(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)

(gentle music) >> Announcer: "theCube's" live coverage is made possible by funding from Dell Technologies, creating technologies that drive human progress. (upbeat music) (logo whooshing) >> Hey, everyone, welcome back to "theCube's" coverage of day one, MWC23 live from Barcelona, Lisa Martin here with Dave Vellante. Dave, we've got some great conversations so far This is the biggest, most packed show I've been to in years. About 80,000 people here so far. >> Yeah, down from its peak of 108, but still pretty good. You know, a lot of folks from China come to this show, but with the COVID situation in China, that's impacted the attendance, but still quite amazing. >> Amazing for sure. We're going to be talking about trends and mobility, and all sorts of great things. We have a couple of guests joining us for the first time on "theCUBE." Please welcome Dr. Srinivas Mukkamala or Sri, chief product officer at Ivanti. And Dave Shepherd, VP Ivanti. Guys, welcome to "theCUBE." Great to have you here. >> Thank you. >> So, day one of the conference, Sri, we'll go to you first. Talk about some of the trends that you're seeing in mobility. Obviously, the conference renamed from Mobile World Congress to MWC mobility being part of it, but what are some of the big trends? >> It's interesting, right? I mean, I was catching up with Dave. The first thing is from the keynotes, it took 45 minutes to talk about security. I mean, it's quite interesting when you look at the shore floor. We're talking about Edge, we're talking about 5G, the whole evolution. And there's also the concept of are we going into the Cloud? Are we coming back from the Cloud, back to the Edge? They're really two different things. Edge is all decentralized while you recompute. And one thing I observed here is they're talking about near real-time reality. When you look at automobiles, when you look at medical, when you look at robotics, you can't have things processed in the Cloud. It'll be too late. Because you got to make millisecond-based stations. That's a big trend for me. When I look at staff... Okay, the compute it takes to process in the Cloud versus what needs to happen on-prem, on device, is going to revolutionize the way we think about mobility. >> Revolutionize. David, what are some of the things that you're saying? Do you concur? >> Yeah, 100%. I mean, look, just reading some of the press recently, they're predicting 22 billion IoT devices by 2024. Everything Sri just talked about there. It's growing exponentially. You know, problems we have today are a snapshot. We're probably in the slowest place we are today. Everything's just going to get faster and faster and faster. So it's a, yeah, 100% concur with that. >> You know, Sri, on your point, so Jose Maria Alvarez, the CEO of Telefonica, said there are three pillars of the future of telco, low latency, programmable networks, and Cloud and Edge. So, as to your point, Cloud and low latency haven't gone hand in hand. But the Cloud guys are saying, "All right, we're going to bring the Cloud to the Edge." That's sort of an interesting dynamic. We're going to bypass them. We heard somebody, another speaker say, "You know, Cloud can't do it alone." You know? (chuckles) And so, it's like these worlds need each other in a way, don't they? >> Definitely right. So that's a fantastic way to look at it. The Cloud guys can say, "We're going to come closer to where the computer is." And if you really take a look at it with data localization, where are we going to put the Cloud in, right? I mean, so the data sovereignty becomes a very interesting thing. The localization becomes a very interesting thing. And when it comes to security, it gets completely different. I mean, we talked about moving everything to a centralized compute, really have massive processing, and give you the addition back wherever you are. Whereas when you're localized, I have to process everything within the local environment. So there's already a conflict right there. How are we going to address that? >> Yeah. So another statement, I think, it was the CEO of Ericsson, he was kind of talking about how the OTT guys have heard, "We can't let that happen again. And we're going to find new ways to charge for the network." Basically, he's talking about monetizing the API access. But I'm interested in what you're hearing from customers, right? 'Cause our mindset is, what value you're going to give to customers that they're going to pay for, versus, "I got this data I'm going to charge developers for." But what are you hearing from customers? >> It's amazing, Dave, the way you're looking at it, right? So if we take a look at what we were used to perpetual, and we said we're going to move to a subscription, right? I mean, everybody talks about subscription economy. Telcos on the other hand, had subscription economy for a long time, right? They were always based on usage, right? It's a usage economy. But today, we are basically realizing on compute. We haven't even started charging for compute. If you go to AWS, go to Azure, go to GCP, they still don't quite charge you for actual compute, right? It's kind of, they're still leaning on it. So think about API-based, we're going to break the bank. What people don't realize is, we do millions of API calls for any high transaction environment. A consumer can't afford that. What people don't realize is... I don't know how you're going to monetize. Even if you charge a cent a call, that is still going to be hundreds and thousands of dollars a day. And that's where, if you look at what you call low-code no-code motion? You see a plethora of companies being built on that. They're saying, "Hey, you don't have to write code. I'll give you authentication as a service. What that means is, Every single time you call my API to authenticate a user, I'm going to charge you." So just imagine how many times we authenticate on a single day. You're talking a few dozen times. And if I have to pay every single time I authenticate... >> Real friction in the marketplace, David. >> Yeah, and I tell you what. It's a big topic, right? And it's a topic that we haven't had to deal with at the Edge before, and we hear it probably daily really, complexity. The complexity's growing all the time. That means that we need to start to get insight, visibility. You know? I think a part of... Something that came out of the EU actually this week, stated, you know, there's a cyber attack every 11 seconds. That's fast, right? 2016, that was 40 seconds. So actually that speed I talked about earlier, everything Sri says that's coming down to the Edge, we want to embrace the Edge and that is the way we're going to move. But customers are mindful of the complexity that's involved in that. And that, you know, lens thought to how are we going to deal with those complexities. >> I was just going to ask you, how are you planning to deal with those complexities? You mentioned one ransomware attack every 11 seconds. That's down considerably from just a few years ago. Ransomware is a household word. It's no longer, "Are we going to get attacked?" It's when, it's to what extent, it's how much. So how is Ivanti helping customers deal with some of the complexities, and the changes in the security landscape? >> Yeah. Shall I start on that one first? Yeah, look, we want to give all our customers and perspective customers full visibility of their environment. You know, devices that are attached to the environment. Where are they? What are they doing? How often are we going to look for those devices? Not only when we find those devices. What applications are they running? Are those applications secure? How are we going to manage those applications moving forward? And overall, wrapping it round, what kind of service are we going to do? What processes are we going to put in place? To Sri's point, the low-code no-code angle. How do we build processes that protect our organization? But probably a point where I'll pass to Sri in a moment is how do we add a level of automation to that? How do we add a level of intelligence that doesn't always require a human to be fixing or remediating a problem? >> To Sri, you mentioned... You're right, the keynote, it took 45 minutes before it even mentioned security. And I suppose it's because they've historically, had this hardened stack. Everything's controlled and it's a safe environment. And now that's changing. So what would you add? >> You know, great point, right? If you look at telcos, they're used to a perimeter-based network. >> Yep. >> I mean, that's what we are. Boxed, we knew our perimeter. Today, our perimeter is extended to our home, everywhere work, right? >> Yeah- >> We don't have a definition of a perimeter. Your browser is the new perimeter. And a good example, segueing to that, what we have seen is horizontal-based security. What we haven't seen is verticalization, especially in mobile. We haven't seen vertical mobile security solutions, right? Yes, you hear a little bit about automobile, you hear a little bit about healthcare, but what we haven't seen is, what about food sector? What about the frontline in food? What about supply chain? What security are we really doing? And I'll give you a simple example. You brought up ransomware. Last night, Dole was attacked with ransomware. We have seen the beef producer colonial pipeline. Now, if we have seen agritech being hit, what does it mean? We are starting to hit humanity. If you can't really put food on the table, you're starting to really disrupt the supply chain, right? In a massive way. So you got to start thinking about that. Why is Dole related to mobility? Think about that. They don't carry service and computers. What they carry is mobile devices. that's where the supply chain works. And then that's where you have to start thinking about it. And the evolution of ransomware, rather than a single-trick pony, you see them using multiple vulnerabilities. And Pegasus was the best example. Spyware across all politicians, right? And CEOs. It is six or seven vulnerabilities put together that actually was constructed to do an attack. >> Yeah. How does AI kind of change this? Where does it fit in? The attackers are going to have AI, but we could use AI to defend. But attackers are always ahead, right? (chuckles) So what's your... Do you have a point of view on that? 'Cause everybody's crazy about ChatGPT, right? The banks have all banned it. Certain universities in the United States have banned it. Another one's forcing his students to learn how to use ChatGPT to prompt it. It's all over the place. You have a point of view on this? >> So definitely, Dave, it's a great point. First, we all have to have our own generative AI. I mean, I look at it as your digital assistant, right? So when you had calculators, you can't function without a calculator today. It's not harmful. It's not going to take you away from doing multiplication, right? So we'll still teach arithmetic in school. You'll still use your calculator. So to me, AI will become an integral part. That's one beautiful thing I've seen on the short floor. Every little thing there is a AI-based solution I've seen, right? So ChatGPT is well played from multiple perspective. I would rather up level it and say, generated AI is the way to go. So there are three things. There is human intense triaging, where humans keep doing easy work, minimal work. You can use ML and AI to do that. There is human designing that you need to do. That's when you need to use AI. >> But, I would say this, in the Enterprise, that the quality of the AI has to be better than what we've seen so far out of ChatGPT, even though I love ChatGPT, it's amazing. But what we've seen from being... It's got to be... Is it true that... Don't you think it has to be cleaner, more accurate? It can't make up stuff. If I'm going to be automating my network with AI. >> I'll answer that question. It comes down to three fundamentals. The reason ChatGPT is giving addresses, it's not trained on the latest data. So for any AI and ML method, you got to look at three things. It's your data, it's your domain expertise, who is training it, and your data model. In ChatGPT, it's older data, it's biased to the people that trained it, right? >> Mm-hmm. >> And then, the data model is it's going to spit out what it's trained on. That's a precursor of any GPT, right? It's pre-trained transformation. >> So if we narrow that, right? Train it better for the specific use case, that AI has huge potential. >> You flip that to what the Enterprise customers talk about to us is, insight is invaluable. >> Right. >> But then too much insight too quickly all the time means we go remediation crazy. So we haven't got enough humans to be fixing all the problems. Sri's point with the ChatGPT data, some of that data we are looking at there could be old. So we're trying to triage something that may still be an issue, but it might have been superseded by something else as well. So that's my overriding when I'm talking to customers and we talk ChatGPT, it's in the news all the time. It's very topical. >> It's fun. >> It is. I even said to my 13-year-old son yesterday, your homework's out a date. 'Cause I knew he was doing some summary stuff on ChatGPT. So a little wind up that's out of date just to make that emphasis around the model. And that's where we, with our Neurons platform Ivanti, that's what we want to give the customers all the time, which is the real-time snapshot. So they can make a priority or a decision based on what that information is telling them. >> And we've kind of learned, I think, over the last couple of years, that access to real-time data, real-time AI, is no longer nice to have. It's a massive competitive advantage for organizations, but it's going to enable the on-demand, everything that we expect in our consumer lives, in our business lives. This is going to be table stakes for organizations, I think, in every industry going forward. >> Yeah. >> But assumes 5G, right? Is going to actually happen and somebody's going to- >> Going to absolutely. >> Somebody's going to make some money off it at some point. When are they going to make money off of 5G, do you think? (all laughing) >> No. And then you asked a very good question, Dave. I want to answer that question. Will bad guys use AI? >> Yeah. Yeah. >> Offensive AI is a very big thing. We have to pay attention to it. It's got to create an asymmetric war. If you look at the president of the United States, he said, "If somebody's going to attack us on cyber, we are going to retaliate." For the first time, US is willing to launch a cyber war. What that really means is, we're going to use AI for offensive reasons as well. And we as citizens have to pay attention to that. And that's where I'm worried about, right? AI bias, whether it's data, or domain expertise, or algorithmic bias, is going to be a big thing. And offensive AI is something everybody have to pay attention to. >> To your point, Sri, earlier about critical infrastructure getting hacked, I had this conversation with Dr. Robert Gates several years ago, and I said, "Yeah, but don't we have the best offensive, you know, technology in cyber?" And he said, "Yeah, but we got the most to lose too." >> Yeah, 100%. >> We're the wealthiest nation of the United States. The wealthiest is. So you got to be careful. But to your point, the president of the United States saying, "We'll retaliate," right? Not necessarily start the war, but who started it? >> But that's the thing, right? Attribution is the hardest part. And then you talked about a very interesting thing, rich nations, right? There's emerging nations. There are nations left behind. One thing I've seen on the show floor today is, digital inequality. Digital poverty is a big thing. While we have this amazing technology, 90% of the world doesn't have access to this. >> Right. >> What we have done is we have created an inequality across, and especially in mobility and cyber, if this technology doesn't reach to the last mile, which is emerging nations, I think we are creating a crater back again and putting societies a few miles back. >> And at much greater risk. >> 100%, right? >> Yeah. >> Because those are the guys. In cyber, all you need is a laptop and a brain to attack. >> Yeah. Yeah. >> If I don't have it, that's where the civil war is going to start again. >> Yeah. What are some of the things in our last minute or so, guys, David, we'll start with you and then Sri go to you, that you're looking forward to at this MWC? The theme is velocity. We're talking about so much transformation and evolution in the telecom industry. What are you excited to hear and learn in the next couple of days? >> Just getting a complete picture. One is actually being out after the last couple of years, so you learn a lot. But just walking around and seeing, from my perspective, some vendor names that I haven't seen before, but seeing what they're doing and bringing to the market. But I think goes back to the point made earlier around APIs and integration. Everybody's talking about how can we kind of do this together in a way. So integrations, those smart things is what I'm kind of looking for as well, and how we plug into that as well. >> Excellent, and Sri? >> So for us, there is a lot to offer, right? So while I'm enjoying what I'm seeing here, I'm seeing at an opportunity. We have an amazing portfolio of what we can do. We are into mobile device management. We are the last (indistinct) company. When people find problems, somebody has to go remediators. We are the world's largest patch management company. And what I'm finding is, yes, all these people are embedding software, pumping it like nobody's business. As you find one ability, somebody has to go fix them, and we want to be the (indistinct) company. We had the last smile. And I find an amazing opportunity, not only we can do device management, but do mobile threat defense and give them a risk prioritization on what needs to be remediated, and manage all that in our ITSM. So I look at this as an amazing, amazing opportunity. >> Right. >> Which is exponential than what I've seen before. >> So last question then. Speaking of opportunities, Sri, for you, what are some of the things that customers can go to? Obviously, you guys talk to customers all the time. In terms of learning what Ivanti is going to enable them to do, to take advantage of these opportunities. Any webinars, any events coming up that we want people to know about? >> Absolutely, ivanti.com is the best place to go because we keep everything there. Of course, "theCUBE" interview. >> Of course. >> You should definitely watch that. (all laughing) No. So we have quite a few industry events we do. And especially there's a lot of learning. And we just raised the ransomware report that actually talks about ransomware from a global index perspective. So one thing what we have done is, rather than just looking at vulnerabilities, we showed them the weaknesses that led to the vulnerabilities, and how attackers are using them. And we even talked about DHS, how behind they are in disseminating the information and how it's actually being used by nation states. >> Wow. >> And we did cover mobility as a part of that as well. So there's a quite a bit we did in our report and it actually came out very well. >> I have to check that out. Ransomware is such a fascinating topic. Guys, thank you so much for joining Dave and me on the program today, sharing what's going on at Ivanti, the changes that you're seeing in mobile, and the opportunities that are there for your customers. We appreciate your time. >> Thank you >> Thank you. >> Yes. Thanks, guys. >> Thanks, guys. >> For our guests and for Dave Vellante, I'm Lisa Martin. You're watching "theCUBE" live from MWC23 in Barcelona. As you know, "theCUBE" is the leader in live tech coverage. Dave and I will be right back with our next guest. (gentle upbeat 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)

>> Narrator: theCUBE's live coverage is made possible by funding from Dell Technologies. Creating technologies that drive human progress. (bright upbeat music) >> Good morning everyone. Welcome to theCUBE. We are live at MWC '23 in Barcelona, Spain. I'm Lisa Martin, and I'm going to have a great conversation next with our esteemed CUBE analyst, Dave Nicholson. Dave, great to have you here. Great to be working this event with you. >> Good to be here with you, Lisa. >> So there are, good to be here with you and about 80,000 people. >> Dave: That's right. >> Virtually and and physically. And it's jammed in, and this is the most jammed show I've seen in years. >> Dave: It's crazy. >> So much going on in the telecom industry. What are some of your expectations for what you're going to hear and see at this year's event? >> So, I expect to hear a lot about 5G. Specifically 5G private networks, and the disaggregation of the hardware and software stacks that have driven telecom for decades. So we're at this transition into 5G. From a consumer perspective, we feel like, oh well 5G has been around for years. In terms of where it's actually been deployed, we're just at the beginning stages of that. >> Right, right. Talk about the changing of the stack. You know, the disaggregation. Why now is it too late? And what are the advantages? That it's going to enable telcos to move faster, I imagine? >> Yeah, so it's really analogous to what we see in the general IT industry that we cover so much. The move to cloud, sometimes you're gaining performance. You're always gaining agility and flexibility. A big concern of the legacy telecom providers is going to be maintaining availability, reliability against a backdrop of increasing agility in the direction that they want to go. So that's going to be the conversation. It's going to be the old school folks, who are interested in maintaining primarily availability and performance, excuse me, contrasted with the open source, OpenStack providers, who are going to be saying, hey this is a path to the future. Without that path to the future, things will stagnate. >> Talk about some of those OpenStack providers. I imagine those are some of the folks that we know quite well? >> Sure, sure. Yeah, so someone like Dell, for example. They're perfectly positioned at this sort of crossroads, because Dell has been creating "cloud stacks," that will live sometimes on-premises. And those stacks of infrastructure, based on cots, commercial off-the-shelf components, integrated within an ecosystem can live at the edge, at literally the base of transmitter towers. So when you think about this whole concept of RAN or a radio access network, think of a cellular tower with an antenna and a transmitter. The transmitter might live on that tower, or it might live in pieces at the base of the tower. But there's always at that base of the tower, forget about the acronyms, it's a box of stuff, teleco stuff. All of these things historically have been integrated into single packages. >> Right. >> For good reason. >> Right. >> Think back to a mainframe, where it was utterly, absolutely reliable. We moved, in the general IT space, from the era of the mainframe to the world of client server, through virtualization, containerization. That exact transition is happening in the world of telecom right now. >> Why is it finally happening now? It seems a bit late, given that in our consumer lives, we have this expectation that we could be mobile 24 by seven. >> Right. Well it's because, first of all, we get mad if a call doesn't go through. How often, when you make, when you try to make a cellular call or when you try to send a text, how often does it not work? >> I can count on one hand. >> Right, rarely. >> Right. >> Now, you may be in an area that has spotty coverage. But when you're in an area where you have coverage it just works all of the time. And you expect it to work all of the time. And the miracle of the services that have been delivered to us over the last decade has really kind of blunted the need for next generation stuff. Well, we're at this transition point. And 5G as a technology enables so much more bandwidth. Think of it as, you know, throughput bandwidth latency. It allows the kind of performance characteristics so that things can be delivered that couldn't be delivered in the past. Virtual reality, augmented reality. We're already seeing you know 4K data streams to our phones. So, it's sort of lagged because of our expectations for absolute, rock solid, reliability. >> Yeah. >> The technology is ahead of that area now. And so this question is how do you navigate from utter reliability to awesome openness without sacrificing performance and reliability? >> Well, and also from a stack perspective, from looking at desegregation, and the opportunities there are for the telcos, but also the public cloud providers, are they friends, are they foes? What's the relationship like? >> They're going to be frenemies. >> Lisa: Frenemies? >> Yeah, coopetition is going to be the word of the day again. Yeah because when you think of a cloud, most people automatically think off-premises. >> Lisa: Yes. >> Maybe they even think automatically you know, hyper scale or Azure, GCP, AWS. In this case, it really is a question of cloud as an operating model. Cloud facilitating agility, cloud adopting cloud native architecture from a software perspective, so that you can rapidly deploy net new capabilities into an environment. You can't do that with proprietary closed systems that might use a waterfall development process and take years to develop. You and I have covered the Kubernetes world pretty closely. And what's the big thing that we hear constantly? The hunger, the thirst for human resources, >> Right. >> people who can actually work in this world of containerization. >> Yes, yes. >> Well guess what? In the macroeconomic environment, a lot of folks in the IT space have recently been disrupted. This is a place to look, if you have that skillset. Look at the telecom space, because they need people who are forward thinking in the era of cloud. But this concept of cloud is really, it's going to be, the telcos are both competing and partnering with what we think of as the traditional, hyper scale public cloud providers. >> And what do you think, one of the things that we know at MWC '23 is virtually every industry is represented here. Every vertical is here, whether it's a sports arena, or a retail outlet, or a manufacturer. Every organization, every industry needs to have networks that deliver what they need to do but also enable them to move faster and deliver what the end user wants. What are some of the industries that you think are really ripe for this disruption? And the ability to use private 5G networks, for example? >> Well, so it's interesting, you mentioned private 5G networks. I think a good example of the transition that's underway is this, the move to 4K video. So, you get a high definition television. The first time you see a 720p TV, it's like oh my gosh, amazing. Then we get 1080p, then it's 4K. People get 4K TVs, they bring them home, and there's no content. >> No. >> The first content, was it from your cable provider? No. >> Yeah. >> Was it over the air? ABC, NBC, CBS? No, it was YouTube. YouTube delivered the first reliable 4K content, over the internet. Similarly, everything comes to us now to our mobile devices. So we're not accessing the world around us so much from a desktop or even a laptop. It's mobile. So if you want to communicate with a customer, it's mobile. If you're creating a private 5G network, you now are standing something up that is net new in a greenfield environment. And you can deploy agility and functionality that the large scale telecom providers can't, because of the massive investment they might need. So the irony is, you have a factory that sits on 20 acres and you have folks traveling around, if you create a private 5G network, it might become, it might be more feature rich than what your employees are used to being able to access through their personal mobile devices. >> Wow. >> Yeah, because you're starting net new, you have the luxury of starting greenfield, as opposed to the responsibility and legacy for supporting a massive system that exists already. >> So then, what's in it for the existing incumbent telcos from an advantage opportunity perspective? Because you mentioned frenemies, coopetition. >> Right. >> There's irony there, as you talked about. >> Right, well you could look at it as either opportunity or headache. And it's both. Because they have very, very real SLAs that they need to meet. >> Right. >> Very, very real expectations that have been set in terms of reliability, availability, and performance. So they can't slip off of that. Making that transition is, I think going to be driven by economics, because the idea of having things be open means that there's competition for every part of the stack. There will be a critical role for integration vendors. Folks like Dell, and the ecosystems that they're creating around this will be critical, because often you would prefer to have one back to pat or one throat to choke instead of many. So, you still want to have that centralized entity to go to when something goes wrong. >> Right. >> Or when you want to implement something new. So, for the incumbents, it's a classic example of what you do in the face of disruption. How do you leverage technology? In my role as adjunct faculty at the Wharton CTO Academy, we talk about the CTO mindset. And the idea that your role is to leverage technology, in the service of your organization's mission, whatever that organization and mission is. So from a telecom provider perspective, they need to stay on top of this. >> Yes. >> Or they will be disrupted. >> Right. >> It's fascinating to think of how this disruption's taking place. >> Lisa: They have no choice, if they want to survive. >> No, yeah they have no choice. >> Lisa: In the next few years. >> They have no choice, but they'll come along, kicking and screaming. I'm sure if you had someone sitting here in the industry, they'd say, well, no, no, no, no, no. >> Yeah, of course. >> We love it! It's like, yeah, well but you're going to have to make some painful changes to adopt these things. >> What are some of the opportunities for those folks like Dell that you mentioned, in terms of coming in, being able to disrupt that stack, open things up? Great opportunities for the Dells, and other similar organizations to really start gaining a bigger foothold in the telecom industry, I imagine. >> Well, I look at it through the lens of sort of traditional IT and the transitions that we've been watching for the last couple of decades. It's exactly the same. I mean you, there is a parallel. It is like coming out of the mainframe era to the client server era. So, you know, we went in that transition, it was mainframe operating systems, very, very closed systems to more slightly opened. You know, the worlds of SUN and SGI and HP, and the likes, transitioned to kind of Microsoft based software running with like Dell hardware. >> Yeah. >> And, that stack is now getting deployed into one of the remaining legacy environments which is the telco space. So, the opportunity for Dell is pretty massive because on some fronts they're competing with the move to proper off-premises public cloud. >> Right. >> In this case, they are the future for telecom as opposed to sort of representing legacy, compared to some of the other cloud opportunities that are out there. >> So ultimately, what does a modern telecom network look like? I imagine, cloud native? Distributed? >> Yeah, yeah. So, traditionally, like I said, you've got the tower and the transmitters and the computer hardware that's running it. Those are then networked together. So you can sort of think of it as leaves on a twig, on a branch, on a tree. Eventually it gets into a core network, where there is terrestrial line communication and or communication up to satellites. And that's all been humming along just fine, making the transition from 3G to 4G to 5G. But, the real transition from a cloud perspective is this idea that you're taking these proprietary systems, disaggrevating, disaggrevating them and disaggregating them, carving them up into pieces where now you're introducing virtualization. So there's a VMware play here. Some things are virtualized using that stack. I think more often we're going to be talking about containerized and truly cloud native stacks. So instead of having the proprietary stack, where all the hardware and software is designed together. Now you're going to have Dell servers running some execution layer, orchestration layer, for cloud native, containerized applications and microservices. And that's the way things are going to be developed. >> And who, from a stakeholder perspective is involved here? 