billion, that's market capital, so that's a big company. You said you didn't want to work for a big company unless you founded it, is that... >> Unless it acts like a small company. >> There's the caveat. We'll keep our eye on that. >> Thank you very much. >> It's such a pleasure having you on. >> Thank you. >> Same here, thank you. >> All right, for our guests and for Dave Vellante, I'm Lisa Martin. You're watching theCUBE, the leader in live emerging and enterprise tech coverage. (upbeat music)

>>Hey everyone. Welcome back to the Cube's live coverage of AWS Reinvent 2022. This is day one, I should say evening one of three and a half days of wall to wall coverage on the cube. Lisa Martin here with Dave Ante. Dave, we love talking about data, but the most important thing about data is if there's a breach, which are happening more and more frequently, that you can get it back. So data backup, data protection, data resiliency, hugely >>Important. Well, it used to be you got snake bit and then you closed the barn door after the horse ran away. Now I think people are a lot more aware that they gotta protect their data and be proactive about it. It can't just be an afterthought. >>It can't be an afterthought. We've got the CTO of own backup here. We're gonna be talking about that Adrian Consul. Adrian, welcome to the Cube. >>Thanks for having me. >>Talk a little bit about own backup. The what is unique about it? >>So we are the leading SaaS data protection vendor. We've built a business based on the fact that SAS has become a center of gravity for a lot of companies. Now, a lot of people have moved with digital transformation and more recently with the covid effects to digitize their business. Our platform is powered by aws. We've got 5,000 plus customers that trust what we do and to look after their data. We help them with resiliency, compliance, security, and we do it for people who are using Salesforce, ServiceNow, and Microsoft Dynamics 365 people >>Are gonna say, wait a minute, my data in the cloud isn't already backed up. Why do I Right. That's what they're gonna say. So how do you >>Respond? Yes. Lots of people say that. That is exactly right. So what people are beginning to realize much more is that there's actually a shared responsibility model between your SaaS provider and yourselves. And you know, the SaaS providers do a phenomenal job of giving you disaster recovery, a database copy, networking infrastructure, a bunch of security controls at that level. But they're pretty frank about the data you put in there is your data, right? And just that it's up to you to put the data in there. It's also up to you to keep it in there. And that's not so easy when you've got lots of integrations. You've got users running around in the applications, et cetera. So yeah, the heart of it is, it's your data, you put it in there, you better be looking after it too. >>That's so important for customers to understand what is Salesforce's responsibility? What's my responsibility to the really nail that? What are some of the main challenges as we see the cybersecurity landscape has changed so much in the last couple of years? Ransomware is now a, when it's gonna happen to us. How often, what's gonna be the significance? What are some of the main challenges that you're talking with customers about these days? >>So really on the data side, it definitely hinges around ransomware. But I would also say when you think about what digital transformation has done for customers, moved you to a world where you've gotta be on 24 7, right? You can't afford to have systems down, whether that's your public website or even things your salespeople are using. And so on the, on the data side, we talk a lot with our customers about really recovery. Not so much about backup. Backup is in our name, but our product is called Recover. And there's a reason for that. We're trying to focus on how can we help customers quickly get back to a good state when they've had an incident. So that's kind of the data side of it. On the security side of it, it's really about how do they manage all the controls that SaaS providers now give them. >>Make sure the right people in their organization can see the right data and the data. They should not be able to see the data they shouldn't be able to see. And that's just getting increasingly complex, really anchored around the fact that the volume of the data is growing, the complexity of that data is growing and really the sensitivity of that data is growing, right? When you think about all the data privacy rules, 10 years ago we didn't care about keeping a whole bunch of data around. Now you've kind of gotta get rid of it. So you've actually gotta manage it through its lifecycle. >>So the shared responsibility model has applied to data protection is, is kind of an interesting topic cuz you always think about it for security and I know security and data protection are these adjacencies, but it's a complicated situation cuz you've got shared responsibility models now across multiple clouds. It's gotta be way more complicated across SaaS because you've got different policies, you've got a lot more SaaS than you have. There's three clouds, four, if you put in Alibaba, you know, and yeah, I know this hosting and Oracle and IBM, et cetera, but hyperscalers and so, but there's dozens if not hundreds of SaaS products at a company. So are you able to create a consistent experience and, and for your customers across all those, now of course, I know you're not doing hundreds and thousands of SaaS products, but you got, you know, pretty big ones here. ServiceNow, Salesforce, right? 365. Let's start >>There. So, so consistency we are hoping will come honestly where the industry is right now. It's getting, getting each one in a state where you are comfortable with it, >>Right? Get it protected. >>Yeah. Take a sales force. A typical sales force environment right now has a survey we did recently, about 2000 fields that have sensitive data in it in some way, shape or form. You've couple that with about 80, 85% of the users can see some fields that are sensitive. How you manage that matrix is, is just really hard. And that's part of what our secure product brings to the table, helps you understand who can see what and why they can see it. >>So where are your customer conversations these days? Are you talking to CIOs and CISOs? Is this, is this at that level >>It for some of our customers? Yes, it absolutely gets there. The, the real core of our discussion is the guy who owns and runs the sales technology, for example, right? Or the ServiceNow technology or typically a center of excellence. Those have been, those have been a key way for us to help an organization understand what the risks are, what's necessary, what they're having to do given that they don't have a backup now and have those, those shared responsibility model conversations. That's kind of where >>It starts. Are you finding that most customers are not backing up Salesforce, for example, or ServiceNow? Or are they switching from a competitor over to own back? >>Sad to say that it's mostly not. Yeah, it's, it's predominantly, I thought my cloud provider had me covered for that. >>So the market is huge. Yes. Massive opportunity. Yeah. >>Yeah. If you think of the number of Salesforce instances, not ignoring ServiceNow and Dynamics for a moment, Salesforce talks about, I don't know, 150,000 customers somewhere in that mark and we have 500 of them. >>So how do you get the first penguin off the iceberg? What's the sort of customer conversation like just in terms of, you know, educating them and sending them and, and kind of pushing 'em over the edge so that they actually do start protecting their data? >>Yeah, so, so sadly it sometimes starts with, I had a data loss, I spent weeks working at it, I got 75% of my data back, but not all of it. And that's a real customer quote. And in other cases it's, sorry. In other cases it's how do we, you know, how are you thinking about your sales source environment, particularly customers that have a lot of them, how sensitive is the data? How critical is the data in there? What are you doing to protect it? Today we have some people doing, doing weekly exports, which Salesforce provides. It's a manual step. The first penguin off the iceberg, as you say, it's kind of to say, Hey, well why didn't you automate that? Right? Don't have to rely on somebody on a Tuesday pulling the data down. So that's, those are places where it starts. >>Yeah. So, you know, Lisa, I was saying earlier that, you know, it closed the barn door, right? And that's, that's essentially what Adrian's saying is you've, you've got, you basically gotta look for that customer that's been snake bitten. Yeah. But generally speaking, I feel like there's more awareness. I was gonna ask you, you know, in this economic climate is, is data protection recession proof? And I think it's, it's not right. People sort of, but at the same time, if you're not proactive about it, you really could hurt your business. Absolutely. So what, what are your thoughts on customers getting more efficient with regard to their, their data estate, their data protection? Can you turn it into a positive? >>I think, I think it absolutely is a positive. Obviously we're in an environment where CIOs are having to look at every penny they're spending. But if you think about what you're using the data for, you're making business decisions based on this data every day. Your, your entire organization is making business decisions. So if you've got missing data or inaccurate data, you're making suboptimal decisions, right? So that comes back to data protection, comes back to brand reputation. Yes. And it comes back to how quickly can you get the data back into the shape you need it to be. And that again, is why we focus on the recovery side of the equation, not just the backup side. Right. Sorry. I would also say that in these recession bit times you've got fewer people doing as much work as you had before that raises the chance of errors. And we see across our customer base 50% of the data corruption or or data loss occurrences happen cause a human did something by mistake. Yeah, sure. And if you up the, the stress of those humans, you're gonna get more errors. >>Should you, when you're talking with IT professionals or maybe sales leaders, should it be thinking differently about spend for data protection versus general spend? Given that the whole point is to be able to recover data when something happens? >>I think you have to think about it from a kind of a risk and a business continuity perspective, right? Data protection tangibly reduces your business risk, right? It gets you back up faster. It, it helps you stay running. It helps ensure that the right people have access to the right data and from a secure standpoint and, and all of those just lower your risk. And if you're having discussions as CIOs should be with their business counterparts around business continuity, with the criticality of the data that's in Salesforce and these other SaaS applications today, I think it's pretty obvious that, that you should have a strong data protection strategy around >>It. Absolutely. >>Your business is at >>Risk, right? And nobody wants to be the next headline. No. My last question for you, Adrian, is if there was a billboard near your headquarters, what's that? What would it say? What's that tagline about own backup that really nails it home? >>I think it's, nobody operating in the cloud should ever lose data and that's what we're here to do. >>Excellent. Adrian, it's been a pleasure having you on the program. Thank you for talking with David, me, great talking to you about and back up what you guys are doing and really how organizations need to be very aware of that shared responsibility model. It sounds like you guys are well on your way to helping them understand that. We appreciate your time. >>Thank you both. Thank you. Best of luck. >>Appreciate it. Thank our pleasure. For our guest and Dave Ante, I'm Lisa Martin. You're watching The Cube, the leader in emerging and enterprise tech coverage.