'Cause one of the things that I'm hearing is with this disaggregation of the staff, which is a huge change, what you're articulated, that's already happened at enterprise IT, change management is a hard thing to do. If they want to be successful, and well not just survive, they want to thrive. I'm just imagining, who are the stakeholders that are involved in having to push those incumbents to make these decisions, to move faster, to become agile, to compete. >> So, I remember when VMware had the problem that anytime they suggested introducing a hypervisor to to virtualize a physical machine and then run software on top or an operating system on top, and then applications, the big question the customer would have was, well is Microsoft going to support that? What if I can't get support from Microsoft? I dunno if I can do this. Within about a year of those conversations taking place, the question was, can I run this in my production environment? So it was, can I get support in my test environment too? Can I please run this in production? >> Yeah. >> And so, there are folks in the kind of legacy telecom world who are going to be afraid. It's, whatever the dynamic is, there is a no one ever got fired for buying from fill in the blank >> Exactly, yep. >> in the telecom space. >> Yeah, yeah. >> Because they would buy a consolidated, aggregated stack. >> Right. >> And, if something went wrong they could say, boom, blame you. And yeah, that stack doesn't lend itself to the kind of pace of change. >> Right. >> So it doesn't necessarily need the same kind of change management. Or at least it's very, very centralized. >> Okay. Okay. >> We're getting into the brave new world of things where if you let them spin out of control, you can have big problems. And that's where the folks like Dell come in, to make sure that yes, disaggregated, yes best of commercial off-the-shelf stuff, but also the best in terms of performance and reliability and availability. >> Yeah. >> So, that's the execution part, you must execute flawlessly. >> It sounds like from a thematic perspective, the theme of MWC '23 is velocity. But it seems like an underlying theme under that, or maybe an overlying theme is disruption. It's going to be so interesting, we're only on day one. We just started our coverage. Four days of wall to wall coverage on theCUBE. Excited to hear what you're excited about, what you learn over the next few days. We get to host some segments together. >> Yeah. >> But it seems like disruption is the overall theme. And it's going to be so interesting to see how this industry evolves, what the opportunities are, what the coopetition opportunities are. We're going to be learning a lot this week. I'm excited. >> Yeah, and what's fascinating to me about this whole thing is we talk about this, all of this tumultuous, disruptive stuff that's happening. For the average consumer, they're never going to be aware of it. >> Nope. >> Dave: They're just going to see services piled on top of services. >> Which is what we want. >> There are billions of people with mobile devices and the hundreds of billions, I don't know, trillions I guess at some point of connected devices at the edge. >> Lisa: Yes, yes. >> The whole concept of the internet of things. We'll sort of be blissfully unaware of what's happening at the middle. But there's a lot of action there. So we're going to be focusing on that action that's going on. In, you know, in in the middle of it. >> Yeah. >> But there's also some cool consumer stuff out here. >> There is. >> I know I'm going to be checking out the augmented reality and virtual reality stuff. >> Yeah, yeah. Well it's all about that customer experience. We expect things right away, 24/7, wherever we are in the world. And it's enabling that to make that happen. >> Yeah. >> Dave, thank you so much for really sharing what you think you're excited about for the event and some of the trends in telecom. It sounds like it's such an interesting time to be unpacking this. >> It's going to be a great week. >> It is going to be a great week. All right, for Dave Nicholson, I'm Lisa Martin. You're watching theCUBE, the leader in live tech coverage, covering day one of MWC '23. Stick around. We'll be back with our next guest in just a minute. (bright music resumes) (music fades out)

(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 music) >> Welcome back, everybody, to the Supercloud 2. My name is Dave Vellante. And I'm pleased to welcome Nir Zuk. He's the founder and CTO of Palo Alto Networks. Nir, good to see you again. Welcome. >> Same here. Good to see you. >> So let's start with the right security architecture in the context of today's fragmented market. You've got a lot of different tools, you've got different locations, on-prem, you've got hardware and software. Tell us about the right security architecture from your standpoint. What's that look like? >> You know, the funny thing is using the word security in architecture rarely works together. (Dave chuckles) If you ask a typical information security person to step up to a whiteboard and draw their security architecture, they will look at you as if you fell from the moon. I mean, haven't you been here in the last 25 years? There's no security architecture. The architecture today is just buying a bunch of products and dropping them into the infrastructure at some relatively random way without really any guiding architecture. And that's a huge challenge in cybersecurity. It's always been, we've always tried to find ways to put an architecture into writing blueprints, whatever you want to call it, and it's always been difficult. Luckily, two things. First, there's something called zero trust, which we can talk a little bit about more, if you want, and zero trust among other things is really a way to create a security architecture, and second, because in the cloud, in the supercloud, we're starting from scratch, we can do things differently. We don't have to follow the way we've always done cybersecurity, again, buying random products, okay, maybe not random, maybe there is some thinking going into it by buying products, one of the other, dropping them in, and doing it over 20 years and ending up with a mess in the cloud, we have an opportunity to do it differently and really have an architecture. >> You know, I love talking to founders and particularly technical founders from StartupNation. I think I saw an article, I think it was Erie Levine, one of the founders or co-founders of Waze, and he had a t-shirt on, it said, "Fall in love with the problem, not the solution." Is that how you approached architecture? You talk about zero trust, it's a relatively new term, but was that in your head when you thought about forming the company? >> Yeah, so when I started Palo Alto Networks, exactly, by the way, 17 years ago, we got funded January, 2006, January 18th, 2006. The idea behind Palo Alto Networks was to create a security platform and over time take more and more cybersecurity functions and deliver them on top of that platform, by the way, as a service, SaaS. Everybody thought we were crazy trying to combine many functions into one platform, best of breed and defense in death and putting all your eggs in the same basket and a bunch of other slogans were flying around, and also everybody thought we were crazy asking customers to send information to the cloud in order to secure themselves. Of course, step forward 17 years, everything is now different. We changed the market. Almost all of cybersecurity today is delivered as SaaS and platforms are ruling more and more the world. And so again, the idea behind the platform was to over time take more and more cybersecurity functions and deliver them together, one brain, one decision being made for each and every packet or system call or file or whatever it is that you're making the decision about and it works really, really well. As a side effect, when you combine that with zero trust and you end up with, let's not call it an architecture yet. You end up with with something where any user, any location, both geographically as well as any location in terms of branch office, headquarters, home, coffee shop, hotel, whatever, so any user, any geographical location, any location, any connectivity method, whether it is SD1 or IPsec or Client VPN or Client SVPN or proxy or browser isolation or whatever and any application deployed anywhere, public cloud, private cloud, traditional data center, SaaS, you secure the same way. That's really zero trust, right? You secure everything, no matter who the user is, no matter where they are, no matter where they go, you secure them exactly the same way. You don't make any assumptions about the user or the application or the location or whatever, just because you trust nothing. And as a side effect, when you do that, you end up with a security architecture, the security architecture I just described. The same thing is true for securing applications. If you try to really think and not just act instinctively the way we usually do in cybersecurity and you say, I'm going to secure my traditional data center applications or private cloud applications and public cloud applications and my SaaS applications the same way, I'm not going to trust something just because it's deployed in the private data center. I'm not going to trust two components of an application or two applications talking to each other just because they're deployed in the same place versus if one component is deployed in one public cloud and the other component is deployed in another public cloud or private cloud or whatever. I'm going to secure all of them the same way without making any trust assumptions. You end up with an architecture for securing your applications, which is applicable for the supercloud. >> It was very interesting. There's a debate I want to pick up on what you said because you said don't call it an architecture yet. So Bob Muglia, I dunno if you know Bob, but he sort of started the debate, said, "Supercloud, think of it as a platform, not an architecture." And there are others that are saying, "No, no, if we do that, then we're going to have a bunch of more stove pipes. So there needs to be standard, almost a purist view. There needs to be a supercloud architecture." So how do you think about it? And it's a bit academic, I know, but do you think of this idea of a supercloud, this layer of value on top of the hyperscalers, do you think of that as a platform approach that each of the individual vendors are responsible for the architecture? Or is there some kind of overriding architecture of standards that needs to emerge to enable the supercloud? >> So we can talk academically or we can talk practically. >> Yeah, let's talk practically. That's who you are. (Dave laughs) >> Practically, this world is ruled by financial interests and none of the public cloud providers, especially the bigger they are has any interest of making it easy for anyone to go multi-cloud, okay? Also, on top of that, if we want to be even more practical, each of those large cloud providers, cloud scale providers have engineers and all these engineers think they're the best in the world, which they are and they all like to do things differently. So you can't expect things in AWS and in Azure and GCP and in the other clouds like Oracle and Ali and so on to be the same. They're not going to be the same. And some things can be abstracted. Maybe cloud storage or bucket storage can be abstracted with the layer that makes them look the same no matter where you're running. And some things cannot be abstracted and unfortunately will not be abstracted because the economical interest and the way engineers work won't let it happen. We as a third party provider, cybersecurity provider, and I'm sure other providers in other areas as well are trying or we're doing our best. We're not trying, we are doing our best, and it's pretty close to being the way you describe the top of your supercloud. We're building something that abstracts the underlying cloud such that securing each of these clouds, and by the way, I would add private cloud to it as well, looks exactly the same. So we use, almost always, whenever possible, the same terminology, no matter which cloud we're securing and the same policy and the same alerts and the same information and so on. And that's also very important because when you look at the people that actually end up using the product, security engineers and more importantly, SOC, security operations center analysts, they're not going to study the details of each and every cloud. It's just going to be too much. So we need to abstract it for them. >> Yeah, we agree by the way that the supercloud definition is inclusive of on-prem, you know, what you call private cloud. And I want to pick up on something else you said. I think you're right that abstracting and making consistent across clouds something like object storage, get put, you know, whether it's an S3 bucket or an Azure Blob, relatively speaking trivial. When you now bring that supercloud concept to something more complex like security, first of all, as a technically feasible and inferring the answer there is yes, and if so, what do you see as the main technical challenges of doing so? >> So it is feasible to the extent that the different cloud provide the same functionality. Then you step into a territory where different cloud providers have different paths services and different cloud providers do things a little bit differently and they have different sets of permissions and different logging that sometimes provides all the information and sometimes it doesn't. So you end up with some differences. And then the question is, do you abstract the lowest common dominator and that's all you support? Or do you find a way to be smarter than that? And yeah, whatever can be abstracted is abstracted and whatever cannot be abstracted, you find an easy way to represent that to your users, security engineers, security analysts, and so on, which is what I believe we do. >> And you do that by what? Inventing or developing technology that presents that experience to users? Could you be more specific there? >> Yeah, so different cloud providers call their storage in different names and you use different ways to configure them and the logs come out the same. So we normalize it. I mean, the keyword is probably normalization. Normalize it. And we try to, you know, then you have to pick a winner here and to use someone's terminology or you need to invent new terminology. So we try to use the terminology of the largest cloud provider so that we have a better chance of doing that but we can't always do that because they don't support everything that other cloud providers provide, but the important thing is, with or thanks to that normalization, our customers both on the engineering side and on the user side, operations side end up having to learn one terminology in order to set policies and understand attacks and investigate incidents. >> I wonder if I could pick your brain on what you see as the ideal deployment model to achieve this supercloud experience. For example, do you think instantiating your stack in multiple regions and multiple clouds is the right way to do it? Or is building a single global instance on top of the clouds a more preferable way? Are maybe other models we should consider? What do you see as the trade off of these different deployment models and which one is ideal in your view? >> Yeah, so first, when you deploy cloud security, you have to decide whether you're going to use agents or not. By agents, I mean something working, something running inside the workload. Inside a virtual machine on the container host attached to function, serverless function and so on and I, of course, recommend using agents because that enables prevention, it enables functionality you cannot get without agents but you have to choose that. Now, of course, if you choose agent, you need to deploy AWS agents in AWS and GCP agents in GCP and Azure agents in Azure and so on. Of course, you don't do it manually. You do it through the CICD pipeline. And then the second thing that you need to do is you need to connect with the consoles. Of course, that can be done over the internet no matter where your security instances is running. You can run it on premise, you can run it in one of the other different clouds. Of course, we don't run it on premise. We prefer not to run it on premise because if you're secured in cloud, you might as well run in the cloud. And then the question is, for example, do you run a separate instance for AWS for GCP or for Azure, or you want to run one instance for all of them in one of these clouds? And there are advantages and disadvantages. I think that from a security perspective, it's always better to run in one place because then when you collect the information, you get information from all the clouds and you can start looking for cross-cloud issues, incidents, attacks, and so on. The downside of that is that you need to send all the information to one of the clouds and you probably know that sending data out of the cloud costs a lot of money versus keeping it in the cloud. So theoretically, you can build an architecture where you keep the data for AWS in AWS, Azure in Azure, GCP in GCP, and then you try to run distributed queries. When you do that, you find out you'd end up paying more for the compute to do that than you would've paid for sending all the data to a central location. So we prefer the approach of running in one place, bringing all the data there, and running all the security, the machine learning or whatever, the rules or whatever it is that you're running in one place versus trying to create a distributed deployment in order to try to save some money on the data, the network data transfers. >> Yeah, thank you for that. That makes a lot of sense. And so basically, should we think about the next layer building security data lake, if you will, and then running machine learning on top of that if I can use that term of a data lake or a lake house? Is that sort of where you're headed? >> Yeah, look, the world is headed in that direction, not just the cybersecurity world. The world is headed from being rule-based to being data-based. So cybersecurity is not different and what we used to do with rules in the past, we're now doing with machine learning. So in the past, you would define rules saying, if you see this, this, and this, it's an attack. Now you just throw the data at the machine, I mean, I'm simplifying it, but you throw data at a machine. You'll tell the machine, find the attack in the data. It's not that simple. You need to build the right machine learning models. It needs to be done by people that are both cybersecurity experts and machine learning experts. We do it mostly with ex-military offensive people that take their offensive knowledge and translate it into machine learning models. But look, the world is moving in that direction and cybersecurity is moving in that direction as well. You need to collect a lot of data. Like I said, I prefer to see all the data in one place so that the machine learning can be much more efficient, pay for transferring the data, save money on the compute. >> I think the drop the mic quote it ignite that you had was within five years, your security operation is going to be AI-powered. And so you could probably apply that to virtually any job over the next five years. >> I don't know if any job. Certainly writing essays for school is automated already as we've seen with ChatGPT and potentially other things. By the way, we need to talk at some point about ChatGPT security. I don't want to think what happens when someone spends a lot of money on creating a lot of fake content and teaches ChatGPT the wrong answer to a question. We start seeing ChatGPT as the oracle of everything. We need to figure out what to do with the security of that. But yeah, things have to be automated in cybersecurity. They have to be automated. They're just too much data to deal with and it's just not even close to being good enough to wait for an incident to happen and then going investigate the incident based on the data that we have. It's better to look at all the data all the time, millions of events per second, and find those incidents before they happen. There's no way to do that without machine learning. >> I'd love to have you back and talk about ChatGPT. I know they're trying to put in some guardrails but there are a lot of unintended consequences, aren't there? >> Look, if they're not going to have a person filtering the data, then with enough money, you can create thousands or tens of thousands of pieces of articles or whatever that look real and teach the machine something that is totally wrong. >> We were talking about the hyper skills before and I agree with you. It's very unlikely they're going to get together, band together, and create these standards. But it's not a static market. It's a moving train, if you will. So assuming you're building this cross cloud experience which you are, what do you want from the hyperscalers? What do you want them to bring to the table? What is a technology supplier like Palo Alto Networks bring? In other words, where do you see ongoing as your unique value add and that moat that you're building and how will that evolve over time vis-a-vis the hyperscaler evolution? >> Yeah, look, we need APIs. The more data we have, the more access we have to more data, the less restricted the access is and the cheaper the access is to the data because someone has to pay today for some reason for accessing that data, the more secure their customers are going to be. So we need help and are helping by the way a lot, all of them in finding easy ways for customers to deploy things in the cloud, access data, and again, a lot of data, very diversified data and do it in a cost-effective way. >> And when we talk about the edge, I presume you look at the edge as just another data center or maybe it's the reverse. Maybe the data center is just another edge location, but you're seeing specific edge security solutions come out. I'm guessing that you would say, that's not what we want. Edge should be part of that architecture that we talked about earlier. Do you agree? >> Correct, it should be part of the architecture. I would also say that the edge provides an opportunity specifically for network security, whereas traditional network security would be deployed on premise. I'm talking about internet security but half network security market, and not just network security but also the other network intelligent functions like routing and QS. We're seeing a trend of pushing those to the edge of the cloud. So what you deploy on premise is technology for bringing packets to the edge of the cloud and then you run your security at the edge, whatever that edge is, whether it's a private edge or public edge, you run it in the edge. It's called SASE, Secure Access Services Edge, pronounced SASE. >> Nir, I got to thank you so much. You're such a clear thinker. I really appreciate you participating in Supercloud 2. >> Thank you. >> All right, keep it right there for more content covering the future of cloud and data. This is Dave Vellante for John Furrier. I'll be right back. (bright upbeat music)

>> Welcome back to SuperCloud2. This is Dave Vellante, and we're here with Jack Greenfield. He's the Vice President of Enterprise Architecture and the Chief Architect for the global technology platform at Walmart. Jack, I want to thank you for coming on the program. Really appreciate your time. >> Glad to be here, Dave. Thanks for inviting me and appreciate the opportunity to chat with you. >> Yeah, it's our pleasure. Now we call what you've built a SuperCloud. That's our term, not yours, but how would you describe the Walmart Cloud Native Platform? >> So WCNP, as the acronym goes, is essentially an implementation of Kubernetes for the Walmart ecosystem. And what that means is that we've taken Kubernetes off the shelf as open source, and we have integrated it with a number of foundational services that provide other aspects of our computational environment. So Kubernetes off the shelf doesn't do everything. It does a lot. In particular the orchestration of containers, but it delegates through API a lot of key functions. So for example, secret management, traffic management, there's a need for telemetry and observability at a scale beyond what you get from raw Kubernetes. That is to say, harvesting the metrics that are coming out of Kubernetes and processing them, storing them in time series databases, dashboarding them, and so on. There's also an angle to Kubernetes that gets a lot of attention in the daily DevOps routine, that's not really part of the open source deliverable itself, and that is the DevOps sort of CICD pipeline-oriented lifecycle. And that is something else that we've added and integrated nicely. And then one more piece of this picture is that within a Kubernetes cluster, there's a function that is critical to allowing services to discover each other and integrate with each other securely and with proper configuration provided by the concept of a service mesh. So Istio, Linkerd, these are examples of service mesh technologies. And we have gone ahead and integrated actually those two. There's more than those two, but we've integrated those two with Kubernetes. So the net effect is that when a developer within Walmart is going to build an application, they don't have to think about all those other capabilities where they come from or how they're provided. Those are already present, and the way the CICD pipelines are set up, it's already sort of in the picture, and there are configuration points that they can take advantage of in the primary YAML and a couple of other pieces of config that we supply where they can tune it. But at the end of the day, it offloads an awful lot of work for them, having to stand up and operate those services, fail them over properly, and make them robust. All of that's provided for. >> Yeah, you know, developers often complain they spend too much time wrangling and doing things that aren't productive. So I wonder if you could talk about the high level business goals of the initiative in terms of the hardcore benefits. Was the real impetus to tap into best of breed cloud services? Were you trying to cut costs? Maybe gain negotiating leverage with the cloud guys? Resiliency, you know, I know was a major theme. Maybe you could give us a sense of kind of the anatomy of the decision making process that went in. >> Sure, and in the course of answering your question, I think I'm going to introduce the concept of our triplet architecture which we haven't yet touched on in the interview here. First off, just to sort of wrap up the motivation for WCNP itself which is kind of orthogonal to the triplet architecture. It can exist with or without it. Currently does exist with it, which is key, and I'll get to that in a moment. The key drivers, business drivers for WCNP were developer productivity by offloading the kinds of concerns that we've just discussed. Number two, improving resiliency, that is to say reducing opportunity for human error. One of the challenges you tend to run into in a large enterprise is what we call snowflakes, lots of gratuitously different workloads, projects, configurations to the extent that by developing and using WCNP and continuing to evolve it as we have, we end up with cookie cutter like consistency across our workloads which is super valuable when it comes to building tools or building services to automate operations that would otherwise be manual. When everything is pretty much done the same way, that becomes much simpler. Another key motivation for WCNP was the ability to abstract from the underlying cloud provider. And this is going to lead to a discussion of our triplet architecture. At the end of the day, when one works directly with an underlying cloud provider, one ends up taking a lot of dependencies on that particular cloud provider. Those dependencies can be valuable. For example, there are best of breed services like say Cloud Spanner offered by Google or say Cosmos DB offered by Microsoft that one wants to use and one is willing to take the dependency on the cloud provider to get that functionality because it's unique and valuable. On the other hand, one doesn't want to take dependencies on a cloud provider that don't add a lot of value. And with Kubernetes, we have the opportunity, and this is a large part of how Kubernetes was designed and why it is the way it is, we have the opportunity to sort of abstract from the underlying cloud provider for stateless workloads on compute. And so what this lets us do is build container-based applications that can run without change on different cloud provider infrastructure. So the same applications can run on WCNP over Azure, WCNP over GCP, or WCNP over the Walmart private cloud. And we have a private cloud. Our private cloud is OpenStack based and it gives us some significant cost advantages as well as control advantages. So to your point, in terms of business motivation, there's a key cost driver here, which is that we can use our own private cloud when it's advantageous and then use the public cloud provider capabilities when we need to. A key place with this comes into play is with elasticity. So while the private cloud is much more cost effective for us to run and use, it isn't as elastic as what the cloud providers offer, right? We don't have essentially unlimited scale. We have large scale, but the public cloud providers are elastic in the extreme which is a very powerful capability. So what we're able to do is burst, and we use this term bursting workloads into the public cloud from the private cloud to take advantage of the elasticity they offer and then fall back into the private cloud when the traffic load diminishes to the point where we don't need that elastic capability, elastic capacity at low cost. And this is a very important paradigm that I think is going to be very commonplace ultimately as the industry evolves. Private cloud is easier to operate and less expensive, and yet the public cloud provider capabilities are difficult to match. >> And the triplet, the tri is your on-prem private cloud and the two public clouds that you mentioned, is that right? >> That is correct. And we actually have an architecture in which we operate all three of those cloud platforms in close proximity with one another in three different major regions in the US. So we have east, west, and central. And in each of those regions, we have all three cloud providers. And the way it's configured, those data centers are within 10 milliseconds of each other, meaning that it's of negligible cost to interact between them. And this allows us to be fairly agnostic to where a particular workload is running. >> Does a human make that decision, Jack or is there some intelligence in the system that determines that? >> That's a really great question, Dave. And it's a great question because we're at the cusp of that transition. So currently humans make that decision. Humans choose to deploy workloads into a particular region and a particular provider within that region. That said, we're actively developing patterns and practices that will allow us to automate the placement of the workloads for a variety of criteria. For example, if in a particular region, a particular provider is heavily overloaded and is unable to provide the level of service that's expected through our SLAs, we could choose to fail workloads over from that cloud provider to a different one within the same region. But that's manual today. We do that, but people do it. Okay, we'd like to get to where that happens automatically. In the same way, we'd like to be able to automate the failovers, both for high availability and sort of the heavier disaster recovery model between, within a region between providers and even within a provider between the availability zones that are there, but also between regions for the sort of heavier disaster recovery or maintenance driven realignment of workload placement. Today, that's all manual. So we have people moving workloads from region A to region B or data center A to data center B. It's clean because of the abstraction. The workloads don't have to know or care, but there are latency considerations that come into play, and the humans have to be cognizant of those. And automating that can help ensure that we get the best performance and the best reliability. >> But you're developing the dataset to actually, I would imagine, be able to make those decisions in an automated fashion over time anyway. Is that a fair assumption? >> It is, and that's what we're actively developing right now. So if you were to look at us today, we have these nice abstractions and APIs in place, but people run that machine, if you will, moving toward a world where that machine is fully automated. >> What exactly are you abstracting? Is it sort of the deployment model or, you know, are you able to abstract, I'm just making this up like Azure functions and GCP functions so that you can sort of run them, you know, with a consistent experience. What exactly are you abstracting and how difficult was it to achieve that objective technically? >> that's a good question. What we're abstracting is the Kubernetes node construct. That is to say a cluster of Kubernetes nodes which are typically VMs, although they can run bare metal in certain contexts, is something that typically to stand up requires knowledge of the underlying cloud provider. So for example, with GCP, you would use GKE to set up a Kubernetes cluster, and in Azure, you'd use AKS. We are actually abstracting that aspect of things so that the developers standing up applications don't have to know what the underlying cluster management provider is. They don't have to know if it's GCP, AKS or our own Walmart private cloud. Now, in terms of functions like Azure functions that you've mentioned there, we haven't done that yet. That's another piece that we have sort of on our radar screen that, we'd like to get to is serverless approach, and the Knative work from Google and the Azure functions, those are things that we see good opportunity to use for a whole variety of use cases. But right now we're not doing much with that. We're strictly container based right now, and we do have some VMs that are running in sort of more of a traditional model. So our stateful workloads are primarily VM based, but for serverless, that's an opportunity for us to take some of these stateless workloads and turn them into cloud functions. >> Well, and that's another cost lever that you can pull down the road that's going to drop right to the bottom line. Do you see a day or maybe you're doing it today, but I'd be surprised, but where you build applications that actually span multiple clouds or is there, in your view, always going to be a direct one-to-one mapping between where an application runs and the specific cloud platform? >> That's a really great question. Well, yes and no. So today, application development teams choose a cloud provider to deploy to and a location to deploy to, and they have to get involved in moving an application like we talked about today. That said, the bursting capability that I mentioned previously is something that is a step in the direction of automatic migration. That is to say we're migrating workload to different locations automatically. Currently, the prototypes we've been developing and that we think are going to eventually make their way into production are leveraging Istio to assess the load incoming on a particular cluster and start shedding that load into a different location. Right now, the configuration of that is still manual, but there's another opportunity for automation there. And I think a key piece of this is that down the road, well, that's a, sort of a small step in the direction of an application being multi provider. We expect to see really an abstraction of the fact that there is a triplet even. So the workloads are moving around according to whatever the control plane decides is necessary based on a whole variety of inputs. And at that point, you will have true multi-cloud applications, applications that are distributed across the different providers and in a way that application developers don't have to think about. >> So Walmart's been a leader, Jack, in using data for competitive advantages for decades. It's kind of been a poster child for that. You've got a mountain of IP in the form of data, tools, applications best practices that until the cloud came out was all On Prem. But I'm really interested in this idea of building a Walmart ecosystem, which obviously you have. Do you see a day or maybe you're even doing it today where you take what we call the Walmart SuperCloud, WCNP in your words, and point or turn that toward an external world or your ecosystem, you know, supporting those partners or customers that could drive new revenue streams, you know directly from the platform? >> Great questions, Dave. So there's really two things to say here. The first is that with respect to data, our data workloads are primarily VM basis. I've mentioned before some VMware, some straight open stack. But the key here is that WCNP and Kubernetes are very powerful for stateless workloads, but for stateful workloads tend to be still climbing a bit of a growth curve in the industry. So our data workloads are not primarily based on WCNP. They're VM based. Now that said, there is opportunity to make some progress there, and we are looking at ways to move things into containers that are currently running in VMs which are stateful. The other question you asked is related to how we expose data to third parties and also functionality. Right now we do have in-house, for our own use, a very robust data architecture, and we have followed the sort of domain-oriented data architecture guidance from Martin Fowler. And we have data lakes in which we collect data from all the transactional systems and which we can then use and do use to build models which are then used in our applications. But right now we're not exposing the data directly to customers as a product. That's an interesting direction that's been talked about and may happen at some point, but right now that's internal. What we are exposing to customers is applications. So we're offering our global integrated fulfillment capabilities, our order picking and curbside pickup capabilities, and our cloud powered checkout capabilities to third parties. And this means we're standing up our own internal applications as externally facing SaaS applications which can serve our partners' customers. >> Yeah, of course, Martin Fowler really first introduced to the world Zhamak Dehghani's data mesh concept and this whole idea of data products and domain oriented thinking. Zhamak Dehghani, by the way, is a speaker at our event as well. Last question I had is edge, and how you think about the edge? You know, the stores are an edge. Are you putting resources there that sort of mirror this this triplet model? Or is it better to consolidate things in the cloud? I know there are trade-offs in terms of latency. How are you thinking about that? >> All really good questions. It's a challenging area as you can imagine because edges are subject to disconnection, right? Or reduced connection. So we do place the same architecture at the edge. So WCNP runs at the edge, and an application that's designed to run at WCNP can run at the edge. That said, there are a number of very specific considerations that come up when running at the edge, such as the possibility of disconnection or degraded connectivity. And so one of the challenges we have faced and have grappled with and done a good job of I think is dealing with the fact that applications go offline and come back online and have to reconnect and resynchronize, the sort of online offline capability is something that can be quite challenging. And we have a couple of application architectures that sort of form the two core sets of patterns that we use. One is an offline/online synchronization architecture where we discover that we've come back online, and we understand the differences between the online dataset and the offline dataset and how they have to be reconciled. The other is a message-based architecture. And here in our health and wellness domain, we've developed applications that are queue based. So they're essentially business processes that consist of multiple steps where each step has its own queue. And what that allows us to do is devote whatever bandwidth we do have to those pieces of the process that are most latency sensitive and allow the queue lengths to increase in parts of the process that are not latency sensitive, knowing that they will eventually catch up when the bandwidth is restored. And to put that in a little bit of context, we have fiber lengths to all of our locations, and we have I'll just use a round number, 10-ish thousand locations. It's larger than that, but that's the ballpark, and we have fiber to all of them, but when the fiber is disconnected, When the disconnection happens, we're able to fall back to 5G and to Starlink. Starlink is preferred. It's a higher bandwidth. 5G if that fails. But in each of those cases, the bandwidth drops significantly. And so the applications have to be intelligent about throttling back the traffic that isn't essential, so that it can push the essential traffic in those lower bandwidth scenarios. >> So much technology to support this amazing business which started in the early 1960s. Jack, unfortunately, we're out of time. I would love to have you back or some members of your team and drill into how you're using open source, but really thank you so much for explaining the approach that you've taken and participating in SuperCloud2. >> You're very welcome, Dave, and we're happy to come back and talk about other aspects of what we do. For example, we could talk more about the data lakes and the data mesh that we have in place. We could talk more about the directions we might go with serverless. So please look us up again. Happy to chat. >> I'm going to take you up on that, Jack. All right. This is Dave Vellante for John Furrier and the Cube community. Keep it right there for more action from SuperCloud2. (upbeat music)

(upbeat music) >> Hello, and welcome to Supercloud2. I'm John Furrier, host of theCUBE here. We're exploring all the new Supercloud trends around multiple clouds, hyper scale gaps in their systems, new innovations, new applications, new companies, new products, new brands emerging from this big inflection point. Got a great guest who's going to unpack it with me today, Ramesh Prabagaran, who's the co-founder and CEO of Prosimo, CUBE alumni. Ramesh, legend in the industry, you've been around. You've seen many cycles. Welcome to Supercloud2. >> Thank you. You're being too kind. >> Well, you know, you guys have been a technical, great technical founding team, multiple ventures, multiple times around the track as they say, but now we're seeing something completely different. This is our second event, kind of we're doing to start the the ball rolling around unpacking this idea of Supercloud which evolved from a riff with me and Dave to now a working group paper, multiple definitions. People are saying they're Supercloud. CloudFlare says this is their version. Someone says there over there. Fitzi over there in the blog is always, you know, challenging us on our definitions, but it's, the consensus is though something's happening. >> Ramesh: Absolutely. >> And what's your take on this kind of big inflection point? >> Absolutely, so if you just look at kind of this in layers right, so you have hyper scalers that are innovating really quickly on underlying capabilities, and then you have enterprises adopting these technologies, right, there is a layer in the middle that I would say is largely missing, right? And one that addresses the gaps introduced by these new capabilities, by the hyper scalers. At the same time, one that actually spans, let's say multiple regions, multiple clouds and so forth. So that to me is kind of the Supercloud layer of sorts. One that helps enterprises adopt the underlying hyper scaler capabilities a lot faster, and at the same time brings a certain level of consistency and homogeneity also. >> What do you think the big driver of Supercloud is? Is it the industry growing up or is it the demand for new kinds of capabilities or both? Or just evolution? What's your take? >> I would say largely it depends on kind of who the entity is that you're talking about, right? And so I would say both. So if you look at one cohort here, it's adoption, right? If I have a externally facing digital presence, for example, then I'm going to scale that up and get to as many subscribers and users no matter what, right? And at that time it's a different set of problems. If you're looking at kind of traditional enterprise inward that are bringing apps into the cloud and so forth, it's a different set of care abouts, right? So both are, I would say, equally important problems to solve for. >> Well, one reality that we're definitely tracking, and it's not really a debate anymore, is hybrid. >> Ramesh: Yep >> Hybrid happened. It happened faster than most people thought. But, you know, we were talking about this in 2015 when it first got kicked around, but now you see hybrid in the cloud, on premises and the edge. This kind of forms that distributed computing paradigm that we've always been predicting. And so if that continues to play out the way it is, you're now going to have a completely distributed, connected internet and sets of systems, intra and external within companies. So again, the world is connected 100%. Everything's changing, right? >> And that introduces. >> It wasn't your grandfather's networking anymore or storage. The game is still the same, but the play, the components are acting differently. What's your take on this? >> Absolutely. No, absolutely. That's a very key important point, and it's one that we always ask our customers right at the front end, right? Because your starting assumptions matter. If you have workloads of workloads in the cloud and data center is something that you want to connect into, then you'll make decisions kind of keeping cloud in the center and then kind of bolt on technologies for what that means to extend it to the data center. If your center of gravity is in the data center, and then cloud is let's say 10% right now, but you see that growing, then what choices do you have? Right, do you want to bring your data center technologies into the cloud because you want that consistency in operations? Or do you want to start off fresh, right? So this is a really key, important question, and one that many of our customers are actually are grappling with, right? They have this notion that going cloud native is the right approach, but at the same time that means I have a bifurcation in kind of how do I operate my data center versus my cloud, right? Two different operating models, and slowly it'll shift over to one. But you're going to have to deal with dual reality for a while. >> I was talking to an old friend of mine, CIO, very experienced CIO. Big time company, large deployment, a lot of IT. I said, so what's the big trend everyone's telling me about IT's going. He goes no, not really. IT's not going away for me. It's going everywhere in the company. >> Ramesh: Exactly. >> So I need to scale my IT-like capabilities everywhere and then make it invisible. >> Ramesh: Correct. >> Which is essentially code words for saying it's going to be completely cloud native everywhere. This is what is happening. Do you agree? >> Absolutely right, and so if you look at what do enterprises care about it? The reason to go to the cloud is to get speed of operations, and it's apps, apps, apps, right? Do you ever have a conversation on networking and infrastructure first? No, that kind of gets brought into the conversation because you want to deal with users, applications and services, right? And so the end goal is essentially how do users communicate with apps and get the right experience, security and whatnot, and how do apps talk to each other and make sure that you get all of the connectivity and security requirements? Underneath the covers, what does this mean for infrastructure, networking, security and whatnot? It's actually going to be someone else's job, right? And you shouldn't have to think too much about it. So this whole notion of kind of making that transparent is real actually, right? But at the same time, us and all the guys that we talk to on the customer side, that's their job, right? Like we have to work towards making that transparent. Some are going to be in the form of capability, some are going to be driven by data, but that's really where the two worlds are going to come together. >> Lots of debates going on. We just heard from Bob Muglia here on Supercloud2. He said Supercloud's a platform that provides programmatically consistent services hosted on heterogeneous cloud providers. So the question that's being debated is is Supercloud a platform or an architecture in your view? >> Okay, that's a tough one actually. I'm going to side on the side on kind of the platform side right, and the reason for that is architectural choices are things that you make ahead of time. And you, once you're in, there really isn't a fork in the road, right? Platforms continue to evolve. You can iterate, innovate and so on and so forth. And so I'm thinking Supercloud is more of a platform because you do have a choice. Hey, am I going AWS, Azure, GCP. You make that choice. What is my center of gravity? You make that choice. That's kind of an architectural decision, right? Once you make that, then how do I make things work consistently across like two or three clouds? That's a platform choice. >> So who's responsible for the architecture as the platform, the vendor serving the platform or is the platform vendor agnostic? >> You know, this is where you have to kind of peel the onion in layers, right? If you talk about applications, you can't go to a developer team or an app team and say I want you to operate on Google or AWS. They're like I'll pick the cloud that I want, right? Now who are we talking to? The infrastructure guys and the networking guys, right? They want to make sure that it's not bifurcated. It's like, hey, I want to make sure whatever I build for AWS I can equally use that on Azure. I can equally use that on GCP. So if you're talking to more of the application centric teams who really want infrastructure to be transparent, they'll say, okay, I want to make this choice of whether this is AWS, Azure, GCP, and stick to that. And if you come kind of down the layers of the stack into infrastructure, they are thinking a little more holistically, a little more Supercloud, a little more multicloud, and that. >> That's a good point. So that brings up the deployment question. >> Ramesh: Exactly! >> I want to ask you the next question, okay, what is the preferred deployment in your opinion for a Supercloud narrative? Is it single instance, spread it around everywhere? What's the, do you have a single global instance or do you have everything synchronized? >> So I would say first layer of that Supercloud really kind of fix the holes that have been introduced as a result of kind of adopting the hyper scaler technologies, right? So each, the hyper scalers have been really good at innovating and providing really massive scale elastic capabilities, right? But once you start to build capabilities on top of that to help serve the application, there's a few holes start to show up. So first job of Supercloud really is to plug those holes, right? Second is can I get to an operating model, so that I can replicate this not just in a single region, but across multiple regions, same cloud, and then across multiple clouds, right? And so both of those need to be solved for in order to be (cross talking). >> So is that multiple instantiations of the stack or? >> Yeah, so this again depends on kind of the capability, right? So if you take a more solution view, and so I can speak for kind of networking security combined right? There you always take a solution view. You don't ever look at, you know, what does this mean for a single instance in a single region. You take a macro view, and then you then break it down into what does this mean for region, what does it mean for instance, what does this mean for AZs? And so on and so forth. So you kind of have to go top to bottom. >> Okay, welcome you down into the trap now. Okay, synchronizing the data, latency, these are all questions. So what does the network Supercloud look like to you? Because networking is big here. >> Ramesh: Yes, absolutely. >> This is what you guys do. >> Exactly, yeah. So the different set of problems as you go up the stack, right? So if you have hundreds of workloads in a single region, the set of problems you're dealing with there are kind of app native connectivity, how do I go from kind of east/west, all of those fun things, right? Which are usually bound in terms of latency. You don't have those challenges as much, but can you build your entire enterprise application architecture in one region? No, you're going to have to create multiple instances, right? So my data lake is invariably going to be in one place. My business logic is going to be spread across a few places. What does that bring in? I need to go across regions. Am I going to put those two regions right next to each other? No, I'm not going to, right? I'm going to have places in Europe. I'm going to have APAC, and I'm going to have a North American presence, and I need to bring all these things together. So this is where, back to your point, latency really matters, right? Because I need to be able to find out not just best path but also how do I reduce the millisecond, microseconds that my application cares about, which brings in a layer of optimization and then so on and so on and so forth. So this is what we call kind of to borrow the Prosimo language full stack networking, right? Because I'm not just dealing with how do I go from one region to another because that's laws of physics. I can only control so much. But there are a few elements up the application stack in software that you can tweak to actually bring these things closer and closer. >> And on that point, you're seeing security being talked a lot more at the network layer. So how do you secure the Supercloud at the network layer? What's that look like? >> Yeah, we've been grappling with essentially is security kind of foundational, and then is the network on top. And then we had an alternative viewpoint which is kind of network and then security on top. And the answer is actually it's neither, right? It's almost like a meshed up sandwich of sorts. So you need to have networking security work really well together, right? Case in point, I mean we were talking to a customer yesterday. He said, hey, I have my data lake in one region that needs to talk to an analytics service in a completely different region of a different cloud. These two things just need to be able to talk to each other, which means I need to bring elements of networking. I need to bring elements of security, secure access, app segmentation, all of those things. Very simple, I have an analytics service that needs to contact a data lake. That's what he starts with, but then before you know it, it actually brings up a whole stack underneath, so that's. >> VMware calls that cloud chaos. >> Ramesh: Yes, exactly. >> And then that's the halfway point between cloud smart. Cloud first, cloud chaos, cloud smart, and the next thing, you can skip that whole step. But again, again, it's pick your strategy right? Again, this comes back down to your earlier point. I want to ask you from a customer standpoint, you got the hyper scalers doing very, very well. >> Ramesh: Yep, absolutely. >> And I love what their Amazon's doing. I think Microsoft again though they had a little bit of downgrade are catching up fast, and they have their installed base. So you got the land of the installed bases. >> Correct. >> First and greater, better cloud. Install base getting better, almost as good, almost as good is a gift, but close. Now you have them specializing. Silicon, special silicon. So there's gaps for other services. >> Ramesh: Correct. >> And Amazon Web Services, Adam Selipsky's a open book saying, hey, we want our ecosystem to pick up these gaps and build on them. Go ahead, go to town. >> So this is where I think choices are tough, right? Because if you had one choice, you would work with it, and you would work around it, right? Now I have five different choices. Now what do I do? Our viewpoint is there are a bunch of things that say AWS does really, really well. Use that as a foundational layer, right? Like don't reinvent the wheel on those things. Transit gateways, global accelerators and whatnot, they exist for a reason. Billions of dollars have gone into building those things. Use that foundational layer, right? But what you want to build on top of that is actually driven by the application. The requirements of a lambda application that's serverless, it's very different than a packaged application that's responding for transactions, right? Like it's just completely very, very different. And so bring in the right set of capabilities required for those set of applications, and then you go based on that. This is also where I think whether something is a regional construct versus an overall global construct really, really matters, right? Because if you start with the assumption that everything is going to be built regionally, then it's someone else's job to make sure that all of these things are connected. But if you start with kind of the global purview, then the rest of them start to (cross talking). >> What are some of the things that the enterprises might want that are gaps that are going to be filled by the, by startups like you guys and the ecosystem because we're seeing the ecosystem form into two big camps. >> Ramesh: Yep. >> ISVs, which is an old school definition of independent software vendor, aka someone who writes software. >> Ramesh: Exactly. >> SaaS app. >> Ramesh: Correct. >> And then ecosystem software players that were once ISVs now have people building on top of them. >> Ramesh: Correct. >> They're building on top of the cloud. So you have that new hyper scale effect going on. >> Ramesh: Exactly. >> You got ISVs, which is software developers, software vendors. >> Ramesh: Correct. >> And ecosystems. >> Yep. >> What's that impact of that? Cause it's a new dynamic. >> Exactly, so if you take kind of enterprises, want to make sure that that their apps and the data center migrate to the cloud, new apps are developed the right way in the cloud, right? So that's kind of table stakes. So now what choices do they have? They listen to AWS and say, okay, I have all these cloud native services. I want to be able to instantiate all that. Now comes the interesting choice that they have to make. Do I go hire a whole bunch of people and do it myself or do I go there on the platform route, right? Because I made an architectural choice. Now I have to decide whether I want to do this myself or the platform choice. DIY works great for some, but you don't know what you're getting into, and it's people involved, right? People, process, all those fun things involved, right? So we show up there and say, you don't know what you don't know, right? Like because that's the nature of it. Why don't you invest in a platform like what what we provide, and then you actually build on top of it. We will, it's our job to make sure that we keep up with the innovation happening underneath the covers. And at the same time, this is not a closed ended system. You can actually build on top of our platform, right? And so that actually gives you a good mix. Now the care abouts are interesting. Some apps care about experience. Some apps care about latency. Some apps are extremely charty and extremely data intensive, but nobody wants to pay for it, right? And so it's a interesting Jenga that you have to play between experience versus security versus cost, right? And that makes kind of head of infrastructure and cloud platform teams' life really, really, really interesting. >> And this is why I love your background, and Stu Miniman, when he was with theCUBE, and now he's at Red Hat, we used to riff about the network and how network folks are now, those concepts are now up the top of the stack because the cloud is one big network effect. >> Ramesh: Exactly, correct. >> It's a computer. >> Yep, absolutely. No, and case in point, right, like say we're in let's say in San Jose here or or Palo Alto here, and let's say my application is sitting in London, right? The cloud gives you different express lanes. I can go down to my closest pop location provided by AWS and then I can go ride that all the way up to up to London. It's going to give me better performance, low latency, but I'm going to have to incur some costs associated with it. Or I can go all the wild internet all the way from Palo Alta up to kind of the ingress point into London and then go access, but I'm spending time on the wild internet, which means all kinds of fun things happen, right? But I'm not paying much, but my experience is not going to be so great. So, and there are various degrees of shade in them, of gray in the middle, right? So how do you pick what? It all kind of is driven by the applications. >> Well, we certainly want you back for Supercloud3, our next version of this virtual/live event here in our Palo Alto studios. Really appreciate you coming on. >> Absolutely. >> While you're here, give a quick plug for the company. Next minute, we can take a minute to talk about the success of the company. >> Ramesh: Absolutely. >> I know you got a fresh financing this past year. Plenty of money in the bank, going to ride this new wave, Supercloud wave. Give us a quick plug. >> Absolutely, yeah. So three years going on to four this calendar year. So it's an interesting time for the company. We have proven that our technology, product and our initial customers are quite happy with it. Now comes essentially more of those and scale and so forth. That's kind of the interesting phase that we are in. Also heartened to see quite a few of kind of really large and dominant players in the market, partners, channels and so forth, invest in us to take this to the next set of customers. I would say there's been a dramatic shift in the conversation with our customers. The first couple of years or so of the company, we are about three years old right now, was really about us educating them. This is what you need. This is what you need. Now actually it's a lot of just pull, right? We've seen a good indication, as much as a hate RFIs, a good indication is the number of RFIs that show up at our door saying we want you to participate in this because we want to understand more, right? And so as a, I think we are at an interesting point of the, of that shift. >> RFIs always like do all this work and hope for the best. Pray for a deal. You know, you guys on the right side of history. If a customer asks with respect to Supercloud, multicloud, is that your focus? Is that the direction you guys are going into? >> Yeah, so I would say we are kind of both, right? Supercloud and multicloud because we, our customers are hybrid, multiple clouds, all of the above, right? Our main pitch and kind of value back to the customers is go embrace cloud native because that's the right approach, right? It doesn't make sense to go reinvent the wheel on that one, but then make a really good choice about whether you want to do this yourself or invest in a platform to make your life easy. Because we have seen this story play out with many many enterprises, right? They pick the right technologies. They do a simple POC overnight, and they say, yeah, I can make this work for two apps, right? And then they say, yes, I can make this work for 100. You go down a certain path. You hit a wall. You hit a wall, and it's a hard wall. It's like, no, there isn't a thing that you can go around it. >> A lot of dead bodies laying around. >> Ramesh: Exactly. >> Dead wall. >> And then they have to unravel around that, and then they come talk to us, and they say, okay, now what? Like help me, help me through this journey. So I would say to the extent that you can do this diligence ahead of time, do that, and then, and then pick the right platform. >> You've got to have the talent. And you got to be geared up. You got to know what you're getting into. >> Ramesh: Exactly. >> You got to have the staff to do this. >> And cloud talent and skillset in particular, I mean there's lots available but it's in pockets right? And if you look at kind of web three companies, they've gone and kind of amassed all those guys, right? So enterprises are not left with the cream of the crop. >> John: They might be coming back. >> Exactly, exactly, so. >> With this downturn. Ramesh, great to see you and thanks for contributing to Supercloud2, and again, love your team. Very technical team, and you're in the right side of history in this one. Congratulations. >> Ramesh: No, and thank you, thank you very much. >> Okay, this is Supercloud2. I'm John Furrier with Dave Vellante. We'll be back right after this short break. (upbeat music)