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 the ascendancy of AWS under the leadership of Andy jassy was marked by a tsunami of data and corresponding cloud services to leverage that data now those Services they mainly came in the form of Primitives I.E basic building blocks that were used by developers to create more sophisticated capabilities AWS in the 2020s being led by CEO Adam solipski will be marked by four high-level Trends in our opinion one A Rush of data that will dwarf anything we've previously seen two a doubling or even tripling down on the basic elements of cloud compute storage database security Etc three a greater emphasis on end-to-end integration of AWS services to simplify and accelerate customer adoption of cloud and four significantly deeper business integration of cloud Beyond it as an underlying element of organizational operations hello and welcome to this week's wikibon Cube insights powered by ETR in this breaking analysis we extract and analyze nuggets from John furrier's annual sit-down with the CEO of AWS we'll share data from ETR and other sources to set the context for the market and competition in cloud and we'll give you our glimpse of what to expect at re invent in 2022. now before we get into the core of our analysis Alibaba has announced earnings they always announced after the big three you know a month later and we've updated our Q3 slash November hyperscale Computing forecast for the year as seen here and we're going to spend a lot of time on this as most of you have seen the bulk of it already but suffice to say alibaba's cloud business is hitting that same macro Trend that we're seeing across the board but a more substantial slowdown than we expected and more substantial than its peers they're facing China headwinds they've been restructuring its Cloud business and it's led to significantly slower growth uh in in the you know low double digits as opposed to where we had it at 15 this puts our year-end estimates for 2022 Revenue at 161 billion still a healthy 34 growth with AWS surpassing 80 billion in 2022 Revenue now on a related note one of the big themes in Cloud that we've been reporting on is how customers are optimizing their Cloud spend it's a technique that they use and when the economy looks a little shaky and here's a graphic that we pulled from aws's website which shows the various pricing plans at a high level as you know they're much more granular than that and more sophisticated but Simplicity we'll just keep it here basically there are four levels first one here is on demand I.E pay by the drink now we're going to jump down to what we've labeled as number two spot instances that's like the right place at the right time I can use that extra capacity in the moment the third is reserved instances or RIS where I pay up front to get a discount and the fourth is sort of optimized savings plans where customers commit to a one or three year term and for a better price now you'll notice we labeled the choices in a different order than AWS presented them on its website and that's because we believe that the order that we chose is the natural progression for customers this started on demand they maybe experiment with spot instances they move to reserve instances when the cloud bill becomes too onerous and if you're large enough you lock in for one or three years okay the interesting thing is the order in which AWS presents them we believe that on-demand accounts for the majority of AWS customer spending now if you think about it those on-demand customers they're also at risk customers yeah sure there's some switching costs like egress and learning curve but many customers they have multiple clouds and they've got experience and so they're kind of already up to a learning curve and if you're not married to AWS with a longer term commitment there's less friction to switch now AWS here presents the most attractive plan from a financial perspective second after on demand and it's also the plan that makes the greatest commitment from a lock-in standpoint now In fairness to AWS it's also true that there is a trend towards subscription-based pricing and we have some data on that this chart is from an ETR drill down survey the end is 300. pay attention to the bars on the right the left side is sort of busy but the pink is subscription and you can see the trend upward the light blue is consumption based or on demand based pricing and you can see there's a steady Trend toward subscription now we'll dig into this in a later episode of Breaking analysis but we'll share with you a little some tidbits with the data that ETR provides you can select which segment is and pass or you can go up the stack Etc but so when you choose is and paths 44 of customers either prefer or are required to use on-demand pricing whereas around 40 percent of customers say they either prefer or are required to use subscription pricing again that's for is so now the further mu you move up the stack the more prominent subscription pricing becomes often with sixty percent or more for the software-based offerings that require or prefer subscription and interestingly cyber security tracks along with software at around 60 percent that that prefer subscription it's likely because as with software you're not shutting down your cyber protection on demand all right let's get into the expectations for reinvent and we're going to start with an observation in data in this 2018 book seeing digital author David michella made the point that whereas most companies apply data on the periphery of their business kind of as an add-on function successful data companies like Google and Amazon and Facebook have placed data at the core of their operations they've operationalized data and they apply machine intelligence to that foundational element why is this the fact is it's not easy to do what the internet Giants have done very very sophisticated engineering and and and cultural discipline and this brings us to reinvent 2022 in the future of cloud machine learning and AI will increasingly be infused into applications we believe the data stack and the application stack are coming together as organizations build data apps and data products data expertise is moving from the domain of Highly specialized individuals to Everyday business people and we are just at the cusp of this trend this will in our view be a massive theme of not only re invent 22 but of cloud in the 2020s the vision of data mesh We Believe jamachtagani's principles will be realized in this decade now what we'd like to do now is share with you a glimpse of the thinking of Adam solipsky from his sit down with John Furrier each year John has a one-on-one conversation with the CEO of AWS AWS he's been doing this for years and the outcome is a better understanding of the directional thinking of the leader of the number one Cloud platform so we're now going to share some direct quotes I'm going to run through them with some commentary and then bring in some ETR data to analyze the market implications here we go this is from solipsky quote I.T in general and data are moving from departments into becoming intrinsic parts of how businesses function okay we're talking here about deeper business integration let's go on to the next one quote in time we'll stop talking about people who have the word analyst we inserted data he meant data data analyst in their title rather will have hundreds of millions of people who analyze data as part of their day-to-day job most of whom will not have the word analyst anywhere in their title we're talking about graphic designers and pizza shop owners and product managers and data scientists as well he threw that in I'm going to come back to that very interesting so he's talking about here about democratizing data operationalizing data next quote customers need to be able to take an end-to-end integrated view of their entire data Journey from ingestion to storage to harmonizing the data to being able to query it doing business Intelligence and human-based Analysis and being able to collaborate and share data and we've been putting together we being Amazon together a broad Suite of tools from database to analytics to business intelligence to help customers with that and this last statement it's true Amazon has a lot of tools and you know they're beginning to become more and more integrated but again under jassy there was not a lot of emphasis on that end-to-end integrated view we believe it's clear from these statements that solipsky's customer interactions are leading him to underscore that the time has come for this capability okay continuing quote if you have data in one place you shouldn't have to move it every time you want to analyze that data couldn't agree more it would be much better if you could leave that data in place avoid all the ETL which has become a nasty three-letter word more and more we're building capabilities where you can query that data in place end quote okay this we see a lot in the marketplace Oracle with mySQL Heatwave the entire Trend toward converge database snowflake [ __ ] extending their platforms into transaction and analytics respectively and so forth a lot of the partners are are doing things as well in that vein let's go into the next quote the other phenomenon is infusing machine learning into all those capabilities yes the comments from the michelleographic come into play here infusing Ai and machine intelligence everywhere next one quote it's not a data Cloud it's not a separate Cloud it's a series of broad but integrated capabilities to help you manage the end-to-end life cycle of your data there you go we AWS are the cloud we're going to come back to that in a moment as well next set of comments around data very interesting here quote data governance is a huge issue really what customers need is to find the right balance of their organization between access to data and control and if you provide too much access then you're nervous that your data is going to end up in places that it shouldn't shouldn't be viewed by people who shouldn't be viewing it and you feel like you lack security around that data and by the way what happens then is people overreact and they lock it down so that almost nobody can see it it's those handcuffs there's data and asset are reliability we've talked about that for years okay very well put by solipsky but this is a gap in our in our view within AWS today and we're we're hoping that they close it at reinvent it's not easy to share data in a safe way within AWS today outside of your organization so we're going to look for that at re invent 2022. now all this leads to the following statement by solipsky quote data clean room is a really interesting area and I think there's a lot of different Industries in which clean rooms are applicable I think that clean rooms are an interesting way of enabling multiple parties to share and collaborate on the data while completely respecting each party's rights and their privacy mandate okay again this is a gap currently within AWS today in our view and we know snowflake is well down this path and databricks with Delta sharing is also on this curve so AWS has to address this and demonstrate this end-to-end data integration and the ability to safely share data in our view now let's bring in some ETR spending data to put some context around these comments with reference points in the form of AWS itself and its competitors and partners here's a chart from ETR that shows Net score or spending momentum on the x-axis an overlap or pervasiveness in the survey um sorry let me go back up the net scores on the y-axis and overlap or pervasiveness in the survey is on the x-axis so spending momentum by pervasiveness okay or should have share within the data set the