(upbeat music) >> Okay, welcome back everyone at Supercloud 2 event, live here in Palo Alto, theCUBE Studios live stage performance, virtually syndicating it all over the world. I'm John Furrier with Dave Vellante here as Cube alumni, and special influencer guest, Howie Xu, VP of Machine Learning and Zscaler, also part-time as a CUBE analyst 'cause he is that good. Comes on all the time. You're basically a CUBE analyst as well. Thanks for coming on. >> Thanks for inviting me. >> John: Technically, you're not really a CUBE analyst, but you're kind of like a CUBE analyst. >> Happy New Year to everyone. >> Dave: Great to see you. >> Great to see you, Dave and John. >> John: We've been talking about ChatGPT online. You wrote a great post about it being more like Amazon, not like Google. >> Howie: More than just Google Search. >> More than Google Search. Oh, it's going to compete with Google Search, which it kind of does a little bit, but more its infrastructure. So a clever point, good segue into this conversation, because this is kind of the beginning of these kinds of next gen things we're going to see. Things where it's like an obvious next gen, it's getting real. Kind of like seeing the browser for the first time, Mosaic browser. Whoa, this internet thing's real. I think this is that moment and Supercloud like enablement is coming. So this has been a big part of the Supercloud kind of theme. >> Yeah, you talk about Supercloud, you talk about, you know, AI, ChatGPT. I really think the ChatGPT is really another Netscape moment, the browser moment. Because if you think about internet technology, right? It was brewing for 20 years before early 90s. Not until you had a, you know, browser, people realize, "Wow, this is how wonderful this technology could do." Right? You know, all the wonderful things. Then you have Yahoo and Amazon. I think we have brewing, you know, the AI technology for, you know, quite some time. Even then, you know, neural networks, deep learning. But not until ChatGPT came along, people realize, "Wow, you know, the user interface, user experience could be that great," right? So I really think, you know, if you look at the last 30 years, there is a browser moment, there is iPhone moment. I think ChatGPT moment is as big as those. >> Dave: What do you see as the intersection of things like ChatGPT and the Supercloud? Of course, the media's going to focus, journalists are going to focus on all the negatives and the privacy. Okay. You know we're going to get by that, right? Always do. Where do you see the Supercloud and sort of the distributed data fitting in with ChatGPT? Does it use that as a data source? What's the link? >> Howie: I think there are number of use cases. One of the use cases, we talked about why we even have Supercloud because of the complexity, because of the, you know, heterogeneous nature of different clouds. In order for me as a developer, in order for me to create applications, I have so many things to worry about, right? It's a complexity. But with ChatGPT, with the AI, I don't have to worry about it, right? Those kind of details will be taken care of by, you know, the underlying layer. So we have been talking about on this show, you know, over the last, what, year or so about the Supercloud, hey, defining that, you know, API layer spanning across, you know, multiple clouds. I think that will be happening. However, for a lot of the things, that will be more hidden, right? A lot of that will be automated by the bots. You know, we were just talking about it right before the show. One of the profound statement I heard from Adrian Cockcroft about 10 years ago was, "Hey Howie, you know, at Netflix, right? You know, IT is just one API call away." That's a profound statement I heard about a decade ago. I think next decade, right? You know, the IT is just one English language away, right? So when it's one English language away, it's no longer as important, API this, API that. You still need API just like hardware, right? You still need all of those things. That's going to be more hidden. The high level thing will be more, you know, English language or the language, right? Any language for that matter. >> Dave: And so through language, you'll tap services that live across the Supercloud, is what you're saying? >> Howie: You just tell what you want, what you desire, right? You know, the bots will help you to figure out where the complexity is, right? You know, like you said, a lot of criticism about, "Hey, ChatGPT doesn't do this, doesn't do that." But if you think about how to break things down, right? For instance, right, you know, ChatGPT doesn't have Microsoft stock price today, obviously, right? However, you can ask ChatGPT to write a program for you, retrieve the Microsoft stock price, (laughs) and then just run it, right? >> Dave: Yeah. >> So the thing to think about- >> John: It's only going to get better. It's only going to get better. >> The thing people kind of unfairly criticize ChatGPT is it doesn't do this. But can you not break down humans' task into smaller things and get complex things to be done by the ChatGPT? I think we are there already, you know- >> John: That to me is the real game changer. That's the assembly of atomic elements at the top of the stack, whether the interface is voice or some programmatic gesture based thing, you know, wave your hand or- >> Howie: One of the analogy I used in my blog was, you know, each person, each professional now is a quarterback. And we suddenly have, you know, a lot more linebacks or you know, any backs to work for you, right? For free even, right? You know, and then that's sort of, you should think about it. You are the quarterback of your day-to-day job, right? Your job is not to do everything manually yourself. >> Dave: You call the play- >> Yes. >> Dave: And they execute. Do your job. >> Yes, exactly. >> Yeah, all the players are there. All the elves are in the North Pole making the toys, Dave, as we say. But this is the thing, I want to get your point. This change is going to require a new kind of infrastructure software relationship, a new kind of operating runtime, a new kind of assembler, a new kind of loader link things. This very operating systems kind of concepts. >> Data intensive, right? How to process the data, how to, you know, process so gigantic data in parallel, right? That's actually a tough job, right? So if you think about ChatGPT, why OpenAI is ahead of the game, right? You know, Google may not want to acknowledge it, right? It's not necessarily they do, you know, not have enough data scientist, but the software engineering pieces, you know, behind it, right? To train the model, to actually do all those things in parallel, to do all those things in a cost effective way. So I think, you know, a lot of those still- >> Let me ask you a question. Let me ask you a question because we've had this conversation privately, but I want to do it while we're on stage here. Where are all the alpha geeks and developers and creators and entrepreneurs going to gravitate to? You know, in every wave, you see it in crypto, all the alphas went into crypto. Now I think with ChatGPT, you're going to start to see, like, "Wow, it's that moment." A lot of people are going to, you know, scrum and do startups. CTOs will invent stuff. There's a lot of invention, a lot of computer science and customer requirements to figure out. That's new. Where are the alpha entrepreneurs going to go to? What do you think they're going to gravitate to? If you could point to the next layer to enable this super environment, super app environment, Supercloud. 'Cause there's a lot to do to enable what you just said. >> Howie: Right. You know, if you think about using internet as the analogy, right? You know, in the early 90s, internet came along, browser came along. You had two kind of companies, right? One is Amazon, the other one is walmart.com. And then there were company, like maybe GE or whatnot, right? Really didn't take advantage of internet that much. I think, you know, for entrepreneurs, suddenly created the Yahoo, Amazon of the ChatGPT native era. That's what we should be all excited about. But for most of the Fortune 500 companies, your job is to surviving sort of the big revolution. So you at least need to do your walmart.com sooner than later, right? (laughs) So not be like GE, right? You know, hand waving, hey, I do a lot of the internet, but you know, when you look back last 20, 30 years, what did they do much with leveraging the- >> So you think they're going to jump in, they're going to build service companies or SaaS tech companies or Supercloud companies? >> Howie: Okay, so there are two type of opportunities from that perspective. One is, you know, the OpenAI ish kind of the companies, I think the OpenAI, the game is still open, right? You know, it's really Close AI today. (laughs) >> John: There's room for competition, you mean? >> There's room for competition, right. You know, you can still spend you know, 50, $100 million to build something interesting. You know, there are company like Cohere and so on and so on. There are a bunch of companies, I think there is that. And then there are companies who's going to leverage those sort of the new AI primitives. I think, you know, we have been talking about AI forever, but finally, finally, it's no longer just good, but also super useful. I think, you know, the time is now. >> John: And if you have the cloud behind you, what do you make the Amazon do differently? 'Cause Amazon Web Services is only going to grow with this. It's not going to get smaller. There's more horsepower to handle, there's more needs. >> Howie: Well, Microsoft already showed what's the future, right? You know, you know, yes, there is a kind of the container, you know, the serverless that will continue to grow. But the future is really not about- >> John: Microsoft's shown the future? >> Well, showing that, you know, working with OpenAI, right? >> Oh okay. >> They already said that, you know, we are going to have ChatGPT service. >> $10 billion, I think they're putting it. >> $10 billion putting, and also open up the Open API services, right? You know, I actually made a prediction that Microsoft future hinges on OpenAI. I think, you know- >> John: They believe that $10 billion bet. >> Dave: Yeah. $10 billion bet. So I want to ask you a question. It's somewhat academic, but it's relevant. For a number of years, it looked like having first mover advantage wasn't an advantage. PCs, spreadsheets, the browser, right? Social media, Friendster, right? Mobile. Apple wasn't first to mobile. But that's somewhat changed. The cloud, AWS was first. You could debate whether or not, but AWS okay, they have first mover advantage. Crypto, Bitcoin, first mover advantage. Do you think OpenAI will have first mover advantage? >> It certainly has its advantage today. I think it's year two. I mean, I think the game is still out there, right? You know, we're still in the first inning, early inning of the game. So I don't think that the game is over for the rest of the players, whether the big players or the OpenAI kind of the, sort of competitors. So one of the VCs actually asked me the other day, right? "Hey, how much money do I need to spend, invest, to get, you know, another shot to the OpenAI sort of the level?" You know, I did a- (laughs) >> Line up. >> That's classic VC. "How much does it cost me to replicate?" >> I'm pretty sure he asked the question to a bunch of guys, right? >> Good luck with that. (laughs) >> So we kind of did some napkin- >> What'd you come up with? (laughs) >> $100 million is the order of magnitude that I came up with, right? You know, not a billion, not 10 million, right? So 100 million. >> John: Hundreds of millions. >> Yeah, yeah, yeah. 100 million order of magnitude is what I came up with. You know, we can get into details, you know, in other sort of the time, but- >> Dave: That's actually not that much if you think about it. >> Howie: Exactly. So when he heard me articulating why is that, you know, he's thinking, right? You know, he actually, you know, asked me, "Hey, you know, there's this company. Do you happen to know this company? Can I reach out?" You know, those things. So I truly believe it's not a billion or 10 billion issue, it's more like 100. >> John: And also, your other point about referencing the internet revolution as a good comparable. The other thing there is online user population was a big driver of the growth of that. So what's the equivalent here for online user population for AI? Is it more apps, more users? I mean, we're still early on, it's first inning. >> Yeah. We're kind of the, you know- >> What's the key metric for success of this sector? Do you have a read on that? >> I think the, you know, the number of users is a good metrics, but I think it's going to be a lot of people are going to use AI services without even knowing they're using it, right? You know, I think a lot of the applications are being already built on top of OpenAI, and then they are kind of, you know, help people to do marketing, legal documents, you know, so they're already inherently OpenAI kind of the users already. So I think yeah. >> Well, Howie, we've got to wrap, but I really appreciate you coming on. I want to give you a last minute to wrap up here. In your experience, and you've seen many waves of innovation. You've even had your hands in a lot of the big waves past three inflection points. And obviously, machine learning you're doing now, you're deep end. Why is this Supercloud movement, this wave of Supercloud and the discussion of this next inflection point, why is it so important? For the folks watching, why should they be paying attention to this particular moment in time? Could you share your super clip on Supercloud? >> Howie: Right. So this is simple from my point of view. So why do you even have cloud to begin with, right? IT is too complex, too complex to operate or too expensive. So there's a newer model. There is a better model, right? Let someone else operate it, there is elasticity out of it, right? That's great. Until you have multiple vendors, right? Many vendors even, you know, we're talking about kind of how to make multiple vendors look like the same, but frankly speaking, even one vendor has, you know, thousand services. Now it's kind of getting, what Kid was talking about what, cloud chaos, right? It's the evolution. You know, the history repeats itself, right? You know, you have, you know, next great things and then too many great things, and then people need to sort of abstract this out. So it's almost that you must do this. But I think how to abstract this out is something that at this time, AI is going to help a lot, right? You know, like I mentioned, right? A lot of the abstraction, you don't have to think about API anymore. I bet 10 years from now, you know, IT is one language away, not API away. So think about that world, right? So Supercloud in, in my opinion, sure, you kind of abstract things out. You have, you know, consistent layers. But who's going to do that? Is that like we all agreed upon the model, agreed upon those APIs? Not necessary. There are certain, you know, truth in that, but there are other truths, let bots take care of, right? Whether you know, I want some X happens, whether it's going to be done by Azure, by AWS, by GCP, bots will figure out at a given time with certain contacts with your security requirement, posture requirement. I'll think that out. >> John: That's awesome. And you know, Dave, you and I have been talking about this. We think scale is the new ratification. If you have first mover advantage, I'll see the benefit, but scale is a huge thing. OpenAI, AWS. >> Howie: Yeah. Every day, we are using OpenAI. Today, we are labeling data for them. So you know, that's a little bit of the- (laughs) >> John: Yeah. >> First mover advantage that other people don't have, right? So it's kind of scary. So I'm very sure that Google is a little bit- (laughs) >> When we do our super AI event, you're definitely going to be keynoting. (laughs) >> Howie: I think, you know, we're talking about Supercloud, you know, before long, we are going to talk about super intelligent cloud. (laughs) >> I'm super excited, Howie, about this. Thanks for coming on. Great to see you, Howie Xu. Always a great analyst for us contributing to the community. VP of Machine Learning and Zscaler, industry legend and friend of theCUBE. Thanks for coming on and sharing really, really great advice and insight into what this next wave means. This Supercloud is the next wave. "If you're not on it, you're driftwood," says Pat Gelsinger. So you're going to see a lot more discussion. We'll be back more here live in Palo Alto after this short break. >> Thank you. (upbeat music)

(lively music) >> Hello, everyone. Welcome back to the Supercloud presentation here. I'm theCUBE, I'm John Furrier, your host. What a great segment here. We're going to unpack the networking aspect of the cloud, how that translates into what Supercloud architecture and platform deployment scenarios look like. And demystify multi-cloud, hybridcloud. We've got two great experts. Amir Khan, the Co-Founder and CEO of Alkira, Atif Khan, Co-Founder and CTO of Alkira. These guys been around since 2018 with the startup, but before that story, history in the tech industry. I mean, routing early days, multiple waves, multiple cycles. >> Welcome three decades. >> Welcome to Supercloud. >> Thanks. >> Thanks for coming on. >> Thank you so much for having us. >> So, let's get your take on Supercloud because it's been one of those conversations that really galvanized the industry because it kind of highlights almost this next wave, this next side of the street that everyone's going to be on that's going to be successful. The laggards on the legacy seem to be stuck on the old model. SaaS is growing up, it's ISVs, it's ecosystems, hyperscale, full hybrid. And then multi-cloud around the corners cause all this confusion, everyone's hand waving. You know, this is a solution, that solution, where are we? What do you guys see as this supercloud dynamic? >> So where we start from is always focusing on the customer problem. And in 2018 when we identified the problem, we saw that there were multiple clouds with many diverse ways of doing things from the network perspective, and customers were struggling with that. So we delved deeper into that and looked at each one of the cloud architectures completely independent. And there was no common solution and customers were struggling with that from the perspective. They wanted to be in multiple clouds, either through mergers and acquisitions or running an application which may be more cost effective to run in something or maybe optimized for certain reasons to run in a different cloud. But from the networking perspective, everything needed to come together. So that's, we are starting to define it as a supercloud now, but basically, it's a common infrastructure across all clouds. And then integration of high lift services like, you know, security or IPAM services or many other types of services like inter-partner routing and stuff like that. So, Amir, you agree then that multi-cloud is simply a default result of having whatever outcomes, either M&A, some productivity software, maybe Azure. >> Yes. >> Amazon has this and then I've got on-premise application, so it's kinds mishmash. >> So, I would qualify it with hybrid multi-cloud because everything is going to be interconnected. >> John: Got it. >> Whether it's on-premise, remote users or clouds. >> But have CTO perspective, obviously, you got developers, multiple stacks, got AWS, Azure and GCP, other. Not everyone wants to kind of like go all in, but yet they don't want to hedge too much because it's a resource issue. And I got to learn this stack, I got to learn that stack. So then now, you have this default multi-cloud, hybrid multi-cloud, then it's like, okay, what do I do? How do you spread that around? Is it dangerous? What's the the approach technically? What's some of the challenges there? >> Yeah, certainly. John, first, thanks for having us here. So, before I get to that, I'll just add a little bit to what Amir was saying, like how we started, what we were seeing and how it, you know, correlates with the supercloud. So, as you know, before this company, Alkira, we were doing, we did the SD-WAN company, which was Viptela. So there, we started seeing when people started deploying SD-WAN at like a larger scale. We started like, you know, customers coming to us and saying they needed connectivity into the cloud from the SD-WAN. They wanted to extend the SD-WAN fabric to the cloud. So we came up with an architecture, which was like later we started calling them Cloud onRamps, where we built, you know, a transit VPC and put like the virtual instances of SD-WAN appliances extended from there to the cloud. But before we knew, like it started becoming very complicated for the customers because it wasn't just connectivity, it also required, you know, other use cases. You had to instantiate or bring in security appliances in there. You had to secure all of that stuff. There were requirements for, you know, different regions. So you had to bring up the same thing in different regions. Then multiple clouds, what did you do? You had to replicate the same thing in multiple clouds. And now if there was was requirement between clouds, how were you going to do it? You had to route traffic from somewhere, and come up with all those routing controls and stuff. So, it was very complicated. >> Like spaghetti code, but on network. >> The games begin, in fact, one of our customers called it spaghetti mess. And so, that's where like we thought about where was the industry going and which direction the industry was going into? And we came up with the Alkira where what we are doing is building a common infrastructure across multiple clouds, across in, you know, on-prem locations, be it data centers or physical sites, branches sites, et cetera, with integrated security and network networking services inside. And, you know, nowadays, networking is not only about connectivity, you have to secure everything. So, security has to be built in. Redundancy, high availability, disaster recovery. So all of that needs to be built in. So that's like, you know, kind of a definition of like what we thought at that time, what is turning into supercloud now. >> Yeah. It's interesting too, you mentioned, you know, VPCs is not, configuration of loans a hassle. Nevermind the manual mistakes could be made, but as you decide to do something you got to, "Oh, we got to get these other things." A lot of the hyper scales and a lot of the alpha cloud players now, and cloud native folks, they're kind of in that mode of, "Wow, look at what we've built." Now, they're got to maintain, how do I refresh it? Like, how do I keep the talent? So they got this similar chaotic environment where it's like, okay, now they're already already through, so I think they're going to be okay. But then some people want to bypass it completely. So there's a lot of customers that we see out there that fit the makeup of, I'm cloud first, I've lifted and shifted, I move some stuff to the cloud. But I want to bypass all that learnings from all the people that are gone through the past three years. Can I just skip that and go to a multi-cloud or coherent infrastructure? What do you think about that? What's your view? >> So yeah, so if you look at these enterprises, you know, many of them just to find like the talent, which for one cloud as far as the IT staff is concerned, it's hard enough. And now, when you have multiple clouds, it's hard to find people the talent which is, you know, which has expertise across different clouds. So that's where we come into the picture. So our vision was always to simplify all of this stuff. And simplification, it cannot be just simplification because you cannot just automate the workflows of the cloud providers underneath. So you have to, you know, provide your full data plane on top of it, fed full control plane, management plane, policy and management on top of it. And coming back to like your question, so these nowadays, those people who are working on networking, you know, before it used to be like CLI. You used to learn about Cisco CLI or Juniper CLI, and you used to work on it. Nowadays, it's very different. So automation, programmability, all of that stuff is the key. So now, you know, Ops guys, the DevOps guys, so these are the people who are in high demand. >> So what do you think about the folks out there that are saying, okay, you got a lot of fragmentation. I got the stacks, I got a lot of stove pipes, if you will, out there on the stack. I got to learn this from Azure. Can you guys have with your product abstract the way that's so developers don't need to know the ins and outs of stack's, almost like a gateway, if you will, the old days. But like I'm a developer or team develop, why should I have to learn the management layer of Azure? >> That's exactly what we started, you know, out with to solve. So it's, what we have built is a platform and the platform sits inside the cloud. And customers are able to build their own network or a virtual network on top using that platform. So the platform has its own data plane, own control plane and management plane with a policy layer on top of it. So now, it's the platform which is sitting in different clouds, but from a customer's point of view, it's one way of doing networking. One way of instantiating or bringing in services or security services in the middle. Whether those are our security services or whether those are like services from our partners, like Palo Alto or Checkpoint or Cisco. >> So you guys brought the SD-WAN mojo and refactored it for the cloud it sounds like. >> No. >> No? (chuckles) >> We cannot said. >> All right, explain. >> It's way more than that. >> I mean, SD-WAN was wan. I mean, you're talking about wide area networks, talking about connected, so explain the difference. >> SD-WAN was primarily done for one major reason. MPLS was expensive, very strong SLAs, but very low speed. Internet, on the other hand, you sat at home and you could access your applications much faster. No SLA, very low cost, right? So we wanted to marry the two together so you could have a purely private infrastructure and a public infrastructure and secure both of them by creating a common secure fabric across all those environments. And then seamlessly tying it into your internal branch and data center and cloud network. So, it merely brought you to the edge of the cloud. It didn't do anything inside the cloud. Now, the major problem resides inside the clouds where you have to optimize the clouds themselves. Take a step back. How were the clouds built? Basically, the cloud providers went to the Ciscos and Junipers and the rest of the world, built the network in the data centers or across wide area infrastructure, and brought it all together and tried to create a virtualized layer on top of that. But there were many limitations of this underlying infrastructure that they had built. So number of routes per region, how inter region connectivity worked, or how many routes you could carry to the VPCs of V nets? That all those were becoming no common policy across, you know, these environments, no segmentation across these environments, right? So the networking constructs that the enterprise customers were used to as enterprise class carry class capabilities, they did not exist in the cloud. So what did the customer do? They ended up stitching it together all manually. And that's why Atif was alluding to earlier that it became a spaghetti mess for the customers. And then what happens is, as a result, day two operations, you know, troubleshooting, everything becomes a nightmare. So what do you do? You have to build an infrastructure inside the cloud. Cloud has enough raw capabilities to build the solutions inside there. Netflix's of the world. And many different companies have been born in the cloud and evolved from there. So why could we not take the raw capabilities of the clouds and build a network cloud or a supercloud on top of these clouds to optimize the whole infrastructure and seamlessly connecting it into the on-premise and remote user locations, right? So that's your, you know, hybrid multi-cloud solution. >> Well, great call out on the SD-WAN in common versus cloud. 