table that's inserted there with the Reds and the greens that informs us to how the dots are positioned so it's Net score and then the shared ends are how the plots are determined now we've filtered the data on the three big data segments analytics database and machine learning slash Ai and we've only selected one company with fewer than 100 ends in the survey and that's databricks you'll see why in a moment the red dotted line indicates highly elevated customer spend at 40 percent now as usual snowflake outperforms all players on the y-axis with a Net score of 63 percent off the charts all three big U.S cloud players are above that line with Microsoft and AWS dominating the x-axis so very impressive that they have such spending momentum and they're so large and you see a number of other emerging data players like rafana and datadog mongodbs there in the mix and then more established players data players like Splunk and Tableau now you got Cisco who's gonna you know it's a it's a it's a adjacent to their core networking business but they're definitely into you know the analytics business then the really established players in data like Informatica IBM and Oracle all with strong presence but you'll notice in the red from the momentum standpoint now what you're going to see in a moment is we put red highlights around databricks Snowflake and AWS why let's bring that back up and we'll explain so there's no way let's bring that back up Alex if you would there's no way AWS is going to hit the brakes on innovating at the base service level what we call Primitives earlier solipsky told Furrier as much in their sit down that AWS will serve the technical user and data science Community the traditional domain of data bricks and at the same time address the end-to-end integration data sharing and business line requirements that snowflake is positioned to serve now people often ask Snowflake and databricks how will you compete with the likes of AWS and we know the answer focus on data exclusively they have their multi-cloud plays perhaps the more interesting question is how will AWS compete with the likes of Specialists like Snowflake and data bricks and the answer is depicted here in this chart AWS is going to serve both the technical and developer communities and the data science audience and through end-to-end Integrations and future services that simplify the data Journey they're going to serve the business lines as well but the Nuance is in all the other dots in the hundreds or hundreds of thousands that are not shown here and that's the AWS ecosystem you can see AWS has earned the status of the number one Cloud platform that everyone wants to partner with as they say it has over a hundred thousand partners and that ecosystem combined with these capabilities that we're discussing well perhaps behind in areas like data sharing and integrated governance can wildly succeed by offering the capabilities and leveraging its ecosystem now for their part the snowflakes of the world have to stay focused on the mission build the best products possible and develop their own ecosystems to compete and attract the Mind share of both developers and business users and that's why it's so interesting to hear solipski basically say it's not a separate Cloud it's a set of integrated Services well snowflake is in our view building a super cloud on top of AWS Azure and Google when great products meet great sales and marketing good things can happen so this will be really fun to watch what AWS announces in this area at re invent all right one other topic that solipsky talked about was the correlation between serverless and container adoption and you know I don't know if this gets into there certainly their hybrid place maybe it starts to get into their multi-cloud we'll see but we have some data on this so again we're talking about the correlation between serverless and container adoption but before we get into that let's go back to 2017 and listen to what Andy jassy said on the cube about serverless play the clip very very earliest days of AWS Jeff used to say a lot if I were starting Amazon today I'd have built it on top of AWS we didn't have all the capability and all the functionality at that very moment but he knew what was coming and he saw what people were still able to accomplish even with where the services were at that point I think the same thing is true here with Lambda which is I think if Amazon were starting today it's a given they would build it on the cloud and I think we with a lot of the applications that comprise Amazon's consumer business we would build those on on our serverless capabilities now we still have plenty of capabilities and features and functionality we need to add to to Lambda and our various serverless services so that may not be true from the get-go right now but I think if you look at the hundreds of thousands of customers who are building on top of Lambda and lots of real applications you know finra has built a good chunk of their market watch application on top of Lambda and Thompson Reuters has built you know one of their key analytics apps like people are building real serious things on top of Lambda and the pace of iteration you'll see there will increase as well and I really believe that to be true over the next year or two so years ago when Jesse gave a road map that serverless was going to be a key developer platform going forward and so lipsky referenced the correlation between serverless and containers in the Furrier sit down so we wanted to test that within the ETR data set now here's a screen grab of The View across 1300 respondents from the October ETR survey and what we've done here is we've isolated on the cloud computing segment okay so you can see right there cloud computing segment now we've taken the functions from Google AWS Lambda and Microsoft Azure functions all the serverless offerings and we've got Net score on the vertical axis we've got presence in the data set oh by the way 440 by the way is highly elevated remember that and then we've got on the horizontal axis we have the presence in the data center overlap okay that's relative to each other so remember 40 all these guys are above that 40 mark okay so you see that now what we're going to do this is just for serverless and what we're going to do is we're going to turn on containers to see the correlation and see what happens so watch what happens when we click on container boom everything moves to the right you can see all three move to the right Google drops a little bit but all the others now the the filtered end drops as well so you don't have as many people that are aggressively leaning into both but all three move to the right so watch again containers off and then containers on containers off containers on so you can see a really major correlation between containers and serverless okay so to get a better understanding of what that means I call my friend and former Cube co-host Stu miniman what he said was people generally used to think of VMS containers and serverless as distinctly different architectures but the lines are beginning to blur serverless makes things simpler for developers who don't want to worry about underlying infrastructure as solipsky and the data from ETR indicate serverless and containers are coming together but as Stu and I discussed there's a spectrum where on the left you have kind of native Cloud VMS in the middle you got AWS fargate and in the rightmost anchor is Lambda AWS Lambda now traditionally in the cloud if you wanted to use containers developers would have to build a container image they have to select and deploy the ec2 images that they or instances that they wanted to use they have to allocate a certain amount of memory and then fence off the apps in a virtual machine and then run the ec2 instances against the apps and then pay for all those ec2 resources now with AWS fargate you can run containerized apps with less infrastructure management but you still have some you know things that you can you can you can do with the with the infrastructure so with fargate what you do is you'd build the container images then you'd allocate your memory and compute resources then run the app and pay for the resources only when they're used so fargate lets you control the runtime environment while at the same time simplifying the infrastructure management you gotta you don't have to worry about isolating the app and other stuff like choosing server types and patching AWS does all that for you then there's Lambda with Lambda you don't have to worry about any of the underlying server infrastructure you're just running code AS functions so the developer spends their time worrying about the applications and the functions that you're calling the point is there's a movement and we saw in the data towards simplifying the development environment and allowing the cloud vendor AWS in this case to do more of the underlying management now some folks will still want to turn knobs and dials but increasingly we're going to see more higher level service adoption now re invent is always a fire hose of content so let's do a rapid rundown of what to expect we talked about operate optimizing data and the organization we talked about Cloud optimization there'll be a lot of talk on the show floor about best practices and customer sharing data solipsky is leading AWS into the next phase of growth and that means moving beyond I.T transformation into deeper business integration and organizational transformation not just digital transformation organizational transformation so he's leading a multi-vector strategy serving the traditional peeps who want fine-grained access to core services so we'll see continued Innovation compute storage AI Etc and simplification through integration and horizontal apps further up to stack Amazon connect is an example that's often cited now as we've reported many times databricks is moving from its stronghold realm of data science into business intelligence and analytics where snowflake is coming from its data analytics stronghold and moving into the world of data science AWS is going down a path of snowflake meet data bricks with an underlying cloud is and pass layer that puts these three companies on a very interesting trajectory and you can expect AWS to go right after the data sharing opportunity and in doing so it will have to address data governance they go hand in hand okay price performance that is a topic that will never go away and it's something that we haven't mentioned today silicon it's a it's an area we've covered extensively on breaking analysis from Nitro to graviton to the AWS acquisition of Annapurna its secret weapon new special specialized capabilities like inferential and trainium we'd expect something more at re invent maybe new graviton instances David floyer our colleague said he's expecting at some point a complete system on a chip SOC from AWS and maybe an arm-based server to eventually include high-speed cxl connections to devices and memories all to address next-gen applications data intensive applications with low power requirements and lower cost overall now of course every year Swami gives his usual update on machine learning and AI building on Amazon's years of sagemaker innovation perhaps a focus on conversational AI or a better support for vision and maybe better integration across Amazon's portfolio of you know large language models uh neural networks generative AI really infusing AI everywhere of course security always high on the list that reinvent and and Amazon even has reinforce a conference dedicated to it uh to security now here we'd like to see more on supply chain security and perhaps how AWS can help there as well as tooling to make the cio's life easier but the key so far is AWS is much more partner friendly in the security space than say for instance Microsoft traditionally so firms like OCTA and crowdstrike in Palo Alto have plenty of room to play in the AWS ecosystem we'd expect of course to hear something about ESG it's an important topic and hopefully how not only AWS is helping the environment that's important but also how they help customers save money and drive inclusion and diversity again very important topics and finally come back to it reinvent is an ecosystem event it's the Super Bowl of tech events and the ecosystem will be out in full force every tech company on the planet will have a presence and the cube will be featuring many of the partners from the serial floor as well as AWS execs and of course our own independent analysis so you'll definitely want to tune into thecube.net and check out our re invent coverage we start Monday evening and then we go wall to wall through Thursday hopefully my voice will come back we have three sets at the show and our entire team will be there so please reach out or stop by and say hello all right we're going to leave it there for today many thanks to Stu miniman and David floyer for the input to today's episode of course John Furrier for extracting the signal from the noise and a sit down with Adam solipski thanks to Alex Meyerson who was on production and manages the podcast Ken schiffman as well Kristen Martin and Cheryl Knight helped get the word out on social and of course in our newsletters Rob hoef is our editor-in-chief over at siliconangle does some great editing thank thanks to all of you remember all these episodes are available as podcasts wherever you listen you can pop in the headphones go for a walk just search breaking analysis podcast I published each week on wikibon.com at siliconangle.com or you can email me at david.valante at siliconangle.com or DM me at di vallante or please comment on our LinkedIn posts and do check out etr.ai for the best survey data in the Enterprise Tech business this is Dave vellante for the cube insights powered by ETR thanks for watching we'll see it reinvent or we'll see you next time on breaking analysis [Music]

(outro music) >> Hey, I'm John Furrier, here with an exclusive interview with Ali Ghodsi, who's the CEO of Databricks. Ali, great to see you. Preview for reinvent. We're going to launch this story, exclusive Databricks material on the notes, after the keynotes prior to the keynotes and after the keynotes that reinvent. So great to see you. You know, you've been a partner of AWS for a very, very long time. I think five years ago, I think I first interviewed you, you were one of the first to publicly declare that this was a place to build a company on and not just post an application, but refactor capabilities to create, essentially a platform in the cloud, on the cloud. Not just an ISV; Independent Software Vendor, kind of an old term, we're talking about real platform like capability to change the game. Can you talk about your experience as an AWS partner? >> Yeah, look, so we started in 2013. I swiped my personal credit card on AWS and some of my co-founders did the same. And we started building. And we were excited because we just thought this is a much better way to launch a company because you can just much faster get time to market and launch your thing and you can get the end users much quicker access to the thing you're building. So we didn't really talk to anyone at AWS, we just swiped a credit card. And eventually they told us, "Hey, do you want to buy extra support?" "You're asking a lot of advanced questions from us." "Maybe you want to buy our advanced support." And we said, no, no, no, no. We're very advanced ourselves, we know what we're doing. We're not going to buy any advanced support. So, you know, we just built this, you know, startup from nothing on AWS without even talking to anyone there. So at some point, I think around 2017, they suddenly saw this company with maybe a hundred million ARR pop up on their radar and it's driving massive amounts of compute, massive amounts of data. And it took a little bit in the beginning just us to get to know each other because as I said, it's like we were not on their radar and we weren't really looking, we were just doing our thing. And then over the years the partnership has deepened and deepened and deepened and then with, you know, Andy (indistinct) really leaning into the partnership, he mentioned us at Reinvent. And then we sort of figured out a way to really integrate the two service, the Databricks platform with AWS . And today it's an amazing partnership. You know, we directly connected with the general managers for the services. We're connected at the CEO level, you know, the sellers get compensated for pushing Databricks, we're, we have multiple offerings on their marketplace. We have a native offering on AWS. You know, we're prominently always sort of marketed and you know, we're aligned also vision wise in what we're trying to do. So yeah, we've come a very, very long way. >> Do you consider yourself a SaaS app or an ISV or do you see yourself more of a platform company because you have customers. How would you categorize your category as a company? >> Well, it's a data platform, right? And actually the, the strategy of the Databricks is take what's otherwise five, six services in the industry or five, six different startups, but do them as part of one data platform that's integrated. So in one word, the strategy of data bricks is "unification." We call it the data lake house. But really the idea behind the data lake house is that of unification, or in more words it's, "The whole is greater than the sum of its parts." So you could actually go and buy five, six services out there or actually use five, six services from the cloud vendors, stitch it together and it kind of resembles Databricks. Our power is in doing those integrated, together in a way in which it's really, really easy and simple to use for end users. So yeah, we're a data platform. I wouldn't, you know, ISV that's a old term, you know, Independent Software Vendor. You know, I think, you know, we have actually a whole slew of ISVs on top of Databricks, that integrate with our platform. And you know, in our marketplace as well as in our partner connect, we host those ISVs that then, you know, work on top of the data that we have in the Databricks, data lake house. >> You know, I think one of the things your journey has been great to document and watch from the beginning. I got to give you guys credit over there and props, congratulations. But I think you're the poster child as a company to what we see enterprises doing now. So go back in time when you guys swiped a credit card, you didn't need attending technical support because you guys had brains, you were refactoring, rethinking. It wasn't just banging out software, you had, you were doing some complex things. It wasn't like it was just write some software hosted on server. It was really a lot more. And as a result your business worth billions of dollars. I think 38 billion or something like that, big numbers, big numbers of great revenue growth as well, billions in revenue. You have customers, you have an ecosystem, you have data applications on top of Databricks. So in a way you're a cloud on top of the cloud. So is there a cloud on top of the cloud? So you have ISVs, Amazon has ISVs. Can you take us through what this means and at this point in history, because this seems to be an advanced version of benefits of platforming and refactoring, leveraging say AWS. >> Yeah, so look, when we started, there was really only one game in town. It was AWS. So it was one cloud. And the strategy of the company then was, well Amazon had this beautiful set of services that they're building bottom up, they have storage, compute, networking, and then they have databases and so on. But it's a lot of services. So let us not directly compete with AWS and try to take out one of their services. Let's not do that because frankly we can't. We were not of that size. They had the scale, they had the size and they were the only cloud vendor in town. So our strategy instead was, let's do something else. Let's not compete directly with say, a particular service they're building, let's take a different strategy. What if we had a unified holistic data platform, where it's just one integrated service end to end. So think of it as Microsoft office, which contains PowerPoint, and Word, and Excel and even Access, if you want to use it. What if we build that and AWS has this really amazing knack for releasing things, you know services, lots of them, every reinvent. And they're sort of a DevOps person's dream and you can stitch these together and you know you have to be technical. How do we elevate that and make it simpler and integrate it? That was our original strategy and it resonated with a segment of the market. And the reason it worked with AWS so that we wouldn't butt heads with AWS was because we weren't a direct replacement for this service or for that service, we were taking a different approach. And AWS, because credit goes to them, they're so customer obsessed, they would actually do what's right for the customer. So if the customer said we want this unified thing, their sellers would actually say, okay, so then you should use Databricks. So they truly are customer obsessed in that way. And I really mean it, John. Things have changed over the years. They're not the only cloud anymore. You know, Azure is real, GCP is real, there's also Alibaba. And now over 70% of our customers are on more than one cloud. So now what we hear from them is, not only want, do we want a simplified, unified thing, but we want it also to work across the clouds. Because those of them that are seriously considering multiple clouds, they don't want to use a service on cloud one and then use a similar service on cloud two. But it's a little bit different. And now they have to do twice the work to make it work. You know, John, it's hard enough as it is, like it's this data stuff and analytics. It's not a walk in the park, you know. You hire an administrator in the back office that clicks a button and its just, now you're a data driven digital transformed company. It's hard. If you now have to do it again on the second cloud with different set of services and then again on a third cloud with a different set of services. That's very, very costly. So the strategy then has changed that, how do we take that unified simple approach and make it also the same and standardize across the clouds, but then also integrate it as far down as we can on each of the clouds. So that you're not giving up any of the benefits that the particular cloud has. >> Yeah, I think one of the things that we see, and I want get your reaction to this, is this rise of the super cloud as we call it. I think you were involved in the Sky paper that I saw your position paper came out after we had introduced Super Cloud, which is great. Congratulations to the Berkeley team, wearing the hat here. But you guys are, I think a driver of this because you're creating the need for these things. You're saying, okay, we went on one cloud with AWS and you didn't hide that. And now you're publicly saying there's other clouds too, increased ham for your business. And customers have multiple clouds in their infrastructure for the best of breed that they have. Okay, get that. But there's still a challenge around the innovation, growth that's still around the corner. We still have a supply chain problem, we still have skill gaps. You know, you guys are unique at Databricks as other these big examples of super clouds that are developing. Enterprises don't have the Databricks kind of talent. They need, they need turnkey