'Cause I think this is important because you're building a network layer in the cloud that spans out so the customers don't have to get into the, there's a gap in the system that I'm used to, my operating environment, of having lockdown security and network. >> So yeah. So what you do is you use the raw capabilities like bandwidth or virtual machines, or you know, containers, or, you know, different types of serverless capabilities. And you bring it all together in a way to solve the networking problems, thereby creating a supercloud, which is an abstraction layer which hides all the complexity of the underlying clouds from the customer, right? And it provides a common infrastructure across all environments to that customer, right? That's the beauty of it. And it does it in a way that it looks like, if they have the networking knowledge, they can apply it to this new environment and carry it forward. One way of doing security across all clouds and hybrid environments. One way of doing routing. One way of doing large-scale network address translation. One way of doing IPAM services. So people are tired of doing individual things and individual clouds and on-premise locations, right? So now they're getting something common. >> You guys brought that, you brought all that to bear and flexible for the customer to essentially self-serve their network cloud. >> Yes, yeah. Is that the wave? >> And nowadays, from business perspective, agility is the key, right? You have to move at the pace of the business. If you don't, you are losing. >> So, would it be safe to say that you guys have a network supercloud? >> Absolutely, yeah. >> We, pretty much, yeah. Absolutely. >> What does that mean to our customer? What's in it for them? What's the benefit to the customer? I got a network supercloud, it connects, provides SLA, all the capabilities I need. What do they get? What's the end point for them? What's the end? >> Atif, maybe you can talk some examples. >> The IT infrastructure is all like distributed now, right? So you have applications running in data centers. You have applications running in one cloud. Other cloud, public clouds, enterprises are depending on so many SaaS applications. So now, these are, you can call these endpoints. So a supercloud or a network cloud, from our perspective, it's a cloud in the middle or a network in the middle, which provides connectivity from any endpoint to any endpoint. So, you are able to connect to the supercloud or network cloud in one way no matter where you are. So now, whichever cloud you are in, whichever cloud you need to connect to. And also, it's not just connecting to the cloud. So you need to do a lot of stuff, a lot of networking inside the cloud also. So now, as Amir was saying, every cloud has its own from a networking, you know, the concept perspective or the construct, they are different. There are limitations in there also. So this supercloud, which is sitting on top, basically, your platform is sitting into the cloud, but the supercloud is built on top of using your platform. So that abstracts all those complexities, all those limitations. So now your limitations are whatever the limitations of that platform are. So now your platform, that platform is in our control. So we can keep building it, we can keep scaling it horizontally. Because one of the things is that, you know, in this cloud era, one of the things is autoscaling these services. So why can't the network now autoscale also, just like your other services. >> Network autoscaling is a genius idea, and I think that's a killer. I want to ask the the follow on question because I think, first of all, I love what you guys are doing. So, I think it's a great example of this new innovation. It's not obvious until you see it, right? Geographical is huge. So, you know, single instance, global instances, multiple instances, you're seeing global. How do you guys look at that global equation? Because as companies expand their clouds into geos, and then ultimately, you know, it's obviously continent, region and locales. You're going to have geographic issues. So, this is an extension of your network cloud? >> Amir: It is the extension of the network cloud because if you look at this hyperscalers, they're sitting pretty much everywhere in the globe. So, wherever their regions are, the beauty of building a supercloud is that you can by definition, be available in those regions. It literally takes a day or two of testing for our stack to run in those regions, to make sure there are no nuances that we run into, you know, for that region. The moment we bring it up in that region, all customers can onboard into that solution. So literally, what used to take months or years to build a global infrastructure, now, you can configure it in 10 minutes basically, and bring it up in less than one hour. Since when did we see any solution- >> And by the way, >> that can come up with. >> when the edge comes out too, you're going to start to see more clouds get bolted on. >> Exactly. And you can expand to the edge of the network. That's why we call cloud the new edge, right? >> John: Yeah, it is. Now, I think you guys got a good solutions, network clouds, superclouds, good. So the question on the premise side, so I get the cloud play. It's very cool. You can expand out. It's a nice layer. I'm sure you manage the SLAs between latency and all kinds of things. Knowing when not to do things. Physics or physics. Okay. Now, you've got the on-premise. What's the on-premise equation look like? >> So on-premise, the kind of customers, we are working with large enterprises, mid-size enterprises. So they have on-prem networks, they have deployed, in many cases, they have deployed SD-WAN. In many cases, they have MPLS. They have data centers also. And a lot of these companies are, you know, moving the applications from the data center into the cloud. But we still have large enterprise- >> But for you guys, you can sit there too with non server or is it a box or what is it? >> It's a software stack, right? So, we are a software company. >> Okay, so no box. >> No box. >> Okay, got it. >> No box. >> It's even better. So, we can connect any, as I mentioned, any endpoint, whether it's data centers. So, what happens is usually these enterprises from the data centers- >> John: It's a cloud endpoint for you. >> Cloud endpoint for us. And they need highspeed connectivity into the cloud. And our network cloud is sitting inside the or supercloud is sitting inside the cloud. So we need highspeed connectivity from the data centers. This is like multi-gig type of connectivity. So we enable that connectivity as a service. And as Amir was saying, you are able to bring it up in minutes, pretty much. >> John: Well, you guys have a great handle on supercloud. I really appreciate you guys coming on. I have to ask you guys, since you have so much experience in the industry, multiple inflection points you've guys lived through and we're all old, and we can remember those glory days. What's the big deal going on right now? Because you can connect the dots and you can imagine, okay, like a Lambda function spinning up some connectivity. I need instant access to a new route, throw some, I need to send compute to an edge point for process data. A lot of these kind of ad hoc services are going to start flying around, which used to be manually configured as you guys remember. >> Amir: And that's been the problem, right? The shadow IT, that was the biggest problem in the enterprise environment. So that's what we are trying to get the customers away from. Cloud teams came in, individuals or small groups of people spun up instances in the cloud. It was completely disconnected from the on-premise environment or the existing IT environment that the customer had. So, how do you bring it together? And that's what we are trying to solve for, right? At a large scale, in a carrier cloud center (indistinct). >> What do you call that? Shift right or shift left? Shift left is in the cloud native world security. >> Amir: Yes. >> Networking and security, the two hottest areas. What are you shifting? Up or down? I mean, the network's moving up the stack. I mean, you're seeing the run times at Kubernetes later' >> Amir: Right, right. It's true we're end-to-end virtualization. So you have plumbing, which is the physical infrastructure. Then on top of that, now for the first time, you have true end-to-end virtualization, which the cloud-like constructs are providing to us. We tried to virtualize the routers, we try to virtualize instances at the server level. Now, we are bringing it all together in a truly end-to-end virtualized manner to connect any endpoint anywhere across the globe. Whether it's on-premise, home, multiple clouds, or SaaS type environments. >> Yeah. If you talk about the technical benefits beyond virtualizations, you kind of see in virtualization be abstracted away. So you got end-to-end virtualization, but you don't need to know virtualization to take advantage of it. >> Exactly. Exactly. >> What are some of the tech involved where, what's the trend around on top of virtual? What's the easy button for that? >> So there are many, many use cases from the customers and they're, you know, some of those use cases, they used to deliver out of their data centers before. So now, because you, know, it takes a long time to spend something up in the data center and stuff. So the trend is and what enterprises are looking for is agility. And to achieve that agility, they are moving those services or those use cases into the cloud. So another technical benefit of like something like a supercloud and what we are doing is we allow customers to, you know, move their services from existing data centers into the cloud as well. And I'll give you some examples. You know, these enterprises have, you know, tons of partners. They provide connectivity to their partners, to select resources. It used to happen inside the data center. You would bring in connectivity into the data center and apply like tons of ACLs and whatnot to make sure that you are able to only connect. And now those use cases are, they need to be enabled inside the cloud. And the customer's customers are also, it's not just coming from the on-prem, they're coming from the cloud as well. So, if they're coming from the cloud as well as from on-prem, so you need like an infrastructure like supercloud, which is sitting inside the cloud and is able to handle all these use cases. So all of these use cases have to be, so that requires like moving those services from the data center into the cloud or into the supercloud. So, they're, oh, as we started building this service over the last four years, we have come across so many use cases. And to deliver those use cases, you have to have a platform. So you have to have your own platform because otherwise you are depending on somebody else's, you know, capabilities. And every time their capabilities change, you have to change. >> John: I'm glad you brought up the platform 'cause I want to get your both reaction to this. So Bob Muglia just said on theCUBE here at Supercloud, that supercloud is a platform that provides programmatically consistent services hosted on heterogeneous cloud providers. So the question is, is supercloud a platform or an architecture in your view? >> That's an interesting view on things, you know? I mean, if you think of it, you have to design or architect a solution before we turn it into a platform. >> John: It's a trick question actually. >> So it's a, you know, so we look at it as that you have to have an architectural approach end to end, right? And then you build a solution based on that approach. So, I don't think that they are mutually exclusive. I think they go hand in hand. It's an architecture that you turn into a solution and provide that agility and high availability and disaster recovery capability that it built into that. >> It's interesting that these definitions might be actually redefined with this new configuration. >> Amir: Yes. >> Because architecture and platform used to mean something, like, aight here's a platform, you buy this platform. >> And then you architecture solution. >> Architect it via vendor. >> Right, right, right. >> Okay. And they have to deal with that architecture in the place of multiple superclouds. If you have too many stove pipes, then what's the purpose of supercloud? >> Right, right, right. And because, you know, historically, you built a router and you sold it to the customer. And the poor customer was supposed to install it all, you know, and interconnect all those things. And if you have 40, 50,000 router network, which we saw in our lifetime, 'cause there used to be many more branches when we were growing up in the networking industry, right? You had to create hierarchy and all kinds of things to figure out how to solve that problem. We are no longer living in that world anymore. You cannot deploy individual virtual instances. And that's what approach a lot of people are taking, which is a pure overly network. You cannot take that approach anymore. You have to evolve the architecture and then build the solution based on that architecture so that it becomes a platform which is readily available, highly scalable, and available. And at the same time, it's very, very easy to deploy. It's a SaaS type solution, right? >> So you're saying, do the architecture to get the solution for the platform that the customer has. >> Amir: Yes. >> They're not buying a platform, they end up with a platform- >> With the platform. >> as a result of Supercloud path. All right. So that's what's, so you mentioned, that's a great point. I want to double click on what you just said. 'Cause I like that what you said. What's the deployment strategy in your mind for supercloud? I'm an architect. I'm at an enterprise in the Midwest. I'm an insurance company, got some cloud action going on. I'm mostly on-premise. I've got the mandate to transform the company. We have apps. We'll be fully transformed in five years. What's my strategy? What do I do? >> Amir: The resources. >> What's the deployment strategy? Single global instance, code in every region, on every cloud? >> It needs to be a solution which is available as a SaaS service, right? So from the customer's perspective, they are onboarding into the supercloud. And then the supercloud is allowing them to do whatever they used to do, you know, historically and in the new world, right? That needs to come together. And that's what we have built is that, we have brought everything together in a way that what used to take months or years, and now taking an hour or two hours, and then people test it for a week or so and deploy it in production. >> I want to bring up something we were talking about before we were on camera about the TCP/IP, the OSI model. That was a concept that destroyed the proprietary narcissist. Work operating systems of the mini computers, which brought in an era of tech prosperity for generations. TCP/IP was kind of the magical moment that allowed for that kind of super networking connection. Inter networking is what's called as a category. It feels like something's going on here with supercloud. The way you describe it, it feels like there's this unification idea. Like the reality is we've got multiple stuff sitting around by default, you either clean it up or get rid of it, right? Or it's almost a, it's either a nuance, a new nuisance or chaos. >> Yeah. And we live in the new world now. We don't have the luxury of time. So we need to move as fast as possible to solve the business problems. And that's what we are running into. If we don't have automated solutions which scale, which solve our problems, then it's going to be a problem. And that's why SaaS is so important in today's world. Why should we have to deploy the network piecemeal? Why can't we have a solution? We solve our problem as we move forward and we accomplish what we need to accomplish and move forward. >> And we don't really need standards here, dude. It's not that we need a standards body if you have unification. >> So because things move so fast, there's no time to create a standards body. And that's why you see companies like ours popping up, which are trying to create a common infrastructure across all clouds. Otherwise if we vent the standardization path may take long. Eventually, we should be going in that direction. But we don't have the luxury of time. That's what I was trying to get to. >> Well, what's interesting is, is that to your point about standards and ratification, what ratifies a defacto anything? In the old days there was some technical bodies involved, but here, I think developers drive everything. So if you look at the developers and how they're voting with their code. They're instantly, organically defining everything as a collective intelligence. >> And just like you're putting out the paper and making it available, everybody's contributing to that. That's why you need to have APIs and terra form type constructs, which are available so that the customers can continue to improve upon that. And that's the Net DevOps, right? So that you need to have. >> What was once sacrilege, just sayin', in business school, back in the days when I got my business degree after my CS degree was, you know, no one wants to have a better mousetrap, a bad business model to have a better mouse trap. In this case, the better mouse trap, the better solution actually could be that thing. >> It is that thing. >> I mean, that can trigger, tips over the industry. >> And that that's where we are seeing our customers. You know, I mean, we have some publicly referenceable customers like Coke or Warner Music Group or, you know, multiple others and chart industries. The way we are solving the problem. They have some of the largest environments in the industry from the cloud perspective. And their whole network infrastructure is running on the Alkira infrastructure. And they're able to adopt new clouds within days rather than waiting for months to architect and then deploy and then figure out how to manage it and operate it. It's available as a service. >> John: And we've heard from your customer, Warner, they were just on the program. >> Amir: Yes. Okay, okay. >> So they're building a supercloud. So superclouds aren't just for tech companies. >> Amir: No. >> You guys build a supercloud for networking. >> Amir: It is. >> But people are building their own superclouds on top of all this new stuff. Talk about that dynamic. >> Healthcare providers, financials, high-tech companies, even startups. One of our startup customers, Tekion, right? They have these dealerships that they provide sales and support services to across the globe. And for them to be able to onboard those dealerships, it is 80% less time to production. That is real money, right? So, maybe Atif can give you a lot more examples of customers who are deploying. >> Talk about some of the customer activity. What are they like? Are they laggards, they innovators? Are they trying to hit the easy button? Are they coming in late or are you got some high customers? >> Actually most of our customers, all of our customers or customers in general. I don't think they have a choice but to move in this direction because, you know, the cloud has, like everything is quick now. So the cloud teams are moving faster in these enterprises. So now that they cannot afford the network nor to keep up pace with the cloud teams. So, they don't have a choice but to go with something similar where you can, you know, build your network on demand and bring up your network as quickly as possible to meet all those use cases. So, I'll give you an example. >> John: So the demand's high for what you guys do. >> Demand is very high because the cloud teams have- >> John: Yeah. They're going fast. >> They're going fast and there's no stopping. And then network teams, they have to keep up with them. And you cannot keep deploying, you know, networks the way you used to deploy back in the day. And as far as the use cases are concerned, there are so many use cases which our customers are using our platform for. One of the use cases, I'll give you an example of these financial customers. Some of the financial customers, they have their customers who they provide data, like stock exchanges, that provide like market data information to their customers out of data centers part. But now, their customers are moving into the cloud as well. So they need to come in from the cloud. So when they're coming in from the cloud, you cannot be giving them data from your data center because that takes time, and your hair pinning everything back. >> Moving data is like moving, moving money, someone said. >> Exactly. >> Exactly. And the other thing is like you have to optimize your traffic flows in the cloud as well because every time you leave the cloud, you get charged a lot. So, you don't want to leave the cloud unless you have to leave the cloud, your traffic. So, you have to come up or use a service which allows you to optimize all those traffic flows as well, you know? >> My final question to you guys, first of all, thanks for coming on Supercloud Program. Really appreciate it. Congratulations on your success. And you guys have a great positioning and I'm a big fan. And I have to ask, you guys are agile, nimble startup, smart on the cutting edge. Supercloud concept seems to resonate with people who are kind of on the front range of this major wave. While all the incumbents like Cisco, Microsoft, even AWS, they're like, I think they're looking at it, like what is that? I think it's coming up really fast, this trend. Because I know people talk about multi-cloud, I get that. But like, this whole supercloud is not just SaaS, it's more going on there. What do you think is going on between the folks who get it, supercloud, get the concept, and some are who are scratching their heads, whether it's the Ciscos or someone, like I don't get it. Why is supercloud important for the folks that aren't really seeing it? >> So first of all, I mean, the customers, what we saw about six months, 12 months ago, were a little slower to adopt the supercloud kind of concept. And there were leading edge customers who were coming and adopting it. Now, all of a sudden, over the last six to nine months, we've seen a flurry of customers coming in and they are from all disciplines or all very diverse set of customers. And they're starting to see the value of that because of the practical implications of what they're doing. You know, these shadow IT type environments are no longer working and there's a lot of pressure from the management to move faster. And then that's where they're coming in. And perhaps, Atif, if you can give a few examples of. >> Yeah. And I'll also just add to your point earlier about the network needing to be there 'cause the cloud teams are like, let's go faster. And the network's always been slow because, but now, it's been almost turbocharged. >> Atif: Yeah. Yeah, exactly. And as I said, like there was no choice here. You had to move in this industry. And the other thing I would add a little bit is now if you look at all these enterprises, most of their traffic is from, even from which is coming from the on-prem, it's going to the cloud SaaS applications or public clouds. And it's more than 50% of traffic, which is leaving your, you know, what you used to call, your network or the private network. So now it's like, you know, before it used to just connect sites to data centers and sites together. Now, it's a cloud as well as the SaaS application. So it's either internet bound or the public cloud bound. So now you have to build a network quickly, which caters to all these use cases. And that's where like something- >> And you guys, your solution to me is you eliminate all that work for the customer. Now, they can treat the cloud like a bag of Legos. And do their thing. Well, I oversimplify. Well, you know I'm talking about. >> Atif: Right, exactly. >> And to answer your question earlier about what about the big companies coming in and, you know, now they slow to adopt? And, you know, what normally happens is when Cisco came up, right? There used to be 16 different protocols suites. And then we finally settled on TCP/IP and DECnet or AppleTalk or X&S or, you know, you name it, right? Those companies did not adapt to the networking the way it was supposed to be done. And guess what happened, right? So if the companies in the networking space do not adopt this new concept or new way of doing things, I think some of them will become extinct over time. >> Well, I think the force and function too is the cloud teams as well. So you got two evolutions. You got architectural relevance. That's real as impact. >> It's very important. >> Cost, speed. >> And I look at it as a very similar disruption to what Cisco's the world, very early days did to, you know, bring the networking out, right? And it became the internet. But now we are going through the cloud. It's the cloud era, right? How does the cloud evolve over the next 10, 15, 20 years? Everything's is going to be offered as a service, right? So slowly data centers go away, the network becomes a plumbing thing. Very, you know, simple to deploy. And everything on top of that is virtualized in the cloud-like manners. >> And that makes the networks hardened and more secure. >> More secure. >> It's a great way to be secure. You remember the glory days, we'll go back 15 years. The Cisco conversation was, we got to move up to stack. All the manager would fight each other. Now, what does that actually mean? Stay where we are. Stay in your lane. This is kind of like the network's version of moving up the stack because not so much up the stack, but the cloud is everywhere. It's almost horizontally scaled. >> It's extending into the on-premise. It is already moving towards the edge, right? So, you will see a lot- >> So, programmability is a big program. So you guys are hitting programmability, compatibility, getting people into an environment they're comfortable operating. So the Ops people love it. >> Exactly. >> Spans the clouds to a level of SLA management. It might not be perfectly spanning applications, but you can actually know latencies between clouds, measure that. And then so you're basically managing your network now as the overall infrastructure. >> Right. And it needs to be a very intelligent infrastructure going forward, right? Because customers do not want to wait to be able to troubleshoot. They don't want to be able to wait to deploy something, right? So, it needs to be a level of automation. >> Okay. So the question for you guys both on we'll end on is what is the enablement that, because you guys are a disruptive enabler, right? You create this fabric. You're going to enable companies to do stuff. What are some of the things that you see and your customers might be seeing as things that they're going to do as a result of having this enablement? So what are some of those things? >> Amir: Atif, perhaps you can talk through the some of the customer experience on that. >> It's agility. And we are allowing these customers to move very, very quickly and build these networks which meet all these requirements inside the cloud. Because as Amir was saying, in the cloud era, networking is changing. And if you look at, you know, going back to your comment about the existing networking vendors. Some of them still think that, you know, just connecting to the cloud using some concepts like Cloud OnRamp is cloud networking, but it's changing now. >> John: 'Cause there's apps that are depending upon. >> Exactly. And it's all distributed. Like IT infrastructure, as I said earlier, is all distributed. And at the end of the day, you have to make sure that wherever your user is, wherever your app is, you are able to connect them securely. >> Historically, it used to be about building a router bigger and bigger and bigger and bigger, you know, and then interconnecting those routers. Now, it's all about horizontal scale. You don't need to build big, you need to scale it, right? And that's what cloud brings to the customer. >> It's a cultural change for Cisco and Juniper because they have to understand that they're still could be in the game and still win. >> Exactly. >> The question I have for you, what are your customers telling you that, what's some of the anecdotal, like, 'cause you guys have a good solution, is it, "Oh my god, you guys saved my butt." Or what are some of the commentary that you hear from the customers in terms of praise and and glory from your solution? >> Oh, some even say, when we do our demo and stuff, they say it's too hard to believe. >> Believe. >> Like, too hard. It's hard, you know, it's >> I dont believe you. They're skeptics. >> I don't believe you that because now you're able to bring up a global network within minutes. With networking services, like let's say you have APAC, you know, on-prem users, cloud also there, cloud here, users here, you can bring up a global network with full routed connectivity between all these endpoints with security services. You can bring up like a firewall from a third party or our services in the middle. This is a matter of minutes now. And this is all high speed connectivity with SLAs. Imagine like before connecting, you know, Singapore to U.S. East or Hong Kong to Frankfurt, you know, if you were putting your infrastructure in columns like E-connects, you would have to go, you know, figure out like, how am I going to- >> Seal line In, connect to it? Yeah. A lot of hassles, >> If you had to put like firewalls in the middle, segmentation, you had to, you know, isolate different entities. >> That's called heavy lifting. >> So what you're seeing is, you know, it's like customer comes in, there's a disbelief, can you really do that? And then they try it out, they go, "Wow, this works." Right? It's deployed in a small environment. And then all of a sudden they start taking off, right? And literally we have seen customers go from few thousand dollars a month or year type deployments to multi-million dollars a year type deployments in very, very short amount of time, in a few months. >> And you guys are pay as you go? >> Pay as you go. >> Pay as go usage cloud-based compatibility. >> Exactly. And it's amazing once they get to deploy the solution. >> What's the variable on the cost? >> On the cost? >> Is it traffic or is it. >> It's multiple different things. It's packaged into the overall solution. And as a matter of fact, we end up saving a lot of money to the customers. And not only in one way, in multiple different ways. And we do a complete TOI analysis for the customers. So it's bandwidth, it's number of connections, it's the amount of compute power that we are using. >> John: Similar things that they're used to. >> Just like the cloud constructs. Yeah. >> All right. Networking supercloud. Great. Congratulations. >> Thank you so much. >> Thanks for coming on Supercloud. >> Atif: Thank you. >> And looking forward to seeing more of the demand. Translate, instant networking. I'm sure it's going to be huge with the edge exploding. >> Oh yeah, yeah, yeah, yeah. >> Congratulations. >> Thank you so much. >> Thank you so much. >> Okay. So this is Supercloud 2 event here in Palo Alto. I'm John Furrier. The network Supercloud is here. Checkout Alkira. I'm John Furry, the host. Thanks for watching. (lively music)