solutions. So Adam and the team at Amazon are promoting, you know, more solution oriented approaches higher up on the stack. You're starting to see kind of like, I won't say templates, but you know, almost like application specific headless like, low code, no code capability to accelerate clients who are wanting to write code for the modern error. Right, so this kind of, and then now you, as you guys pointed out with these common services, you're pushing the envelope. So you're saying, hey, I need to compete, I don't want to go to my customers and have them to have a staff or this cloud and this cloud and this cloud because they don't have the staff. Or if they do, they're very unique. So what's your reaction? Because this kind is the, it kind of shows your leadership as a partner of AWS and the clouds, but also highlights I think what's coming. But you share your reaction. >> Yeah, look, it's, first of all, you know, I wish I could take credit for this but I can't because it's really the customers that have decided to go on multiple clouds. You know, it's not Databricks that you know, push this or some other vendor, you know, that, Snowflake or someone who pushed this and now enterprises listened to us and they picked two clouds. That's not how it happened. The enterprises picked two clouds or three clouds themselves and we can get into why, but they did that. So this largely just happened in the market. We as data platforms responded to what they're then saying, which is they're saying, "I don't want to redo this again on the other cloud." So I think the writing is on the wall. I think it's super obvious what's going to happen next. They will say, "Any service I'm using, it better work exactly the same on all the clouds." You know, that's what's going to happen. So in the next five years, every enterprise will say, "I'm going to use the service, but you better make sure that this service works equally well on all of the clouds." And obviously the multicloud vendors like us, are there to do that. But I actually think that what you're going to see happening is that you're going to see the cloud vendors changing the existing services that they have to make them work on the other clouds. That's what's goin to happen, I think. >> Yeah, and I think I would add that, first of all, I agree with you. I think that's going to be a forcing function. Because I think you're driving it. You guys are in a way, one, are just an actor in the driving this because you're on the front end of this and there are others and there will be people following. But I think to me, I'm a cloud vendor, I got to differentiate. Adam, If I'm Adam Saleski, I got to say, "Hey, I got to differentiate." So I don't wan to get stuck in the middle, so to speak. Am I just going to innovate on the hardware AKA infrastructure or am I going to innovate at the higher level services? So what we're talking about here is the tail of two clouds within Amazon, for instance. So do I innovate on the silicon and get low level into the physics and squeeze performance out of the hardware and infrastructure? Or do I focus on ease of use at the top of the stack for the developers? So again, there's a channel of two clouds here. So I got to ask you, how do they differentiate? Number one and number two, I never heard a developer ever say, "I want to run my app or workload on the slower cloud." So I mean, you know, back when we had PCs you wanted to go, "I want the fastest processor." So again, you can have common level services, but where is that performance differentiation with the cloud? What do the clouds do in your opinion? >> Yeah, look, I think it's pretty clear. I think that it's, this is, you know, no surprise. Probably 70% or so of the revenue is in the lower infrastructure layers, compute, storage, networking. And they have to win that. They have to be competitive there. As you said, you can say, oh you know, I guess my CPUs are slower than the other cloud, but who cares? I have amazing other services which only work on my cloud by the way, right? That's not going to be a winning recipe. So I think all three are laser focused on, we going to have specialized hardware and the nuts and bolts of the infrastructure, we can do it better than the other clouds for sure. And you can see lots of innovation happening there, right? The Graviton chips, you know, we see huge price performance benefits in those chips. I mean it's real, right? It's basically a 20, 30% free lunch. You know, why wouldn't you, why wouldn't you go for it there? There's no downside. You know, there's no, "got you" or no catch. But we see Azure doing the same thing now, they're also building their own chips and we know that Google builds specialized machine learning chips, TPU, Tenor Processing Units. So their legs are focused on that. I don't think they can give up that or focused on higher levels if they had to pick bets. And I think actually in the next few years, most of us have to make more, we have to be more deliberate and calculated in the picks we do. I think in the last five years, most of us have said, "We'll do all of it." You know. >> Well you made a good bet with Spark, you know, the duke was pretty obvious trend that was, everyone was shut on that bandwagon and you guys picked a big bet with Spark. Look what happened with you guys? So again, I love this betting kind of concept because as the world matures, growth slows down and shifts and that next wave of value coming in, AKA customers, they're going to integrate with a new ecosystem. A new kind of partner network for AWS and the other clouds. But with aws they're going to need to nurture the next Databricks. They're going to need to still provide that SaaS, ISV like experience for, you know, a basic software hosting or some application. But I go to get your thoughts on this idea of multiple clouds because if I'm a developer, the old days was, old days, within our decade, full stack developer- >> It was two years ago, yeah (John laughing) >> This is a decade ago, full stack and then the cloud came in, you kind had the half stack and then you would do some things. It seems like the clouds are trying to say, we want to be the full stack or not. Or is it still going to be, you know, I'm an application like a PC and a Mac, I'm going to write the same application for both hardware. I mean what's your take on this? Are they trying to do full stack and you see them more like- >> Absolutely. I mean look, of course they're going, they have, I mean they have over 300, I think Amazon has over 300 services, right? That's not just compute, storage, networking, it's the whole stack, right? But my key point is, I think they have to nail the core infrastructure storage compute networking because the three clouds that are there competing, they're formidable companies with formidable balance sheets and it doesn't look like any of them is going to throw in the towel and say, we give up. So I think it's going to intensify. And given that they have a 70% revenue on that infrastructure layer, I think they, if they have to pick their bets, I think they'll focus it on that infrastructure layer. I think the layer above where they're also placing bets, they're doing that, the full stack, right? But there I think the demand will be, can you make that work on the other clouds? And therein lies an innovator's dilemma because if I make it work on the other clouds, then I'm foregoing that 70% revenue of the infrastructure. I'm not getting it. The other cloud vendor is going to get it. So should I do that or not? Second, is the other cloud vendor going to be welcoming of me making my service work on their cloud if I am a competing cloud, right? And what kind of terms of service are I giving me? And am I going to really invest in doing that? And I think right now we, you know, most, the vast, vast, vast majority of the services only work on the one cloud that you know, it's built on. It doesn't work on others, but this will shift. >> Yeah, I think the innovators dilemma is also very good point. And also add, it's an integrators dilemma too because now you talk about integration across services. So I believe that the super cloud movement's going to happen before Sky. And I think what explained by that, what you guys did and what other companies are doing by representing advanced, I call platform engineering, refactoring an existing market really fast, time to value and CAPEX is, I mean capital, market cap is going to be really fast. I think there's going to be an opportunity for those to emerge that's going to set the table for global multicloud ultimately in the future. So I think you're going to start to see the same pattern of what you guys did get in, leverage the hell out of it, use it, not in the way just to host, but to refactor and take down territory of markets. So number one, and then ultimately you get into, okay, I want to run some SLA across services, then there's a little bit more complication. I think that's where you guys put that beautiful paper out on Sky Computing. Okay, that makes sense. Now if you go to today's market, okay, I'm betting on Amazon because they're the best, this is the best cloud win scenario, not the most robust cloud. So if I'm a developer, I want the best. How do you look at their bet when it comes to data? Because now they've got machine learning, Swami's got a big keynote on Wednesday, I'm expecting to see a lot of AI and machine learning. I'm expecting to hear an end to end data story. This is what you do, so as a major partner, how do you view the moves Amazon's making and the bets they're making with data and machine learning and AI? >> First I want to lift off my hat to AWS for being customer obsessed. So I know that if a customer wants Databricks, I know that AWS and their sellers will actually help us get that customer deploy Databricks. Now which of the services is the customer going to pick? Are they going to pick ours or the end to end, what Swami is going to present on stage? Right? So that's the question we're getting. But I wanted to start with by just saying, their customer obsessed. So I think they're going to do the right thing for the customer and I see the evidence of it again and again and again. So kudos to them. They're amazing at this actually. Ultimately our bet is, customers want this to be simple, integrated, okay? So yes there are hundreds of services that together give you the end to end experience and they're very customizable that AWS gives you. But if you want just something simply integrated that also works across the clouds, then I think there's a special place for Databricks. And I think the lake house approach that we have, which is an integrated, completely integrated, we integrate data lakes with data warehouses, integrate workflows with machine learning, with real time processing, all these in one platform. I think there's going to be tailwinds because I think the most important thing that's going to happen in the next few years is that every customer is going to now be obsessed, given the recession and the environment we're in. How do I cut my costs? How do I cut my costs? And we learn this from the customers they're adopting the lake house because they're thinking, instead of using five vendors or three vendors, I can simplify it down to one with you and I can cut my cost. So I think that's going to be one of the main drivers of why people bet on the lake house because it helps them lower their TCO; Total Cost of Ownership. And it's as simple as that. Like I have three things right now. If I can get the same job done of those three with one, I'd rather do that. And by the way, if it's three or four across two clouds and I can just use one and it just works across two clouds, I'm going to do that. Because my