>> From theCUBE Studios in Palo Alto in Boston, bringing you data-driven insights from theCUBE and ETR. This is Breaking Analysis with Dave Vellante. >> Confidential computing is a technology that aims to enhance data privacy and security, by providing encrypted computation on sensitive data and isolating data, and apps that are fenced off enclave during processing. The concept of, I got to start over. I fucked that up, I'm sorry. That's not right, what I said was not right. On Dave in five, four, three. Confidential computing is a technology that aims to enhance data privacy and security by providing encrypted computation on sensitive data, isolating data from apps and a fenced off enclave during processing. The concept of confidential computing is gaining popularity, especially in the cloud computing space, where sensitive data is often stored and of course processed. However, there are some who view confidential computing as an unnecessary technology in a marketing ploy by cloud providers aimed at calming customers who are cloud phobic. Hello and welcome to this week's Wikibon Cube Insights powered by ETR. In this Breaking Analysis, we revisit the notion of confidential computing, and to do so, we'll invite two Google experts to the show. But before we get there, let's summarize briefly. There's not a ton of ETR data on the topic of confidential computing, I mean, it's a technology that's deeply embedded into silicon and computing architectures. But at the highest level, security remains the number one priority being addressed by IT decision makers in the coming year as shown here. And this data is pretty much across the board by industry, by region, by size of company. I mean we dug into it and the only slight deviation from the mean is in financial services. The second and third most cited priorities, cloud migration and analytics are noticeably closer to cybersecurity in financial services than in other sectors, likely because financial services has always been hyper security conscious, but security is still a clear number one priority in that sector. The idea behind confidential computing is to better address threat models for data in execution. Protecting data at rest and data in transit have long been a focus of security approaches, but more recently, silicon manufacturers have introduced architectures that separate data and applications from the host system, ARM, Intel, AMD, Nvidia and other suppliers are all on board, as are the big cloud players. Now, the argument against confidential computing is that it narrowly focuses on memory encryption and it doesn't solve the biggest problems in security. Multiple system images, updates, different services and the entire code flow aren't directly addressed by memory encryption. Rather to truly attack these problems, many believe that OSs need to be re-engineered with the attacker and hacker in mind. There are so many variables and at the end of the day, critics say the emphasis on confidential computing made by cloud providers is overstated and largely hype. This tweet from security researcher Rodrigo Bronco, sums up the sentiment of many skeptics. He says, "Confidential computing is mostly a marketing campaign from memory encryption. It's not driving the industry towards the hard open problems. It is selling an illusion." Okay. Nonetheless, encrypting data in use and fencing off key components of the system isn't a bad thing, especially if it comes with the package essentially for free. There has been a lack of standardization and interoperability between different confidential computing approaches. But the confidential computing consortium was established in 2019 ostensibly to accelerate the market and influence standards. Notably, AWS is not part of the consortium, likely because the politics of the consortium were probably a conundrum for AWS because the base technology defined by the consortium is seen as limiting by AWS. This is my guess, not AWS' words. But I think joining the consortium would validate a definition which AWS isn't aligned with. And two, it's got to lead with this Annapurna acquisition. It was way ahead with ARM integration, and so it's probably doesn't feel the need to validate its competitors. Anyway, one of the premier members of the confidential computing consortium is Google, along with many high profile names, including Aem, Intel, Meta, Red Hat, Microsoft, and others. And we're pleased to welcome two experts on confidential computing from Google to unpack the topic. Nelly Porter is Head of Product for GCP Confidential Computing and Encryption and Dr. Patricia Florissi is the Technical Director for the Office of the CTO at Google Cloud. Welcome Nelly and Patricia, great to have you. >> Great to be here. >> Thank you so much for having us. >> You're very welcome. Nelly, why don't you start and then Patricia, you can weigh in. Just tell the audience a little bit about each of your roles at Google Cloud. >> So I'll start, I'm owning a lot of interesting activities in Google and again, security or infrastructure securities that I usually own. And we are talking about encryption, end-to-end encryption, and confidential computing is a part of portfolio. Additional areas that I contribute to get with my team to Google and our customers is secure software supply chain because you need to trust your software. Is it operate in your confidential environment to have end-to-end security, about if you believe that your software and your environment doing what you expect, it's my role. >> Got it. Okay, Patricia? >> Well, I am a Technical Director in the Office of the CTO, OCTO for short in Google Cloud. And we are a global team, we include former CTOs like myself and senior technologies from large corporations, institutions and a lot of success for startups as well. And we have two main goals, first, we walk side by side with some of our largest, more strategic or most strategical customers and we help them solve complex engineering technical problems. And second, we advice Google and Google Cloud Engineering, product management on emerging trends and technologies to guide the trajectory of our business. We are unique group, I think, because we have created this collaborative culture with our customers. And within OCTO I spend a lot of time collaborating with customers in the industry at large on technologies that can address privacy, security, and sovereignty of data in general. >> Excellent. Thank you for that both of you. Let's get into it. So Nelly, what is confidential computing from Google's perspective? How do you define it? >> Confidential computing is a tool and one of the tools in our toolbox. And confidential computing is a way how we would help our customers to complete this very interesting end-to-end lifecycle of the data. And when customers bring in the data to cloud and want to protect it as they ingest it to the cloud, they protect it at rest when they store data in the cloud. But what was missing for many, many years is ability for us to continue protecting data and workloads of our customers when they run them. And again, because data is not brought to cloud to have huge graveyard, we need to ensure that this data is actually indexed. Again, there is some insights driven and drawn from this data. You have to process this data and confidential computing here to help. Now we have end-to-end protection of our customer's data when they bring the workloads and data to cloud thanks to confidential computing. >> Thank you for that. Okay, we're going to get into the architecture a bit, but before we do Patricia, why do you think this topic of confidential computing is such an important technology? Can you explain? Do you think it's transformative for customers and if so, why? >> Yeah, I would maybe like to use one thought, one way, one intuition behind why confidential computing matters because at the end of the day, it reduces more and more the customer's thrush boundaries and the attack surface. That's about reducing that periphery, the boundary in which the customer needs to mind about trust and safety. And in a way is a natural progression that you're using encryption to secure and protect data in the same way that we are encrypting data in transit and at rest. Now, we are also encrypting data while in the use. And among other beneficials, I would say one of the most transformative ones is that organizations will be able to collaborate with each other and retain the confidentiality of the data. And that is across industry, even though it's highly focused on, I wouldn't say highly focused but very beneficial for highly regulated industries, it applies to all of industries. And if you look at financing for example, where bankers are trying to detect fraud and specifically double finance where a customer is actually trying to get a finance on an asset, let's say a boat or a house, and then it goes to another bank and gets another finance on that asset. Now bankers would be able to collaborate and detect fraud while preserving confidentiality and privacy of the data. >> Interesting and I want to understand that a little bit more but I got to push you a little bit on this, Nellie if I can, because there's a narrative out there that says confidential computing is a marketing ploy I talked about this up front, by cloud providers that are just trying to placate people that are scared of the cloud. And I'm presuming you don't agree with that, but I'd like you to weigh in here. The argument is confidential computing is just memory encryption, it doesn't address many other problems. It is over hyped by cloud providers. What do you say to that line of thinking? >> I absolutely disagree as you can imagine Dave, with this statement. But the most importantly is we mixing a multiple concepts I guess, and exactly as Patricia said, we need to look at the end-to-end story, not again, is a mechanism. How confidential computing trying to execute and protect customer's data and why it's so critically important. Because what confidential computing was able to do, it's in addition to isolate our tenants in multi-tenant environments the cloud offering to offer additional stronger isolation, they called it cryptographic isolation. It's why customers will have more trust to customers and to other customers, the tenants running on the same host but also us because they don't need to worry about against rats and more malicious attempts to penetrate the environment. So what confidential computing is helping us to offer our customers stronger isolation between tenants in this multi-tenant environment, but also incredibly important, stronger isolation of our customers to tenants from us. We also writing code, we also software providers, we also make mistakes or have some zero days. Sometimes again us introduce, sometimes introduced by our adversaries. But what I'm trying to say by creating this cryptographic layer of isolation between us and our tenants and among those tenants, we really providing meaningful security to our customers and eliminate some of the worries that they have running on multi-tenant spaces or even collaborating together with very sensitive data knowing that this particular protection is available to them. >> Okay, thank you. Appreciate that. And I think malicious code is often a threat model missed in these narratives. You know, operator access. Yeah, maybe I trust my cloud's provider, but if I can fence off your access even better, I'll sleep better at night separating a code from the data. Everybody's ARM, Intel, AMD, Nvidia and others, they're all doing it. I wonder if Nell, if we could stay with you and bring up the slide on the architecture. What's architecturally different with confidential computing versus how operating systems and VMs have worked traditionally? We're showing a slide here with some VMs, maybe you could take us through that. >> Absolutely, and Dave, the whole idea for Google and now industry way of dealing with confidential computing is to ensure that three main property is actually preserved. Customers don't need to change the code. They can operate in those VMs exactly as they would with normal non-confidential VMs. But to give them this opportunity of lift and shift though, no changing the apps and performing and having very, very, very low latency and scale as any cloud can, some things that Google actually pioneer in confidential computing. I think we need to open and explain how this magic was actually done, and as I said, it's again the whole entire system have to change to be able to provide this magic. And I would start with we have this concept of root of trust and root of trust where we will ensure that this machine within the whole entire host has integrity guarantee, means nobody changing my code on the most low level of system, and we introduce this in 2017 called Titan. So our specific ASIC, specific inch by inch system on every single motherboard that we have that ensures that your low level former, your actually system code, your kernel, the most powerful system is actually proper configured and not changed, not tempered. We do it for everybody, confidential computing included, but for confidential computing is what we have to change, we bring in AMD or future silicon vendors and we have to trust their former, their way to deal with our confidential environments. And that's why we have obligation to validate intelligent not only our software and our former but also former and software of our vendors, silicon vendors. So we actually, when we booting this machine as you can see, we validate that integrity of all of this system is in place. It means nobody touching, nobody changing, nobody modifying it. But then we have this concept of AMD Secure Processor, it's special ASIC best specific things that generate a key for every single VM that our customers will run or every single node in Kubernetes or every single worker thread in our Hadoop spark capability. We offer all of that and those keys are not available to us. It's the best case ever in encryption space because when we are talking about encryption, the first question that I'm receiving all the time, "Where's the key? Who will have access to the key?" because if you have access to the key then it doesn't matter if you encrypted or not. So, but the case in confidential computing why it's so revolutionary technology, us cloud providers who don't have access to the keys, they're sitting in the hardware and they fed to memory controller. And it means when hypervisors that also know about this wonderful things saying I need to get access to the memories, that this particular VM I'm trying to get access to. They do not decrypt the data, they don't have access to the key because those keys are random, ephemeral and per VM, but most importantly in hardware not exportable. And it means now you will be able to have this very interesting world that customers or cloud providers will not be able to get access to your memory. And what we do, again as you can see, our customers don't need to change their applications. Their VMs are running exactly as it should run. And what you've running in VM, you actually see your memory clear, it's not encrypted. But God forbid is trying somebody to do it outside of my confidential box, no, no, no, no, no, you will now be able to do it. Now, you'll see cyber test and it's exactly what combination of these multiple hardware pieces and software pieces have to do. So OS is also modified and OS is modified such way to provide integrity. It means even OS that you're running in your VM box is not modifiable and you as customer can verify. But the most interesting thing I guess how to ensure the super performance of this environment because you can imagine Dave, that's increasing and it's additional performance, additional time, additional latency. So we're able to mitigate all of that by providing incredibly interesting capability in the OS itself. So our customers will get no changes needed, fantastic performance and scales as they would expect from cloud providers like Google. >> Okay, thank you. Excellent, appreciate that explanation. So you know again, the narrative on this is, well, you've already given me guarantees as a cloud provider that you don't have access to my data, but this gives another level of assurance, key management as they say is key. Now humans aren't managing the keys, the machines are managing them. So Patricia, my question to you is in addition to, let's go pre-confidential computing days, what are the sort of new guarantees that these hardware based technologies are going to provide to customers? >> So if I am a customer, I am saying I now have full guarantee of confidentiality and integrity of the data and of the code. So if you look at code and data confidentiality, the customer cares and they want to know whether their systems are protected from outside or unauthorized access, and that we covered with Nelly that it is. Confidential computing actually ensures that the applications and data antennas remain secret. The code is actually looking at the data, only the memory is decrypting the data with a key that is ephemeral, and per VM, and generated on demand. Then you have the second point where you have code and data integrity and now customers want to know whether their data was corrupted, tempered with or impacted by outside actors. And what confidential computing ensures is that application internals are not tempered with. So the application, the workload as we call it, that is processing the data is also has not been tempered and preserves integrity. I would also say that this is all verifiable, so you have attestation and this attestation actually generates a log trail and the log trail guarantees that provides a proof that it was preserved. And I think that the offers also a guarantee of what we call sealing, this idea that the secrets have been preserved and not tempered with, confidentiality and integrity of code and data. >> Got it. Okay, thank you. Nelly, you mentioned, I think I heard you say that the applications is transparent, you don't have to change the application, it just comes for free essentially. And we showed some various parts of the stack before, I'm curious as to what's affected, but really more importantly, what is specifically Google's value add? How do partners participate in this, the ecosystem or maybe said another way, how does Google ensure the compatibility of confidential computing with existing systems and applications? >> And a fantastic question by the way, and it's very difficult and definitely complicated world because to be able to provide these guarantees, actually a lot of work was done by community. Google is very much operate and open. So again our operating system, we working this operating system repository OS is OS vendors to ensure that all capabilities that we need is part of the kernels are part of the releases and it's available for customers to understand and even explore if they have fun to explore a lot of code. We have also modified together with our silicon vendors kernel, host kernel to support this capability and it means working this community to ensure that all of those pages are there. We also worked with every single silicon vendor as you've seen, and it's what I probably feel that Google contributed quite a bit in this world. We moved our industry, our community, our vendors to understand the value of easy to use confidential computing or removing barriers. And now I don't know if you noticed Intel is following the lead and also announcing a trusted domain extension, very similar architecture and no surprise, it's a lot of work done with our partners to convince work with them and make this capability available. The same with ARM this year, actually last year, ARM announced future design for confidential computing, it's called confidential computing architecture. And it's also influenced very heavily with similar ideas by Google and industry overall. So it's a lot of work in confidential computing consortiums that we are doing, for example, simply to mention, to ensure interop as you mentioned, between different confidential environments of cloud providers. They want to ensure that they can attest to each other because when you're communicating with different environments, you need to trust them. And if it's running on different cloud providers, you need to ensure that you can trust your receiver when you sharing your sensitive data workloads or secret with them. So we coming as a community and we have this at Station Sig, the community-based systems that we want to build, and influence, and work with ARM and every other cloud providers to ensure that they can interop. And it means it doesn't matter where confidential workloads will be hosted, but they can exchange the data in secure, verifiable and controlled by customers really. And to do it, we need to continue what we are doing, working open and contribute with our ideas and ideas of our partners to this role to become what we see confidential computing has to become, it has to become utility. It doesn't need to be so special, but it's what what we've wanted to become. >> Let's talk about, thank you for that explanation. Let's talk about data sovereignty because when you think about data sharing, you think about data sharing across the ecosystem in different regions and then of course data sovereignty comes up, typically public policy, lags, the technology industry and sometimes it's problematic. I know there's a lot of discussions about exceptions but Patricia, we have a graphic on data sovereignty. I'm interested in how confidential computing ensures that data sovereignty and privacy edicts are adhered to, even if they're out of alignment maybe with the pace of technology. One of the frequent examples is when you delete data, can you actually prove the data is deleted with a hundred percent certainty, you got to prove that and a lot of other issues. So looking at this slide, maybe you could take us through your thinking on data sovereignty. >> Perfect. So for us, data sovereignty is only one of the three pillars of digital sovereignty. And I don't want to give the impression that confidential computing addresses it at all, that's why we want to step back and say, hey, digital sovereignty includes data sovereignty where we are giving you full control and ownership of the location, encryption and access to your data. Operational sovereignty where the goal is to give our Google Cloud customers full visibility and control over the provider operations, right? So if there are any updates on hardware, software stack, any operations, there is full transparency, full visibility. And then the third pillar is around software sovereignty, where the customer wants to ensure that they can run their workloads without dependency on the provider's software. So they have sometimes is often referred as survivability that you can actually survive if you are untethered to the cloud and that you can use open source. Now, let's take a deep dive on data sovereignty, which by the way is one of my favorite topics. And we typically focus on saying, hey, we need to care about data residency. We care where the data resides because where the data is at rest or in processing need to typically abides to the jurisdiction, the regulations of the jurisdiction where the data resides. And others say, hey, let's focus on data protection, we want to ensure the confidentiality, and integrity, and availability of the data, which confidential computing is at the heart of that data protection. But it is yet another element that people typically don't talk about when talking about data sovereignty, which is the element of user control. And here Dave, is about what happens to the data when I give you access to my data, and this reminds me of security two decades ago, even a decade ago, where we started the security movement by putting firewall protections and logging accesses. But once you were in, you were able to do everything you wanted with the data. An insider had access to all the infrastructure, the data, and the code. And that's similar because with data sovereignty, we care about whether it resides, who is operating on the data, but the moment that the data is being processed, I need to trust that the processing of the data we abide by user's control, by the policies that I put in place of how my data is going to be used. And if you look at a lot of the regulation today and a lot of the initiatives around the International Data Space Association, IDSA and Gaia-X, there is a movement of saying the two parties, the provider of the data and the receiver of the data going to agree on a contract that describes what my data can be used for. The challenge is to ensure that once the data crosses boundaries, that the data will be used for the purposes that it was intended and specified in the contract. And if you actually bring together, and this is the exciting part, confidential computing together with policy enforcement. Now, the policy enforcement can guarantee that the data is only processed within the confines of a confidential computing environment, that the workload is in cryptographically verified that there is the workload that was meant to process the data and that the data will be only used when abiding to the confidentiality and integrity safety of the confidential computing environment. And that's why we believe confidential computing is one necessary and essential technology that will allow us to ensure data sovereignty, especially when it comes to user's control. >> Thank you for that. I mean it was a deep dive, I mean brief, but really detailed. So I appreciate that, especially the verification of the enforcement. Last question, I met you two because as part of my year-end prediction post, you guys sent in some predictions and I wasn't able to get to them in the predictions post, so I'm thrilled that you were able to make the time to come on the program. How widespread do you think the adoption of confidential computing will be in '23 and what's the maturity curve look like this decade in your opinion? Maybe each of you could give us a brief answer. >> So my prediction in five, seven years as I started, it will become utility, it will become TLS. As of freakin' 10 years ago, we couldn't believe that websites will have certificates and we will support encrypted traffic. Now we do, and it's become ubiquity. It's exactly where our confidential computing is heeding and heading, I don't know we deserve yet. It'll take a few years of maturity for us, but we'll do that. >> Thank you. And Patricia, what's your prediction? >> I would double that and say, hey, in the very near future, you will not be able to afford not having it. I believe as digital sovereignty becomes ever more top of mind with sovereign states and also for multinational organizations, and for organizations that want to collaborate with each other, confidential computing will become the norm, it will become the default, if I say mode of operation. I like to compare that today is inconceivable if we talk to the young technologists, it's inconceivable to think that at some point in history and I happen to be alive, that we had data at rest that was non-encrypted, data in transit that was not encrypted. And I think that we'll be inconceivable at some point in the near future that to have unencrypted data while we use. >> You know, and plus I think the beauty of the this industry is because there's so much competition, this essentially comes for free. I want to thank you both for spending some time on Breaking Analysis, there's so much more we could cover. I hope you'll come back to share the progress that you're making in this area and we can double click on some of these topics. Really appreciate your time. >> Anytime. >> Thank you so much, yeah. >> In summary, while confidential computing is being touted by the cloud players as a promising technology for enhancing data privacy and security, there are also those as we said, who remain skeptical. The truth probably lies somewhere in between and it will depend on the specific implementation and the use case as to how effective confidential computing will be. Look as with any new tech, it's important to carefully evaluate the potential benefits, the drawbacks, and make informed decisions based on the specific requirements in the situation and the constraints of each individual customer. But the bottom line is silicon manufacturers are working with cloud providers and other system companies to include confidential computing into their architectures. Competition in our view will moderate price hikes and at the end of the day, this is under-the-covers technology that essentially will come for free, so we'll take it. I want to thank our guests today, Nelly and Patricia from Google. And thanks to Alex Myerson who's on production and manages the podcast. Ken Schiffman as well out of our Boston studio. Kristin Martin and Cheryl Knight help get the word out on social media and in our newsletters, and Rob Hoof is our editor-in-chief over at siliconangle.com, does some great editing for us. Thank you all. Remember all these episodes are available as podcasts. Wherever you listen, just search Breaking Analysis podcast. I publish each week on wikibon.com and siliconangle.com where you can get all the news. If you want to get in touch, you can email me at david.vellante@siliconangle.com or DM me at D Vellante, and you can also comment on my LinkedIn post. Definitely you want to check out etr.ai for the best survey data in the enterprise tech business. I know we didn't hit on a lot today, but there's some amazing data and it's always being updated, so check that out. This is Dave Vellante for theCUBE Insights powered by ETR. Thanks for watching and we'll see you next time on Breaking Analysis. (subtle music)