boss is telling me I need to cut my budget. >> (indistinct) (John laughing) >> Yeah, and I'd rather not to do layoffs and they're asking me to do more. How can I get smaller budgets, not lay people off and do more? I have to cut, I have to optimize. What's happened in the last five, six years is there's been a huge sprawl of services and startups, you know, you know most of them, all these startups, all of them, all the activity, all the VC investments, well those companies sold their software, right? Even if a startup didn't make it big, you know, they still sold their software to some vendors. So the ecosystem is now full of lots and lots and lots and lots of different software. And right now people are looking, how do I consolidate, how do I simplify, how do I cut my costs? >> And you guys have a great solution. You're also an arms dealer and a innovator. So I have to ask this question, because you're a professor of the industry as well as at Berkeley, you've seen a lot of the historical innovations. If you look at the moment we're in right now with the recession, okay we had COVID, okay, it changed how people work, you know, people working at home, provisioning VLAN, all that (indistinct) infrastructure, okay, yeah, technology and cloud health. But we're in a recession. This is the first recession where the Amazon and the other cloud, mainly Amazon Web Services is a major economic puzzle in the piece. So they were never around before, even 2008, they were too small. They're now a major economic enabler, player, they're serving startups, enterprises, they have super clouds like you guys. They're a force and the people, their customers are cutting back but also they can also get faster. So agility is now an equation in the economic recovery. And I want to get your thoughts because you just brought that up. Customers can actually use the cloud and Databricks to actually get out of the recovery because no one's going to say, stop making profit or make more profit. So yeah, cut costs, be more efficient, but agility's also like, let's drive more revenue. So in this digital transformation, if you take this to conclusion, every company transforms, their company is the app. So their revenue is tied directly to their technology deployment. What's your reaction and comment to that because this is a new historical moment where cloud and scale and data, actually could be configured in a way to actually change the nature of a business in such a short time. And with the recession looming, no one's got time to wait. >> Yeah, absolutely. Look, the secular tailwind in the market is that of, you know, 10 years ago it was software is eating the world, now it's AI's going to eat all of software software. So more and more we're going to have, wherever you have software, which is everywhere now because it's eaten the world, it's going to be eaten up by AI and data. You know, AI doesn't exist without data so they're synonymous. You can't do machine learning if you don't have data. So yeah, you're going to see that everywhere and that automation will help people simplify things and cut down the costs and automate more things. And in the cloud you can also do that by changing your CAPEX to OPEX. So instead of I invest, you know, 10 million into a data center that I buy, I'm going to have headcount to manage the software. Why don't we change this to OPEX? And then they are going to optimize it. They want to lower the TCO because okay, it's in the cloud. but I do want the costs to be much lower that what they were in the previous years. Last five years, nobody cared. Who cares? You know what it costs. You know, there's a new brave world out there. Now there's like, no, it has to be efficient. So I think they're going to optimize it. And I think this lake house approach, which is an integration of the lakes and the warehouse, allows you to rationalize the two and simplify them. It allows you to basically rationalize away the data warehouse. So I think much faster we're going to see the, why do I need the data warehouse? If I can get the same thing done with the lake house for fraction of the cost, that's what's going to happen. I think there's going to be focus on that simplification. But I agree with you. Ultimately everyone knows, everybody's a software company. Every company out there is a software company and in the next 10 years, all of them are also going to be AI companies. So that is going to continue. >> (indistinct), dev's going to stop. And right sizing right now is a key economic forcing function. Final question for you and I really appreciate you taking the time. This year Reinvent, what's the bumper sticker in your mind around what's the most important industry dynamic, power dynamic, ecosystem dynamic that people should pay attention to as we move from the brave new world of okay, I see cloud, cloud operations. I need to really make it structurally change my business. How do I, what's the most important story? What's the bumper sticker in your mind for Reinvent? >> Bumper sticker? lake house 24. (John laughing) >> That's data (indistinct) bumper sticker. What's the- >> (indistinct) in the market. No, no, no, no. You know, it's, AWS talks about, you know, all of their services becoming a lake house because they want the center of the gravity to be S3, their lake. And they want all the services to directly work on that, so that's a lake house. We're Bumper see Microsoft with Synapse, modern, you know the modern intelligent data platform. Same thing there. We're going to see the same thing, we already seeing it on GCP with Big Lake and so on. So I actually think it's the how do I reduce my costs and the lake house integrates those two. So that's one of the main ways you can rationalize and simplify. You get in the lake house, which is the name itself is a (indistinct) of two things, right? Lake house, "lake" gives you the AI, "house" give you the database data warehouse. So you get your AI and you get your data warehousing in one place at the lower cost. So for me, the bumper sticker is lake house, you know, 24. >> All right. Awesome Ali, well thanks for the exclusive interview. Appreciate it and get to see you. Congratulations on your success and I know you guys are going to be fine. >> Awesome. Thank you John. It's always a pleasure. >> Always great to chat with you again. >> Likewise. >> You guys are a great team. We're big fans of what you guys have done. We think you're an example of what we call "super cloud." Which is getting the hype up and again your paper speaks to some of the innovation, which I agree with by the way. I think that that approach of not forcing standards is really smart. And I think that's absolutely correct, that having the market still innovate is going to be key. standards with- >> Yeah, I love it. We're big fans too, you know, you're doing awesome work. We'd love to continue the partnership. >> So, great, great Ali, thanks. >> Take care (outro music)

(outro music) >> Hey, I'm John Furrier, here with an exclusive interview with Ali Ghodsi, who's the CEO of Databricks. Ali, great to see you. Preview for reinvent. We're going to launch this story, exclusive Databricks material on the notes, after the keynotes prior to the keynotes and after the keynotes that reinvent. So great to see you. You know, you've been a partner of AWS for a very, very long time. I think five years ago, I think I first interviewed you, you were one of the first to publicly declare that this was a place to build a company on and not just post an application, but refactor capabilities to create, essentially a platform in the cloud, on the cloud. Not just an ISV; Independent Software Vendor, kind of an old term, we're talking about real platform like capability to change the game. Can you talk about your experience as an AWS partner? >> Yeah, look, so we started in 2013. I swiped my personal credit card on AWS and some of my co-founders did the same. And we started building. And we were excited because we just thought this is a much better way to launch a company because you can just much faster get time to market and launch your thing and you can get the end users much quicker access to the thing you're building. So we didn't really talk to anyone at AWS, we just swiped a credit card. And eventually they told us, "Hey, do you want to buy extra support?" "You're asking a lot of advanced questions from us." "Maybe you want to buy our advanced support." And we said, no, no, no, no. We're very advanced ourselves, we know what we're doing. We're not going to buy any advanced support. So, you know, we just built this, you know, startup from nothing on AWS without even talking to anyone there. So at some point, I think around 2017, they suddenly saw this company with maybe a hundred million ARR pop up on their radar and it's driving massive amounts of compute, massive amounts of data. And it took a little bit in the beginning just us to get to know each other because as I said, it's like we were not on their radar and we weren't really looking, we were just doing our thing. And then over the years the partnership has deepened and deepened and deepened and then with, you know, Andy (indistinct) really leaning into the partnership, he mentioned us at Reinvent. And then we sort of figured out a way to really integrate the two service, the Databricks platform with AWS . And today it's an amazing partnership. You know, we directly connected with the general managers for the services. We're connected at the CEO level, you know, the sellers get compensated for pushing Databricks, we're, we have multiple offerings on their marketplace. We have a native offering on AWS. You know, we're prominently always sort of marketed and you know, we're aligned also vision wise in what we're trying to do. So yeah, we've come a very, very long way. >> Do you consider yourself a SaaS app or an ISV or do you see yourself more of a platform company because you have customers. How would you categorize your category as a company? >> Well, it's a data platform, right? And actually the, the strategy of the Databricks is take what's otherwise five, six services in the industry or five, six different startups, but do them as part of one data platform that's integrated. So in one word, the strategy of data bricks is "unification." We call it the data lake house. But really the idea behind the data lake house is that of unification, or in more words it's, "The whole is greater than the sum of its parts." So you could actually go and buy five, six services out there or actually use five, six services from the cloud vendors, stitch it together and it kind of resembles Databricks. Our power is in doing those integrated, together in a way in which it's really, really easy and simple to use for end users. So yeah, we're a data platform. I wouldn't, you know, ISV that's a old term, you know, Independent Software Vendor. You know, I think, you know, we have actually a whole slew of ISVs on top of Databricks, that integrate with our platform. And you know, in our marketplace as well as in our partner connect, we host those ISVs that then, you know, work on top of the data that we have in the Databricks, data lake house. >> You know, I think one of the things your journey has been great to document and watch from the beginning. I got to give you guys credit over there and props, congratulations. But I think you're the poster child as a company to what we see enterprises doing now. So go back in time when you guys swiped a credit card, you didn't need attending technical support because you guys had brains, you were refactoring, rethinking. It wasn't just banging out software, you had, you were doing some complex things. It wasn't like it was just write some software hosted on server. It was really