(light music) >> Hi everybody. Welcome to this Cube Conversation. I'm really pleased to announce a collaboration with Rob Strechay. He's a guest cube analyst, and we'll be working together to extract the signal from the noise. Rob is a long-time product pro, working at a number of firms including AWS, HP, HPE, NetApp, Snowplow. I did a stint as an analyst at Enterprise Strategy Group. Rob, good to see you. Thanks for coming into our Marlboro Studios. >> Well, thank you for having me. It's always great to be here. >> I'm really excited about working with you. We've known each other for a long time. You've been in the Cube a bunch. You know, you're in between gigs, and I think we can have a lot of fun together. Covering events, covering trends. So. let's get into it. What's happening out there? We're sort of exited the isolation economy. Things were booming. Now, everybody's tapping the brakes. From your standpoint, what are you seeing out there? >> Yeah. I'm seeing that people are really looking how to get more out of their data. How they're bringing things together, how they're looking at the costs of Cloud, and understanding how are they building out their SaaS applications. And understanding that when they go in and actually start to use Cloud, it's not only just using the base services anymore. They're looking at, how do I use these platforms as a service? Some are easier than others, and they're trying to understand, how do I get more value out of that relationship with the Cloud? They're also consolidating the number of Clouds that they have, I would say to try to better optimize their spend, and getting better pricing for that matter. >> Are you seeing people unhook Clouds, or just reduce maybe certain Cloud activities and going maybe instead of 60/40 going 90/10? >> Correct. It's more like the 90/10 type of rule where they're starting to say, Hey I'm not going to get rid of Azure or AWS or Google. I'm going to move a portion of this over that I was using on this one service. Maybe I got a great two-year contract to start with on this platform as a service or a database as a service. I'm going to unhook from that and maybe go with an independent. Maybe with something like a Snowflake or a Databricks on top of another Cloud, so that I can consolidate down. But it also gives them more flexibility as well. >> In our last breaking analysis, Rob, we identified six factors that were reducing Cloud consumption. There were factors and customer tactics. And I want to get your take on this. So, some of the factors really, you got fewer mortgage originations. FinTech, obviously big Cloud user. Crypto, not as much activity there. Lower ad spending means less Cloud. And then one of 'em, which you kind of disagreed with was less, less analytics, you know, fewer... Less frequency of calculations. I'll come back to that. But then optimizing compute using Graviton or AMD instances moving to cheaper storage tiers. That of course makes sense. And then optimize pricing plans. Maybe going from On Demand, you know, to, you know, instead of pay by the drink, buy in volume. Okay. So, first of all, do those make sense to you with the exception? We'll come back and talk about the analytics piece. Is that what you're seeing from customers? >> Yeah, I think so. I think that was pretty much dead on with what I'm seeing from customers and the ones that I go out and talk to. A lot of times they're trying to really monetize their, you know, understand how their business utilizes these Clouds. And, where their spend is going in those Clouds. Can they use, you know, lower tiers of storage? Do they really need the best processors? Do they need to be using Intel or can they get away with AMD or Graviton 2 or 3? Or do they need to move in? And, I think when you look at all of these Clouds, they always have pricing curves that are arcs from the newest to the oldest stuff. And you can play games with that. And understanding how you can actually lower your costs by looking at maybe some of the older generation. Maybe your application was written 10 years ago. You don't necessarily have to be on the best, newest processor for that application per se. >> So last, I want to come back to this whole analytics piece. Last June, I think it was June, Dev Ittycheria, who's the-- I call him Dev. Spelled Dev, pronounced Dave. (chuckles softly) Same pronunciation, different spelling. Dev Ittycheria, CEO of Mongo, on the earnings call. He was getting, you know, hit. Things were starting to get a little less visible in terms of, you know, the outlook. And people were pushing him like... Because you're in the Cloud, is it easier to dial down? And he said, because we're the document database, we support transaction applications. We're less discretionary than say, analytics. Well on the Snowflake earnings call, that same month or the month after, they were all over Slootman and Scarpelli. Oh, the Mongo CEO said that they're less discretionary than analytics. And Snowflake was an interesting comment. They basically said, look, we're the Cloud. You can dial it up, you can dial it down, but the area under the curve over a period of time is going to be the same, because they get their customers to commit. What do you say? You disagreed with the notion that people are running their calculations less frequently. Is that because they're trying to do a better job of targeting customers in near real time? What are you seeing out there? >> Yeah, I think they're moving away from using people and more expensive marketing. Or, they're trying to figure out what's my Google ad spend, what's my Meta ad spend? And what they're trying to do is optimize that spend. So, what is the return on advertising, or the ROAS as they would say. And what they're looking to do is understand, okay, I have to collect these analytics that better understand where are these people coming from? How do they get to my site, to my store, to my whatever? And when they're using it, how do they they better move through that? What you're also seeing is that analytics is not only just for kind of the retail or financial services or things like that, but then they're also, you know, using that to make offers in those categories. When you move back to more, you know, take other companies that are building products and SaaS delivered products. They may actually go and use this analytics for making the product better. And one of the big reasons for that is maybe they're dialing back how many product managers they have. And they're looking to be more data driven about how they actually go and build the product out or enhance the product. So maybe they're, you know, an online video service and they want to understand why people are either using or not using the whiteboard inside the product. And they're collecting a lot of that product analytics in a big way so that they can go through that. And they're doing it in a constant manner. This first party type tracking within applications is growing rapidly by customers. >> So, let's talk about who wins in that. So, obviously the Cloud guys, AWS, Google and Azure. I want to come back and unpack that a little bit. Databricks and Snowflake, we reported on our last breaking analysis, it kind of on a collision course. You know, a couple years ago we were thinking, okay, AWS, Snowflake and Databricks, like perfect sandwich. And then of course they started to become more competitive. My sense is they still, you know, compliment each other in the field, right? But, you know, publicly, they've got bigger aspirations, they get big TAMs that they're going after. But it's interesting, the data shows that-- So, Snowflake was off the charts in terms of spending momentum and our EPR surveys. Our partner down in New York, they kind of came into line. They're both growing in terms of market presence. Databricks couldn't get to IPO. So, we don't have as much, you know, visibility on their financials. You know, Snowflake obviously highly transparent cause they're a public company. And then you got AWS, Google and Azure. And it seems like AWS appears to be more partner friendly. Microsoft, you know, depends on what market you're in. And Google wants to sell BigQuery. >> Yeah. >> So, what are you seeing in the public Cloud from a data platform perspective? >> Yeah. I think that was pretty astute in what you were talking about there, because I think of the three, Google is definitely I think a little bit behind in how they go to market with their partners. Azure's done a fantastic job of partnering with these companies to understand and even though they may have Synapse as their go-to and where they want people to go to do AI and ML. What they're looking at is, Hey, we're going to also be friendly with Snowflake. We're also going to be friendly with a Databricks. And I think that, Amazon has always been there because that's where the market has been for these developers. So, many, like Databricks' and the Snowflake's have gone there first because, you know, Databricks' case, they built out on top of S3 first. And going and using somebody's object layer other than AWS, was not as simple as you would think it would be. Moving between those. >> So, one of the financial meetups I said meetup, but the... It was either the CEO or the CFO. It was either Slootman or Scarpelli talking at, I don't know, Merrill Lynch or one of the other financial conferences said, I think it was probably their Q3 call. Snowflake said 80% of our business goes through Amazon. And he said to this audience, the next day we got a call from Microsoft. Hey, we got to do more. And, we know just from reading the financial statements that Snowflake is getting concessions from Amazon, they're buying in volume, they're renegotiating their contracts. Amazon gets it. You know, lower the price, people buy more. Long term, we're all going to make more money. Microsoft obviously wants to get into that game with Snowflake. They understand the momentum. They said Google, not so much. And I've had customers tell me that they wanted to use Google's AI with Snowflake, but they can't, they got to go to to BigQuery. So, honestly, I haven't like vetted that so. But, I think it's true. But nonetheless, it seems like Google's a little less friendly with the data platform providers. What do you think? >> Yeah, I would say so. I think this is a place that Google looks and wants to own. Is that now, are they doing the right things long term? I mean again, you know, you look at Google Analytics being you know, basically outlawed in five countries in the EU because of GDPR concerns, and compliance and governance of data. And I think people are looking at Google and BigQuery in general and saying, is it the best place for me to go? Is it going to be in the right places where I need it? Still, it's still one of the largest used databases out there just because it underpins a number of the Google services. So you almost get, like you were saying, forced into BigQuery sometimes, if you want to use the tech on top. >> You do strategy. >> Yeah. >> Right? You do strategy, you do messaging. Is it the right call by Google? I mean, it's not a-- I criticize Google sometimes. But, I'm not sure it's the wrong call to say, Hey, this is our ace in the hole. >> Yeah. >> We got to get people into BigQuery. Cause, first of all, BigQuery is a solid product. I mean it's Cloud native and it's, you know, by all, it gets high marks. So, why give the competition an advantage? Let's try to force people essentially into what is we think a great product and it is a great product. The flip side of that is, they're giving up some potential partner TAM and not treating the ecosystem as well as one of their major competitors. What do you do if you're in that position? >> Yeah, I think that that's a fantastic question. And the question I pose back to the companies I've worked with and worked for is, are you really looking to have vendor lock-in as your key differentiator to your service? And I think when you start to look at these companies that are moving away from BigQuery, moving to even, Databricks on top of GCS in Google, they're looking to say, okay, I can go there if I have to evacuate from GCP and go to another Cloud, I can stay on Databricks as a platform, for instance. So I think it's, people are looking at what platform as a service, database as a service they go and use. Because from a strategic perspective, they don't want that vendor locking. >> That's where Supercloud becomes interesting, right? Because, if I can run on Snowflake or Databricks, you know, across Clouds. Even Oracle, you know, they're getting into business with Microsoft. Let's talk about some of the Cloud players. So, the big three have reported. >> Right. >> We saw AWSs Cloud growth decelerated down to 20%, which is I think the lowest growth rate since they started to disclose public numbers. And they said they exited, sorry, they said January they grew at 15%. >> Yeah. >> Year on year. Now, they had some pretty tough compares. But nonetheless, 15%, wow. Azure, kind of mid thirties, and then Google, we had kind of low thirties. But, well behind in terms of size. And Google's losing probably almost $3 billion annually. But, that's not necessarily a bad thing by advocating and investing. What's happening with the Cloud? Is AWS just running into the law, large numbers? Do you think we can actually see a re-acceleration like we have in the past with AWS Cloud? Azure, we predicted is going to be 75% of AWS IAS revenues. You know, we try to estimate IAS. >> Yeah. >> Even though they don't share that with us. That's a huge milestone. You'd think-- There's some people who have, I think, Bob Evans predicted a while ago that Microsoft would surpass AWS in terms of size. You know, what do you think? >> Yeah, I think that Azure's going to keep to-- Keep growing at a pretty good clip. I think that for Azure, they still have really great account control, even though people like to hate Microsoft. The Microsoft sellers that are out there making those companies successful day after day have really done a good job of being in those accounts and helping people. I was recently over in the UK. And the UK market between AWS and Azure is pretty amazing, how much Azure there is. And it's growing within Europe in general. In the states, it's, you know, I think it's growing well. I think it's still growing, probably not as fast as it is outside the U.S. But, you go down to someplace like Australia, it's also Azure. You hear about Azure all the time. >> Why? Is that just because of the Microsoft's software state? It's just so convenient. >> I think it has to do with, you know, and you can go with the reasoning they don't break out, you know, Office 365 and all of that out of their numbers is because they have-- They're in all of these accounts because the office suite is so pervasive in there. So, they always have reasons to go back in and, oh by the way, you're on these old SQL licenses. Let us move you up here and we'll be able to-- We'll support you on the old version, you know, with security and all of these things. And be able to move you forward. So, they have a lot of, I guess you could say, levers to stay in those accounts and be interesting. At least as part of the Cloud estate. I think Amazon, you know, is hitting, you know, the large number. Laws of large numbers. But I think that they're also going through, and I think this was seen in the layoffs that they were making, that they're looking to understand and have profitability in more of those services that they have. You know, over 350 odd services that they have. And you know, as somebody who went there and helped to start yet a new one, while I was there. And finally, it went to beta back in September, you start to look at the fact that, that number of services, people, their own sellers don't even know all of their services. It's impossible to comprehend and sell that many things. So, I think what they're going through is really looking to rationalize a lot of what they're doing from a services perspective going forward. They're looking to focus on more profitable services and bringing those in. Because right now it's built like a layer cake where you have, you know, S3 EBS and EC2 on the bottom of the layer cake. And then maybe you have, you're using IAM, the authorization and authentication in there and you have all these different services. And then they call it EMR on top. And so, EMR has to pay for that entire layer cake just to go and compete against somebody like Mongo or something like that. So, you start to unwind the costs of that. Whereas Azure, went and they build basically ground up services for the most part. And Google kind of falls somewhere in between in how they build their-- They're a sort of layer cake type effect, but not as many layers I guess you could say. >> I feel like, you know, Amazon's trying to be a platform for the ecosystem. Yes, they have their own products and they're going to sell. And that's going to drive their profitability cause they don't have to split the pie. But, they're taking a piece of-- They're spinning the meter, as Ziyas Caravalo likes to say on every time Snowflake or Databricks or Mongo or Atlas is, you know, running on their system. They take a piece of the action. Now, Microsoft does that as well. But, you look at Microsoft and security, head-to-head competitors, for example, with a CrowdStrike or an Okta in identity. Whereas, it seems like at least for now, AWS is a more friendly place for the ecosystem. At the same time, you do a lot of business in Microsoft. >> Yeah. And I think that a lot of companies have always feared that Amazon would just throw, you know, bodies at it. And I think that people have come to the realization that a two pizza team, as Amazon would call it, is eight people. I think that's, you know, two slices per person. I'm a little bit fat, so I don't know if that's enough. But, you start to look at it and go, okay, if they're going to start out with eight engineers, if I'm a startup and they're part of my ecosystem, do I really fear them or should I really embrace them and try to partner closer with them? And I think the smart people and the smart companies are partnering with them because they're realizing, Amazon, unless they can see it to, you know, a hundred million, $500 million market, they're not going to throw eight to 16 people at a problem. I think when, you know, you could say, you could look at the elastic with OpenSearch and what they did there. And the licensing terms and the battle they went through. But they knew that Elastic had a huge market. Also, you had a number of ecosystem companies building on top of now OpenSearch, that are now domain on top of Amazon as well. So, I think Amazon's being pretty strategic in how they're doing it. I think some of the-- It'll be interesting. I think this year is a payout year for the cuts that they're making to some of the services internally to kind of, you know, how do we take the fat off some of those services that-- You know, you look at Alexa. I don't know how much revenue Alexa really generates for them. But it's a means to an end for a number of different other services and partners. >> What do you make of this ChatGPT? I mean, Microsoft obviously is playing that card. You want to, you want ChatGPT in the Cloud, come to Azure. Seems like AWS has to respond. And we know Google is, you know, sharpening its knives to come up with its response. >> Yeah, I mean Google just went and talked about Bard for the first time this week and they're in private preview or I guess they call it beta, but. Right at the moment to select, select AI users, which I have no idea what that means. But that's a very interesting way that they're marketing it out there. But, I think that Amazon will have to respond. I think they'll be more measured than say, what Google's doing with Bard and just throwing it out there to, hey, we're going into beta now. I think they'll look at it and see where do we go and how do we actually integrate this in? Because they do have a lot of components of AI and ML underneath the hood that other services use. And I think that, you know, they've learned from that. And I think that they've already done a good job. Especially for media and entertainment when you start to look at some of the ways that they use it for helping do graphics and helping to do drones. I think part of their buy of iRobot was the fact that iRobot was a big user of RoboMaker, which is using different models to train those robots to go around objects and things like that, so. >> Quick touch on Kubernetes, the whole DevOps World we just covered. The Cloud Native Foundation Security, CNCF. The security conference up in Seattle last week. First time they spun that out kind of like reinforced, you know, AWS spins out, reinforced from reinvent. Amsterdam's coming up soon, the CubeCon. What should we expect? What's hot in Cubeland? >> Yeah, I think, you know, Kubes, you're going to be looking at how OpenShift keeps growing and I think to that respect you get to see the momentum with people like Red Hat. You see others coming up and realizing how OpenShift has gone to market as being, like you were saying, partnering with those Clouds and really making it simple. I think the simplicity and the manageability of Kubernetes is going to be at the forefront. I think a lot of the investment is still going into, how do I bring observability and DevOps and AIOps and MLOps all together. And I think that's going to be a big place where people are going to be looking to see what comes out of CubeCon in Amsterdam. I think it's that manageability ease of use. >> Well Rob, I look forward to working with you on behalf of the whole Cube team. We're going to do more of these and go out to some shows extract the signal from the noise. Really appreciate you coming into our studio. >> Well, thank you for having me on. Really appreciate it. >> You're really welcome. All right, keep it right there, or thanks for watching. This is Dave Vellante for the Cube. And we'll see you next time. (light 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. >> 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)

(upbeat music) >> Hello, this is Dave Vellante, and we're here to talk about the massive $61 billion planned acquisition of VMware by Broadcom. And I'm here with Phil Brotherton of NetApp to discuss the implications for customers, for the industry, and NetApp's particular point of view. Phil, welcome. Good to see you again. >> It's great to see you, Dave. >> So this topic has garnered a lot of conversation. What's your take on this epic event? What does it mean for the industry generally, and customers specifically? >> You know, I think time will tell a little bit, Dave. We're in the early days. We've, you know, so we heard the original announcements and then it's evolved a little bit, as we're going now. I think overall it'll be good for the ecosystem in the end. There's a lot you can do when you start combining what VMware can do with compute and some of the hardware assets of Broadcom. There's a lot of security things that can be brought, for example, to the infrastructure, that are very high-end and cool, and then integrated, so it's easy to do. So I think there's a lot of upside for it. There's obviously a lot of concern about what it means for vendor consolidation and pricing and things like that. So time will tell. >> You know, when this announcement first came out, I wrote a piece, you know, how "Broadcom will tame the VMware beast," I called it. And, you know, looked at Broadcom's history and said they're going to cut, they're going to raise prices, et cetera, et cetera. But I've seen a different tone, certainly, as Broadcom has got into the details. And I'm sure I and others maybe scared a lot of customers, but I think everybody's kind of calming down now. What are you hearing from customers about this acquisition? How are they thinking about it? >> You know, I think it varies. There's, I'd say generally we have like half our installed base, Dave, runs ESX Server, so the bulk of our customers use VMware, and generally they love VMware. And I'm talking mainly on-prem. We're just extending to the cloud now, really, at scale. And there's a lot of interest in continuing to do that, and that's really strong. The piece that's careful is this vendor, the cost issues that have come up. The things that were in your piece, actually. And what does that mean to me, and how do I balance that out? Those are the questions people are dealing with right now. >> Yeah, so there's obviously a lot of talk about the macro, the macro headwinds. Everybody's being a little cautious. The CIOs are tapping the brakes. We all sort of know that story. But we have some data from our partner ETR that ask, they go out every quarter and they survey, you know, 1500 or so IT practitioners, and they ask the ones that are planning to spend less, that are cutting, "How are you going to approach that? What's your primary methodology in terms of achieving, you know, cost optimization?" The number one, by far, answer was to consolidate redundant vendors. It was like, it's now up to about 40%. The second, distant second, was, "We're going to, you know, optimize cloud costs." You know, still significant, but it was really that consolidating the redundant vendors. Do you see that? How does NetApp fit into that? >> Yeah, that is an interesting, that's a very interesting bit of research, Dave. I think it's very right. One thing I would say is, because I've been in the infrastructure business in Silicon Valley now for 30 years. So these ups and downs are, that's a consistent thing in our industry, and I always think people should think of their infrastructure and cost management. That's always an issue, with infrastructure as cost management. What I've told customers forever is that when you look at cost management, our best customers at cost management are typically service providers. There's another aspect to cost management, is you want to automate as much as possible. And automation goes along with vendor consolidation, because how you automate different products, you don't want to have too many vendors in your layers. And what I mean by the layers of ecosystem, there's a storage layer, the network layer, the compute layer, like, the security layer, database layer, et cetera. When you think like that, everybody should pick their partners very carefully, per layer. And one last thought on this is, it's not like people are dumb, and not trying to do this. It's, when you look at what happens in the real world, acquisitions happen, things change as you go. And in these big customers, that's just normal, that things change. But you always have to have this push towards consolidating and picking your vendors very carefully. >> Also, just to follow up on that, I mean, you know, when you think about multi-cloud, and you mentioned, you know, you've got some big customers, they do a lot of M & A, it's kind of been multi-cloud by accident. "Oh, we got all these other tools and storage platforms and whatever it is." So where does NetApp fit in that whole consolidation equation? I'm thinking about, you know, cross-cloud services, which is a big VMware theme, thinking about a consistent experience, on-prem, hybrid, across the three big clouds, out to the edge. Where do you fit? >> So our view has been, and it was this view, and we extend it to the cloud, is that the data layer, so in our software, is called ONTAP, the data layer is a really important layer that provides a lot of efficiency. It only gets bigger, how you do compliance, how you do backup, DR, blah blah blah. All that data layer services needs to operate on-prem and on the clouds. So when you look at what we've done over the years, we've extended to all the clouds, our data layer. We've put controls, management tools, over the top, so that you can manage the entire data layer, on-prem and cloud, as one layer. And we're continuing to head down that path, 'cause we think that data layer is obviously the path to maximum ability to do compliance, maximum cost advantages, et cetera. So we've really been the company that set our sights on managing the data layer. Now, if you look at VMware, go up into the network layer, the compute layer, VMware is a great partner, and that's why we work with them so closely, is they're so perfect a fit for us, and they've been a great partner for 20 years for us, connecting those infrastructural data layers: compute, network, and storage. >> Well, just to stay on that for a second. I've seen recently, you kind of doubled down on your VMware alliance. You've got stuff at re:Invent I saw, with AWS, you're close to Azure, and I'm really talking about ONTAP, which is sort of an extension of what you were just talking about, Phil, which is, you know, it's kind of NetApp's storage operating system, if you will. It's a world class. But so, maybe talk about that relationship a little bit, and how you see it evolving. >> Well, so what we've been seeing consistently is, customers want to use the advantages of the cloud. So, point one. And when you have to completely refactor apps and all this stuff, it limits, it's friction. It limits what you can do, it raises costs. And what we did with VMware, VMware is this great platform for being able to run basically client-server apps on-prem and cloud, the exact same way. The problem is, when you have large data sets in the VMs, there's some cost issues and things, especially on the cloud. That drove us to work together, and do what we did. We GA-ed, we're the, so NetApp is the only independent storage, independent storage, say this right, independent storage platform certified to run with VMware cloud on Amazon. We GA-ed that last summer. We GA-ed with Azure, the Azure VMware service, a couple months ago. And you'll see news coming with GCP soon. And so the idea was, make it easy for customers to basically run in a hybrid model. And then if you back out and go, "What does that mean for you as a customer?", it's not saying you should go to the cloud, necessarily, or stay on-prem, or whatever. But it's giving you the flexibility to cost-optimize where you want to be. And from a data management point of view, ONTAP gives you the consistent data management, whichever way you decide to go. >> Yeah, so I've been following NetApp for decades, when you were Network Appliance, and I saw you go from kind of the workstation space into the enterprise. I saw you lean into virtualization really early on, and you've been a great VMware partner ever since. And you were early in cloud, so, sort of talking about, you know, that cross-cloud, what we call supercloud. I'm interested in what you're seeing in terms of specific actions that customers are taking. Like, I think about ELAs, and I think it's a two-edged sword. You know, should customers, you know, lean into ELAs right now? You know, what are you seeing there? You talked about, you know, sort of modernizing apps with things like Kubernetes, you know, cloud migration. What are some of the techniques that you're advising customers to take in the context of this acquisition? >> You know, so the basics of this are pretty easy. One is, and I think even Raghu, the CEO of VMware, has talked about this. Extending your ELA is probably a good idea. Like I said, customers love VMware, so having a commitment for a time, consistent cost management for a time is a good strategy. And I think that's why you're hearing ELA extensions being discussed. It's a good idea. The second part, and I think it goes to your surveys, that cost optimization point on the cloud is, moving to the cloud has huge advantages, but if you just kind of lift and shift, oftentimes the costs aren't realized the way you'd want. And the term "modernization," changing your app to use more Kubernetes, more cloud-native services, is often a consideration that goes into that. But that requires time. And you know, most companies have hundreds of apps, or thousands of apps, they have to consider modernizing. So you want to then think through the journey, what apps are going to move, what gets modernized, what gets lifted-shifted, how many data centers are you compressing? There's a lot of data center, the term I've been hearing is "data center evacuations," but data center consolidation. So that there's some even energy savings advantages sometimes with that. But the whole point, I mean, back up to my whole point, the whole point is having the infrastructure that gives you the flexibility to make the journey on your cost advantages and your business requirements. Not being forced to it. Like, it's not really a philosophy, it's more of a business optimization strategy. >> When you think about application modernization and Kubernetes, how does NetApp, you know, fit into that, as a data layer? >> Well, so if you kind of think, you said, like our journey, Dave, was, when we started our life, we were doing basically virtualization of volumes and things for technical customers. And the servers were always bare metal servers that we got involved with back then. This is, like, going back 20 years. Then everyone moved to VMs, and, like, it's probably, today, I mean, getting to your question in a second, but today, loosely, 20% bare metal servers, 80% virtual machines today. And containers is growing, now a big growing piece. So, if you will, sort of another level of virtual machines in containers. And containers were historically stateless, meaning the storage didn't have anything to do. Storage is always the stateful area in the architectures. But as containers are getting used more, stateful containers have become a big deal. So we've put a lot of emphasis into a product line we call Astra that is the world's best data management for containers. And that's both a cloud service and used on-prem in a lot of my customers. It's a big growth area. So that's what, when I say, like, one partner that can do data management, just, that's what we have to do. We have to keep moving with our customers to the type of data they want to store, and how do you store it most efficiently? Hey, one last thought on this is, where I really see this happening, there's a booming business right now in artificial intelligence, and we call it modern data analytics, but people combining big data lakes with AI, and that's where some of this, a lot of the container work comes in. We've extended objects, we have a thing we call file-object duality, to make it easy to bridge the old world of files to the new world of objects. Those all go hand in hand with app modernization. >> Yeah, it's a great thing about this industry. It never sits still. And you're right, it's- >> It's why I'm in it. >> Me too. Yeah, it's so much fun. There's always something. >> It is an abstraction layer. There's always going to be another abstraction layer. Serverless is another example. It's, you know, primarily stateless, that's probably going to, you know, change over time. All right, last question. In thinking about this Broadcom acquisition of VMware, in the macro climate, put a sort of bow on where NetApp fits into this equation. What's the value you bring in this context? >> Oh yeah, well it's like I said earlier, I think it's the data layer of, it's being the data layer that gives you what you guys call the supercloud, that gives you the ability to choose which cloud. Another thing, all customers are running at least two clouds, and you want to be able to pick and choose, and do it your way. So being the data layer, VMware is going to be in our infrastructures for at least as long as I'm in the computer business, Dave. I'm getting a little old. So maybe, you know, but "decades" I think is an easy prediction, and we plan to work with VMware very closely, along with our customers, as they extend from on-prem to hybrid cloud operations. That's where I think this will go. >> Yeah, and I think you're absolutely right. Look at the business case for migrating off of VMware. It just doesn't make sense. It works, it's world class, it recover... They've done so much amazing, you know, they used to be called, Moritz called it the software mainframe, right? And that's kind of what it is. I mean, it means it doesn't go down, right? And it supports virtually any application, you know, around the world, so. >> And I think getting back to your original point about your article, from the very beginning, is, I think Broadcom's really getting a sense of what they've bought, and it's going to be, hopefully, I think it'll be really a fun, another fun era in our business. >> Well, and you can drive EBIT a couple of ways. You can cut, okay, fine. And I'm sure there's some redundancies that they'll find. But there's also, you can drive top-line revenue. And you know, we've seen how, you know, EMC and then Dell used that growth from VMware to throw off free cash flow, and it was just, you know, funded so much, you know, innovation. So innovation is the key. Hock Tan has talked about that a lot. I think there's a perception that Broadcom, you know, doesn't invest in R & D. That's not true. I think they just get very focused with that investment. So, Phil, I really appreciate your time. Thanks so much for joining us. >> Thanks a lot, Dave. It's fun being here. >> Yeah, our pleasure. And thank you for watching theCUBE, your leader in enterprise and emerging tech coverage. (upbeat music)