a lot more. And as a result your business worth billions of dollars. I think 38 billion or something like that, big numbers, big numbers of great revenue growth as well, billions in revenue. You have customers, you have an ecosystem, you have data applications on top of Databricks. So in a way you're a cloud on top of the cloud. So is there a cloud on top of the cloud? So you have ISVs, Amazon has ISVs. Can you take us through what this means and at this point in history, because this seems to be an advanced version of benefits of platforming and refactoring, leveraging say AWS. >> Yeah, so look, when we started, there was really only one game in town. It was AWS. So it was one cloud. And the strategy of the company then was, well Amazon had this beautiful set of services that they're building bottom up, they have storage, compute, networking, and then they have databases and so on. But it's a lot of services. So let us not directly compete with AWS and try to take out one of their services. Let's not do that because frankly we can't. We were not of that size. They had the scale, they had the size and they were the only cloud vendor in town. So our strategy instead was, let's do something else. Let's not compete directly with say, a particular service they're building, let's take a different strategy. What if we had a unified holistic data platform, where it's just one integrated service end to end. So think of it as Microsoft office, which contains PowerPoint, and Word, and Excel and even Access, if you want to use it. What if we build that and AWS has this really amazing knack for releasing things, you know services, lots of them, every reinvent. And they're sort of a DevOps person's dream and you can stitch these together and you know you have to be technical. How do we elevate that and make it simpler and integrate it? That was our original strategy and it resonated with a segment of the market. And the reason it worked with AWS so that we wouldn't butt heads with AWS was because we weren't a direct replacement for this service or for that service, we were taking a different approach. And AWS, because credit goes to them, they're so customer obsessed, they would actually do what's right for the customer. So if the customer said we want this unified thing, their sellers would actually say, okay, so then you should use Databricks. So they truly are customer obsessed in that way. And I really mean it, John. Things have changed over the years. They're not the only cloud anymore. You know, Azure is real, GCP is real, there's also Alibaba. And now over 70% of our customers are on more than one cloud. So now what we hear from them is, not only want, do we want a simplified, unified thing, but we want it also to work across the clouds. Because those of them that are seriously considering multiple clouds, they don't want to use a service on cloud one and then use a similar service on cloud two. But it's a little bit different. And now they have to do twice the work to make it work. You know, John, it's hard enough as it is, like it's this data stuff and analytics. It's not a walk in the park, you know. You hire an administrator in the back office that clicks a button and its just, now you're a data driven digital transformed company. It's hard. If you now have to do it again on the second cloud with different set of services and then again on a third cloud with a different set of services. That's very, very costly. So the strategy then has changed that, how do we take that unified simple approach and make it also the same and standardize across the clouds, but then also integrate it as far down as we can on each of the clouds. So that you're not giving up any of the benefits that the particular cloud has. >> Yeah, I think one of the things that we see, and I want get your reaction to this, is this rise of the super cloud as we call it. I think you were involved in the Sky paper that I saw your position paper came out after we had introduced Super Cloud, which is great. Congratulations to the Berkeley team, wearing the hat here. But you guys are, I think a driver of this because you're creating the need for these things. You're saying, okay, we went on one cloud with AWS and you didn't hide that. And now you're publicly saying there's other clouds too, increased ham for your business. And customers have multiple clouds in their infrastructure for the best of breed that they have. Okay, get that. But there's still a challenge around the innovation, growth that's still around the corner. We still have a supply chain problem, we still have skill gaps. You know, you guys are unique at Databricks as other these big examples of super clouds that are developing. Enterprises don't have the Databricks kind of talent. They need, they need turnkey solutions. So Adam and the team at Amazon are promoting, you know, more solution oriented approaches higher up on the stack. You're starting to see kind of like, I won't say templates, but you know, almost like application specific headless like, low code, no code capability to accelerate clients who are wanting to write code for the modern error. Right, so this kind of, and then now you, as you guys pointed out with these common services, you're pushing the envelope. So you're saying, hey, I need to compete, I don't want to go to my customers and have them to have a staff or this cloud and this cloud and this cloud because they don't have the staff. Or if they do, they're very unique. So what's your reaction? Because this kind is the, it kind of shows your leadership as a partner of AWS and the clouds, but also highlights I think what's coming. But you share your reaction. >> Yeah, look, it's, first of all, you know, I wish I could take credit for this but I can't because it's really the customers that have decided to go on multiple clouds. You know, it's not Databricks that you know, push this or some other vendor, you know, that, Snowflake or someone who pushed this and now enterprises listened to us and they picked two clouds. That's not how it happened. The enterprises picked two clouds or three clouds themselves and we can get into why, but they did that. So this largely just happened in the market. We as data platforms responded to what they're then saying, which is they're saying, "I don't want to redo this again on the other cloud." So I think the writing is on the wall. I think it's super obvious what's going to happen next. They will say, "Any service I'm using, it better work exactly the same on all the clouds." You know, that's what's going to happen. So in the next five years, every enterprise will say, "I'm going to use the service, but you better make sure that this service works equally well on all of the clouds." And obviously the multicloud vendors like us, are there to do that. But I actually think that what you're going to see happening is that you're going to see the cloud vendors changing the existing services that they have to make them work on the other clouds. That's what's goin to happen, I think. >> Yeah, and I think I would add that, first of all, I agree with you. I think that's going to be a forcing function. Because I think you're driving it. You guys are in a way, one, are just an actor in the driving this because you're on the front end of this and there are others and there will be people following. But I think to me, I'm a cloud vendor, I got to differentiate. Adam, If I'm Adam Saleski, I got to say, "Hey, I got to differentiate." So I don't wan to get stuck in the middle, so to speak. Am I just going to innovate on the hardware AKA infrastructure or am I going to innovate at the higher level services? So what we're talking about here is the tail of two clouds within Amazon, for instance. So do I innovate on the silicon and get low level into the physics and squeeze performance out of the hardware and infrastructure? Or do I focus on ease of use at the top of the stack for the developers? So again, there's a channel of two clouds here. So I got to ask you, how do they differentiate? Number one and number two, I never heard a developer ever say, "I want to run my app or workload on the slower cloud." So I mean, you know, back when we had PCs you wanted to go, "I want the fastest processor." So again, you can have common level services, but where is that performance differentiation with the cloud? What do the clouds do in your opinion? >> Yeah, look, I think it's pretty clear. I think that it's, this is, you know, no surprise. Probably 70% or so of the revenue is in the lower infrastructure layers, compute, storage, networking. And they have to win that. They have to be competitive there. As you said, you can say, oh you know, I guess my CPUs are slower than the other cloud, but who cares? I have amazing other services which only work on my cloud by the way, right? That's not going to be a winning recipe. So I think all three are laser focused on, we going to have specialized hardware and the nuts and bolts of the infrastructure, we can do it better than the other clouds for sure. And you can see lots of innovation happening there, right? The Graviton chips, you know, we see huge price performance benefits in those chips. I mean it's real, right? It's basically a 20, 30% free lunch. You know, why wouldn't you, why wouldn't you go for it there? There's no downside. You know, there's no, "got you" or no catch. But we see Azure doing the same thing now, they're also building their own chips and we know that Google builds specialized machine learning chips, TPU, Tenor Processing Units. So their legs are focused on that. I don't think they can give up that or focused on higher levels if they had to pick bets. And I think actually in the next few years, most of us have to make more, we have to be more deliberate and calculated in the picks we do. I think in the last five years, most of us have said, "We'll do all of it." You know. >> Well you made a good bet with Spark, you know, the duke was pretty obvious trend that was, everyone was shut on that bandwagon and you guys picked a big bet with Spark. Look what happened with you guys? So again, I love this betting kind of concept because as the world matures, growth slows down and shifts and that next wave of value coming in, AKA customers, they're going to integrate with a new ecosystem. A new kind of partner network for AWS and the other clouds. But with aws they're going to need to nurture the next Databricks. They're going to need to still provide that SaaS, ISV like experience for, you know, a basic software hosting or some application. But I go to get your thoughts on this idea of multiple clouds because if I'm a developer, the old days was, old days, within our decade, full stack developer- >> It was two years ago, yeah (John laughing) >> This is a decade ago, full stack and then the cloud came in, you kind had the half stack and then you would do some things. It seems like the clouds are trying to say, we want to be the full stack or not. Or is it still going to be, you know, I'm an application like a PC and a Mac, I'm going to write the same application for both hardware. I mean what's your take on this? Are they trying to do full stack and you see them more like- >> Absolutely. I mean look, of course they're going, they have, I mean they have over 300, I think Amazon has over 300 services, right? That's not just compute, storage, networking, it's the whole stack, right? But my key point is, I think they have to nail the core infrastructure storage compute networking because the three clouds that are there competing, they're formidable companies with formidable balance sheets and it doesn't look like any of them is going to throw in the towel and say, we give up. So I think it's going to intensify. And given that they have a 70% revenue on that infrastructure layer, I think they, if they have to pick their bets, I think they'll focus it on that infrastructure layer. I think the layer above where they're also placing bets, they're doing that, the full stack, right? But there I think the demand will be, can you make that work on the other clouds? And therein lies an innovator's dilemma because if I make it work on the other clouds, then I'm foregoing that 70% revenue of the infrastructure. I'm not getting it. The other cloud vendor is going to get it. So should I do that or not? Second, is the other cloud vendor going to be welcoming of me making my service work on their cloud if I am a competing cloud, right? And what kind of terms of service are I giving me? And am I going to really invest in doing that? And I think right now we, you know, most, the vast, vast, vast majority of the services only work on the one cloud that you know, it's built on. It doesn't work on others, but this will shift. >> Yeah, I think the innovators dilemma is also very good point. And also add, it's an integrators dilemma too because now you talk about integration across services. So I believe that the super cloud movement's going to happen before Sky. And I think what explained by that, what you guys did and what other companies are doing by representing advanced, I call platform engineering, refactoring an existing market really fast, time to value and CAPEX is, I mean capital, market cap is going to be really fast. I think there's going to be an opportunity for those to emerge that's going to set the table for global multicloud ultimately in the future. So I think you're going to start to see the same pattern of what you guys did get in, leverage the hell out of it, use it, not in the way just to host, but to refactor and take down territory of markets. So number one, and then ultimately you get into, okay, I want to run some SLA across services, then there's a little bit more complication. I think that's where you guys put that beautiful paper out on Sky Computing. Okay, that makes sense. Now if you go to today's market, okay, I'm betting on Amazon because they're the best, this is the best cloud win scenario, not the most robust cloud. So if I'm a developer, I want the best. How do you look at their bet when it comes to data? Because now they've got machine learning, Swami's got a big keynote on Wednesday, I'm expecting to see a lot of AI and machine learning. I'm expecting to hear an end to end data story. This is what you do, so as a major partner, how do you view the moves Amazon's making and the bets they're making with data and machine learning and AI? >> First I want to lift off my hat to AWS for being customer obsessed. So I know that if a customer wants Databricks, I know that AWS and their sellers will actually help us get that customer deploy Databricks. Now which of the services is the customer going to pick? Are they going to pick ours or the end to end, what Swami is going to present on stage? Right? So that's the question we're getting. But I wanted to start with by just saying, their customer obsessed. So I think they're going to do the right thing for the customer and I see the evidence of it again and again and again. So kudos to them. They're amazing at this actually. Ultimately our bet is, customers want this to be simple, integrated, okay? So yes there are hundreds of services that together give you the end to end experience and they're very customizable that AWS gives you. But if you want just something simply integrated that also works across the clouds, then I think there's a special place for Databricks. And I think the lake house approach that we have, which is an integrated, completely integrated, we integrate data lakes with data warehouses, integrate workflows with machine learning, with real time processing, all these in one platform. I think there's going to be tailwinds because I think the most important thing that's going to happen in the next few years is that every customer is going to now be obsessed, given the recession and the environment we're in. How do I cut my costs? How do I cut my costs? And we learn this from the customers they're adopting the lake house because they're thinking, instead of using five vendors or three vendors, I can simplify it down to one with you and I can cut my cost. So I think that's going to be one of the main drivers of why people bet on the lake house because it helps them lower their TCO; Total Cost of Ownership. And it's as simple as that. Like I have three things right now. If I can get the same job done of those three with one, I'd rather do that. And by the way, if it's three or four across two clouds and I can just use one and it just works across two clouds, I'm going to do that. Because my boss is telling me I need to cut my budget. >> (indistinct) (John laughing) >> Yeah, and I'd rather not to do layoffs and they're asking me to do more. How can I get smaller budgets, not lay people off and do more? I have to cut, I have to optimize. What's happened in the last five, six years is there's been a huge sprawl of services and startups, you know, you know most of them, all these startups, all of them, all the activity, all the VC investments, well those companies sold their software, right? Even if a startup didn't make it big, you know, they still sold their software to some vendors. So the ecosystem is now full of lots and lots and lots and lots of different software. And right now people are looking, how do I consolidate, how do I simplify, how do I cut my costs? >> And you guys have a great solution. You're also an arms dealer and a innovator. So I have to ask this question, because you're a professor of the industry as well as at Berkeley, you've seen a lot of the historical innovations. If you look at the moment we're in right now with the recession, okay we had COVID, okay, it changed how people work, you know, people working at home, provisioning VLAN, all that (indistinct) infrastructure, okay, yeah, technology and cloud health. But we're in a recession. This is the first recession where the Amazon and the other cloud, mainly Amazon Web Services is a major economic puzzle in the piece. So they were never around before, even 2008, they were too small. They're now a major economic enabler, player, they're serving startups, enterprises, they have super clouds like you guys. They're a force and the people, their customers are cutting back but also they can also get faster. So agility is now an equation in the economic recovery. And I want to get your thoughts because you just brought that up. Customers can actually use the cloud and Databricks to actually get out of the recovery because no one's going to say, stop making profit or make more profit. So yeah, cut costs, be more efficient, but agility's also like, let's drive more revenue. So in this digital transformation, if you take this to conclusion, every company transforms, their company is the app. So their revenue is tied directly to their technology deployment. What's your reaction and comment to that because this is a new historical moment where cloud and scale and data, actually could be configured in a way to actually change the nature of a business in such a short time. And with the recession looming, no one's got time to wait. >> Yeah, absolutely. Look, the secular tailwind in the market is that of, you know, 10 years ago it was software is eating the world, now it's AI's going to eat all of software software. So more and more we're going to have, wherever you have software, which is everywhere now because it's eaten the world, it's going to be eaten up by AI and data. You know, AI doesn't exist without data so they're synonymous. You can't do machine learning if you don't have data. So yeah, you're going to see that everywhere and that automation will help people simplify things and cut down the costs and automate more things. And in the cloud you can also do that by changing your CAPEX to OPEX. So instead of I invest, you know, 10 million into a data center that I buy, I'm going to have headcount to manage the software. Why don't we change this to OPEX? And then they are going to optimize it. They want to lower the TCO because okay, it's in the cloud. but I do want the costs to be much lower that what they were in the previous years. Last five years, nobody cared. Who cares? You know what it costs. You know, there's a new brave world out there. Now there's like, no, it has to be efficient. So I think they're going to optimize it. And I think this lake house approach, which is an integration of the lakes and the warehouse, allows you to rationalize the two and simplify them. It allows you to basically rationalize away the data warehouse. So I think much faster we're going to see the, why do I need the data warehouse? If I can get the same thing done with the lake house for fraction of the cost, that's what's going to happen. I think there's going to be focus on that simplification. But I agree with you. Ultimately everyone knows, everybody's a software company. Every company out there is a software company and in the next 10 years, all of them are also going to be AI companies. So that is going to continue. >> (indistinct), dev's going to stop. And right sizing right now is a key economic forcing function. Final question for you and I really appreciate you taking the time. This year Reinvent, what's the bumper sticker in your mind around what's the most important industry dynamic, power dynamic, ecosystem dynamic that people should pay attention to as we move from the brave new world of okay, I see cloud, cloud operations. I need to really make it structurally change my business. How do I, what's the most important story? What's the bumper sticker in your mind for Reinvent? >> Bumper sticker? lake house 24. (John laughing) >> That's data (indistinct) bumper sticker. What's the- >> (indistinct) in the market. No, no, no, no. You know, it's, AWS talks about, you know, all of their services becoming a lake house because they want the center of the gravity to be S3, their lake. And they want all the services to directly work on that, so that's a lake house. We're Bumper see Microsoft with Synapse, modern, you know the modern intelligent data platform. Same thing there. We're going to see the same thing, we already seeing it on GCP with Big Lake and so on. So I actually think it's the how do I reduce my costs and the lake house integrates those two. So that's one of the main ways you can rationalize and simplify. You get in the lake house, which is the name itself is a (indistinct) of two things, right? Lake house, "lake" gives you the AI, "house" give you the database data warehouse. So you get your AI and you get your data warehousing in one place at the lower cost. So for me, the bumper sticker is lake house, you know, 24. >> All right. Awesome Ali, well thanks for the exclusive interview. Appreciate it and get to see you. Congratulations on your success and I know you guys are going to be fine. >> Awesome. Thank you John. It's always a pleasure. >> Always great to chat with you again. >> Likewise. >> You guys are a great team. We're big fans of what you guys have done. We think you're an example of what we call "super cloud." Which is getting the hype up and again your paper speaks to some of the innovation, which I agree with by the way. I think that that approach of not forcing standards is really smart. And I think that's absolutely correct, that having the market still innovate is going to be key. standards with- >> Yeah, I love it. We're big fans too, you know, you're doing awesome work. We'd love to continue the partnership. >> So, great, great Ali, thanks. >> Take care (outro 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