(electronic music) >> Hi everybody, welcome back to Supercloud 2. I'm Dave Vellante with my co-host John Furrier. We're here at our tricked out Palo Alto studio. We're going live wall to wall all day. We're inserting a number of pre-recorded interviews, folks like Walmart. We just heard from Nir Zuk of Palo Alto Networks, and I'm really pleased to welcome in David Flynn. David Flynn, you may know as one of the people behind Fusion-io, completely changed the way in which people think about storing data, accessing data. David Flynn now the founder and CEO of a company called Hammerspace. David, good to see you, thanks for coming on. >> David: Good to see you too. >> And Dr. Nelu Mihai is the CEO and founder of Cloud of Clouds. He's actually built a Supercloud. We're going to get into that. Nelu, thanks for coming on. >> Thank you, Happy New Year. >> Yeah, Happy New Year. So I'm going to start right off with a little debate that's going on in the community if you guys would bring out this slide. So Bob Muglia early today, he gave a definition of Supercloud. He felt like we had to tighten ours up a little bit. He said a Supercloud is a platform, underscoring platform, that provides programmatically consistent services hosted on heterogeneous cloud providers. Now, Nelu, we have this shared doc, and you've been in there. You responded, you said, well, hold on. Supercloud really needs to be an architecture, or else we're going to have this stove pipe of stove pipes, really. And then you went on with more detail, what's the information model? What's the execution model? How are users going to interact with Supercloud? So I start with you, why architecture? The inference is that a platform, the platform provider's responsible for the architecture? Why does that not work in your view? >> No, the, it's a very interesting question. So whenever I think about platform, what's the connotation, you think about monolithic system? Yeah, I mean, I don't know whether it's true or or not, but there is this connotation of of monolithic. On the other hand, if you look at what's a problem right now with HyperClouds, from the customer perspective, they're very complex. There is a heterogeneous world where actually every single one of this HyperClouds has their own architecture. You need rocket scientists to build a cloud applications. Always there is this contradiction between cost and performance. They fight each other. And I'm quoting here a former friend of mine from Bell Labs who work at AWS who used to say "Cloud is cheap as long as you don't use it too much." (group chuckles) So clearly we need something that kind of plays from the principle point of view the role of an operating system, that seats on top of this heterogeneous HyperCloud, and there's nothing wrong by having these proprietary HyperClouds, think about processors, think about operating system and so on, so forth. But in order to build a system that is simple enough, I think we need to go deeper and understand. >> So the argument, the counterargument to that, David, is you'll never get there. You need a proprietary system to get to market sooner, to solve today's problem. Now I don't know where you stand on this platform versus architecture. I haven't asked you, but. >> I think there are aspects of both for sure. I mean it needs to be an architecture in the sense that it's broad based and open and so forth. But you know, platform, you could say as long as people can instantiate it themselves, on their own infrastructure, as long as it's something that can be deployed as, you know, software defined, you don't want the concept of platform being the monolith, you know, combined hardware and software. So it really depends on what you're focused on when you're saying platform, you know, I'd say as long as they software defined thing, to where it can literally run anywhere. I mean, because I really think what we're talking about here is the original concept of cloud computing. The ability to run anything anywhere, without having to care about the physical infrastructure. And what we have today is not that, the cloud today is a big mainframe in the sky, that just happens to be large enough that once you select which region, generally you have enough resources. But, you know, nowadays you don't even necessarily have enough resources in one region. and then you're kind of stuck. So we haven't really gotten to that utility model of computing. And you're also asked to rewrite your application, you know, to abandon the conveniences of high performance file access. You got to rewrite it to use object storage stuff. We have to get away from that. >> Okay, I want to just drill on that, 'cause I think I like that point about, there's not enough availability, but on the developer cloud, the original AWS premise was targeting developers, 'cause at that time, you have to provision a Sun box get a Cisco DSU/CSU, now you get on the cloud. But I think you're giving up the scale question, 'cause I think right now, scale is huge, enterprise grade versus cloud for developers. >> That's Right. >> Because I mean look at, Amazon, Azure, they got compute, they got storage, they got queuing, and some stuff. If you're doing a startup, you throw your app up there, localhost to cloud, no big deal. It's the scale thing that gets me- >> And you can tell by the fact that, in regions that are under high demand, right, like in London or LA, at least with the clients we work with in the median entertainment space, it costs twice as much for the exact same cloud instances that do the exact same amount of work, as somewhere out in rural Canada. So why is it you have such a cost differential, it has to do with that supply and demand, and the fact that the clouds aren't really the ability to run anything anywhere. Even within the same cloud vendor, you're stuck in a specific region. >> And that was never the original promise, right? I mean it was, we turned it into that. But the original promise was get rid of the heavy lifting of IT. >> Not have to run your own, yeah, exactly. >> And then it became, wow, okay I can run anywhere. And then you know, it's like web 2.0. You know people say why Supercloud, you and I talked about this, why do you need a name for Supercloud? It's like web 2.0. >> It's what Cloud was supposed to be. >> It's what cloud was supposed to be, (group laughing and talking) exactly, right. >> Cloud was supposed to be run anything anywhere, or at least that's what we took it as. But you're right, originally it was just, oh don't have to run your own infrastructure, and you can choose somebody else's infrastructure. >> And you did that >> But you're still bound to that. >> Dave: And People said I want more, right? >> But how do we go from here? >> That's, that's actually, that's a very good point, because indeed when the first HyperClouds were designed, were designed really focus on customers. I think Supercloud is an opportunity to design in the right way. Also having in mind the computer science rigor. And we should take advantage of that, because in fact actually, if cloud would've been designed properly from the beginning, probably wouldn't have needed Supercloud. >> David: You wouldn't have to have been asked to rewrite your application. >> That's correct. (group laughs) >> To use REST interfaces to your storage. >> Revisist history is always a good one. But look, cloud is great. I mean your point is cloud is a good thing. Don't hold it back. >> It is a very good thing. >> Let it continue. >> Let it go as as it is. >> Yeah, let that thing continue to grow. Don't impose restrictions on the cloud. Just refactor what you need to for scale or enterprise grade or availability. >> And you would agree with that, is that true or is it problem you're solving? >> Well yeah, I mean it, what the cloud is doing is absolutely necessary. What the public cloud vendors are doing is absolutely necessary. But what's been missing is how to provide a consistent interface, especially to persistent data. And have it be available across different regions, and across different clouds. 'cause data is a highly localized thing in current architecture. It only exists as rendered by the storage system that you put it in. Whether that's a legacy thing like a NetApp or an Isilon or even a cloud data service. It's localized to a specific region of the cloud in which you put that. We have to delocalize data, and provide a consistent interface to it across all sites. That's high performance, local access, but to global data. >> And so Walmart earlier today described their, what we call Supercloud, they call it the Walmart cloud native platform. And they use this triplet model. They have AWS and Azure, no, oh sorry, no AWS. They have Azure and GCP and then on-prem, where all the VMs live. When you, you know, probe, it turns out that it's only stateless in the cloud. (John laughs) So, the state stuff- >> Well let's just admit it, there is no such thing as stateless, because even the application binaries and libraries are state. >> Well I'm happy that I'm hearing that. >> Yeah, okay. >> Because actually I have a lot of debate (indistinct). If you think about no software running on a (indistinct) machine is stateless. >> David: Exactly. >> This is something that was- >> David: And that's data that needs to be distributed and provided consistently >> (indistinct) >> Across all the clouds, >> And actually, it's a nonsense, but- >> Dave: So it's an illusion, okay. (group talks over each other) >> (indistinct) you guys talk about stateless. >> Well, see, people make the confusion between state and persistent state, okay. Persistent state it's a different thing. State is a different thing. So, but anyway, I want to go back to your point, because there's a lot of debate here. People are talking about data, some people are talking about logic, some people are talking about networking. In my opinion is this triplet, which is data logic and connectivity, that has equal importance. And actually depending on the application, can have the center of gravity moving towards data, moving towards what I call execution units or workloads. And connectivity is actually the most important part of it. >> David: (indistinct). >> Some people are saying move the logic towards the data, some other people, and you are saying actually, that no, you have to build a distributed data mesh. What I'm saying is actually, you have to consider all these three variables, all these vector in order to decide, based on application, what's the most important. Because sometimes- >> John: So the application chooses >> That's correct. >> Well it it's what operating systems were in the past, was principally the thing that runs and manages the jobs, the job scheduler, and the thing that provides your persistent data (indistinct). >> Okay. So we finally got operating system into the equation, thank you. (group laughs) >> Nelu: I actually have a PhD in operating system. >> Cause what we're talking about is an operating system. So forget platform or architecture, it's an operating environment. Let's use it as a general term. >> All right. I think that's about it for me. >> All right, let's take (indistinct). Nelu, I want ask you quick, 'cause I want to give a, 'cause I believe it's an operating system. I think it's going to be a reset, refactored. You wrote to me, "The model of Supercloud has to be open theoretical, has to satisfy the rigors of computer science, and customer requirements." So unique to today, if the OS is going to be refactored, it's not going to be, may or may not be Red Hat or somebody else. This new OS, obviously requirements are for customers too but is what's the computer science that is needed? Where are we, what's the missing? Where's the science in this shift? It's not your standard OS it's not like an- (group talks over each other) >> I would beg to differ. >> (indistinct) truly an operation environment. But the, if you think about, and make analogies, what you need when you design a distributed system, well you need an information model, yeah. You need to figure out how the data is located and distributed. You need a model for the execution units, and you need a way to describe the interactions between all these objects. And it is my opinion that we need to go deeper and formalize these operations in order to make a step forward. And when we design Supercloud, and design something that is better than the current HyperClouds. And actually that is when we design something better, you make a system more efficient and it's going to be better from the cost point of view, from the performance point of view. But we need to add some math into all this customer focus centering and I really admire AWS and their executive team focusing on the customer. But now it's time to go back and see, if we apply some computer science, if you try to formalize to build a theoretical model of cloud, can we build a system that is better than existing ones? >> So David, how do you- >> this is what I'm saying. >> That's a good question >> How do You see the operating system of a, or operating environment of a decentralized cloud? >> Well I think it's layered. I mean we have operating systems that can run systems quite efficiently. Linux has sort of one in the data center, but we're talking about a layer on top of that. And I think we're seeing the emergence of that. For example, on the job scheduling side of things, Kubernetes makes a really good example. You know, you break the workload into the most granular units of compute, the containerized microservice, and then you use a declarative model to state what is needed and give the system the degrees of freedom that it can choose how to instantiate it. Because the thing about these distributed systems, is that the complexity explodes, right? Running a piece of hardware, running a single server is not a problem, even with all the many cores and everything like that. It's when you start adding in the networking, and making it so that you have many of them. And then when it's going across whole different data centers, you know, so, at that level the way you solve this is not manually (group laughs) and not procedurally. You have to change the language so it's intent based, it's a declarative model, and what you're stating is what is intended, and you're leaving it to more advanced techniques, like machine learning to decide how to instantiate that service across the cluster, which is what Kubernetes does, or how to instantiate the data across the diverse storage infrastructure. And that's what we do. >> So that's a very good point because actually what has been neglected with HyperClouds is really optimization and automation. But in order to be able to do both of these things, you need, I'm going back and I'm stubborn, you need to have a mathematical model, a theoretical model because what does automation mean? It means that we have to put machines to do the work instead of us, and machines work with what? Formula, with algorithms, they don't work with services. So I think Supercloud is an opportunity to underscore the importance of optimization and automation- >> Totally agree. >> In HyperCloud, and actually by doing that, we can also have an interesting connotation. We are also contributing to save our planet, because if you think right now. we're consuming a lot of energy on this HyperClouds and also all this AI applications, and I think we can do better and build the same kind of application using less energy. >> So yeah, great point, love that call out, the- you know, Dave and I always joke about the old, 'cause we're old, we talk about, you know, (Nelu Laughs) old history, OS/2 versus DOS, okay, OS's, OS/2 is silly better, first threaded OS, DOS never went away. So how does legacy play into this conversation? Because I buy the theoretical, I love the conversation. Okay, I think it's an OS, totally see it that way myself. What's the blocker? Is there a legacy that drags it back? Is the anchor dragging from legacy? Is there a DOS OS/2 moment? Is there an opportunity to flip the script? This is- >> I think that's a perfect example of why we need to support the existing interfaces, Operating Systems, real operating systems like Linux, understands how to present data, it's called a file system, block devices, things that that plumb in there. And by, you know, going to a REST interface and S3 and telling people they have to rewrite their applications, you can't even consume your application binaries that way, the OS doesn't know how to pull that sort of thing. So we, to get to cloud, to get to the ability to host massive numbers of tenants within a centralized infrastructure, you know, we abandoned these lower level interfaces to the OS and we have to go back to that. It's the reason why DOS ultimately won, is it had the momentum of the install base. We're seeing the same thing here. Whatever it is, it has to be a real file system and not a come down file system >> Nelu, what's your reaction, 'cause you're in the theoretical bandwagon. Let's get your reaction. >> No, I think it's a good, I'll give, you made a good analogy between OS/2 and DOS, but I'll go even farther saying, if you think about the evolution operating system didn't stop the evolution of underlying microprocessors, hardware, and so on and so forth. On the contrary, it was a catalyst for that. So because everybody could develop their own hardware, without worrying that the applications on top of operating system are going to modify. The same thing is going to happen with Supercloud. You're going to have the AWSs, you're going to have the Azure and the the GCP continue to evolve in their own way proprietary. But if we create on top of it the right interface >> The open, this is why open is important. >> That's correct, because actually you're going to see sometime ago, everybody was saying, remember venture capitals were saying, "AWS killed the world, nobody's going to come." Now you see what Oracle is doing, and then you're going to see other players. >> It's funny, Amazon's trying to be more like Microsoft. Microsoft's trying to be more like Amazon and Google- Oracle's just trying to say they have cloud. >> That's, that's correct, (group laughs) so, my point is, you're going to see a multiplication of this HyperClouds and cloud technology. So, the system has to be open in order to accommodate what it is and what is going to come. Okay, so it's open. >> So the the legacy- so legacy is an opportunity, not a blocker in your mind. And you see- >> That's correct, I think we should allow them to continue to to to be their own actually. But maybe you're going to find a way to connect with it. >> Amazon's the processor, and they're on the 80 80 80 right? >> That's correct. >> You're saying you love people trying to get put to work. >> That's a good analogy. >> But, performance levels you say good luck, right? >> Well yeah, we have to be able to take traditional applications, high performance applications, those that consume file system and persistent data. Those things have to be able to run anywhere. You need to be able to put, put them onto, you know, more elastic infrastructure. So, we have to actually get cloud to where it lives up to its billing. >> And that's what you're solving for, with Hammerspace, >> That's what we're solving for, making it possible- >> Give me the bumper sticker. >> Solving for how do you have massive quantities of unstructured file data? At the end of the day, all data ultimately is unstructured data. Have that persistent data available, across any data center, within any cloud, within any region on-prem, at the edge. And have not just the same APIs, but have the exact same data sets, and not sucked over a straw remote, but at extreme high performance, local access. So how do you have local access to globally shared distributed data? And that's what we're doing. We are orchestrating data globally across all different forms of storage infrastructure, so you have a consistent access at the highest performance levels, at the lowest level innate built into the OS, how to consume it as (indistinct) >> So are you going into the- all the clouds and natively building in there, or are you off cloud? >> So This is software that can run on cloud instances and provide high performance file within the cloud. It can take file data that's on-prem. Again, it's software, it can run in virtual or on physical servers. And it abstracts the data from the existing storage infrastructure, and makes the data visible and consumable and orchestratable across any of it. >> And what's the elevator pitch for Cloud of Cloud, give that too. >> Well, Cloud of Clouds creates a theoretical model of cloud, and it describes every single object in the cloud. Where is data, execution units, and connectivity, with one single class of very simple object. And I can, I can give you (indistinct) >> And the problem that solves is what? >> The problem that solves is, it creates this mathematical model that is necessary in order to do other interesting things, such as optimization, using sata engines, using automation, applying ML for instance. Or deep learning to automate all this clouds, if you think about in the industrial field, we know how to manage and automate huge plants. Why wouldn't it do the same thing in cloud? It's the same thing you- >> That's what you mean by theoretical model. >> Nelu: That's correct. >> Lay out the architecture, almost the bones of skeleton or something, or, and then- >> That's correct, and then on top of it you can actually build a platform, You can create your services, >> when you say math, you mean you put numbers to it, you kind of index it. >> You quantify this thing and you apply mathematical- It's really about, I can disclose this thing. It's really about describing the cloud as a knowledge graph for every single object in the graph for node, an edge is a vector. And then once you have this model, then you can apply the field theory, and linear algebra to do operation with these vectors. And it's, this creates a very interesting opportunity to let the math do this thing for us. >> Okay, so what happens with hyperscale, or it's like AWS in your model. >> So in, in my model actually, >> Are they happy with this, or they >> I'm very happy with that. >> Will they be happy with you? >> We create an interface to every single HyperCloud. We actually, we don't need to interface with the thousands of APIs, but you know, if we have the 80 20 rule, and we map these APIs into this graph, and then every single operation that is done in this graph is done from the beginning, in an optimized manner and also automation ready. >> That's going to be great. David, I want us to go back to you before we close real quick. You've had a lot of experience, multiple ventures on the front end. You talked to a lot of customers who've been innovating. Where are the classic (indistinct)? Cause you, you used to sell and invent product around the old school enterprises with storage, you know that that trajectory storage is still critical to store the data. Where's the classic enterprise grade mindset right now? Those customers that were buying, that are buying storage, they're in the cloud, they're lifting and shifting. They not yet put the throttle on DevOps. When they look at this Supercloud thing, Are they like a deer in the headlights, or are they like getting it? What's the, what's the classic enterprise look like? >> You're seeing people at different stages of adoption. Some folks are trying to get to the cloud, some folks are trying to repatriate from the cloud, because they've realized it's better to own than to rent when you use a lot of it. And so people are at very different stages of the journey. But the one thing that's constant is that there's always change. And the change here has to do with being able to change the location where you're doing your computing. So being able to support traditional workloads in the cloud, being able to run things at the edge, and being able to rationalize where the data ought to exist, and with a declarative model, intent-based, business objective-based, be able to swipe a mouse and have the data get redistributed and positioned across different vendors, across different clouds, that, we're seeing that as really top of mind right now, because everybody's at some point on this journey, trying to go somewhere, and it involves taking their data with them. (John laughs) >> Guys, great conversation. Thanks so much for coming on, for John, Dave. Stay tuned, we got a great analyst power panel coming right up. More from Palo Alto, Supercloud 2. Be right back. (bouncy music)

>> Narrator: From theCUBE Studios in Palo Alto and Boston bringing you data-driven insights from theCUBE and ETR. This is breaking analysis with Dave Vellante >> Enterprise tech practitioners, like most of us they want to make their lives easier so they can focus on delivering more value to their businesses. And to do so, they want to tap best of breed services in the public cloud, but at the same time connect their on-prem intellectual property to emerging applications which drive top line revenue and bottom line profits. But creating a consistent experience across clouds and on-prem estates has been an elusive capability for most organizations, forcing trade-offs and injecting friction into the system. The need to create seamless experiences is clear and the technology industry is starting to respond with platforms, architectures, and visions of what we've called the Supercloud. Hello and welcome to this week's Wikibon Cube Insights powered by ETR. In this breaking analysis we give you a preview of Supercloud 2, the second event of its kind that we've had on the topic. Yes, folks that's right Supercloud 2 is here. As of this recording, it's just about four days away 33 guests, 21 sessions, combining live discussions and fireside chats from theCUBE's Palo Alto Studio with prerecorded conversations on the future of cloud and data. You can register for free at supercloud.world. And we are super excited about the Supercloud 2 lineup of guests whereas Supercloud 22 in August, was all about refining the definition of Supercloud testing its technical feasibility and understanding various deployment models. Supercloud 2 features practitioners, technologists and analysts discussing what customers need with real-world examples of Supercloud and will expose thinking around a new breed of cross-cloud apps, data apps, if you will that change the way machines and humans interact with each other. Now the example we'd use if you think about applications today, say a CRM system, sales reps, what are they doing? They're entering data into opportunities they're choosing products they're importing contacts, et cetera. And sure the machine can then take all that data and spit out a forecast by rep, by region, by product, et cetera. But today's applications are largely about filling in forms and or codifying processes. In the future, the Supercloud community sees a new breed of applications emerging where data resides on different clouds, in different data storages, databases, Lakehouse, et cetera. And the machine uses AI to inspect the e-commerce system the inventory data, supply chain information and other systems, and puts together a plan without any human intervention whatsoever. Think about a system that orchestrates people, places and things like an Uber for business. So at Supercloud 2, you'll hear about this vision along with some of today's challenges facing practitioners. Zhamak Dehghani, the founder of Data Mesh is a headliner. Kit Colbert also is headlining. He laid out at the first Supercloud an initial architecture for what that's going to look like. That was last August. And he's going to present his most current thinking on the topic. Veronika Durgin of Sachs will be featured and talk about data sharing across clouds and you know what she needs in the future. One of the main highlights of Supercloud 2 is a dive into Walmart's Supercloud. Other featured practitioners include Western Union Ionis Pharmaceuticals, Warner Media. We've got deep, deep technology dives with folks like Bob Muglia, David Flynn Tristan Handy of DBT Labs, Nir Zuk, the founder of Palo Alto Networks focused on security. Thomas Hazel, who's going to talk about a new type of database for Supercloud. It's several analysts including Keith Townsend Maribel Lopez, George Gilbert, Sanjeev Mohan and so many more guests, we don't have time to list them all. They're all up on supercloud.world with a full agenda, so you can check that out. Now let's take a look at some of the things that we're exploring in more detail starting with the Walmart Cloud native platform, they call it WCNP. We definitely see this as a Supercloud and we dig into it with Jack Greenfield. He's the head of architecture at Walmart. Here's a quote from Jack. "WCNP is an implementation of Kubernetes for the Walmart ecosystem. We've taken Kubernetes off the shelf as open source." By the way, they do the same thing with OpenStack. "And we have integrated it with a number of foundational services that provide other aspects of our computational environment. Kubernetes off the shelf doesn't do everything." And so what Walmart chose to do, they took a do-it-yourself approach to build a Supercloud for a variety of reasons that Jack will explain, along with Walmart's so-called triplet architecture connecting on-prem, Azure and GCP. No surprise, there's no Amazon at Walmart for obvious reasons. And what they do is they create a common experience for devs across clouds. Jack is going to talk about how Walmart is evolving its Supercloud in the future. You don't want to miss that. Now, next, let's take a look at how Veronica Durgin of SAKS thinks about data sharing across clouds. Data sharing we think is a potential killer use case for Supercloud. In fact, let's hear it in Veronica's own words. Please play the clip. >> How do we talk to each other? And more importantly, how do we data share? You know, I work with data, you know this is what I do. So if you know I want to get data from a company that's using, say Google, how do we share it in a smooth way where it doesn't have to be this crazy I don't know, SFTP file moving? So that's where I think Supercloud comes to me in my mind, is like practical applications. How do we create that mesh, that network that we can easily share data with each other? >> Now data mesh is a possible architectural approach that will enable more facile data sharing and the monetization of data products. You'll hear Zhamak Dehghani live in studio talking about what standards are missing to make this vision a reality across the Supercloud. Now one of the other things that we're really excited about is digging deeper into the right approach for Supercloud adoption. And we're going to share a preview of a debate that's going on right now in the community. Bob Muglia, former CEO of Snowflake and Microsoft Exec was kind enough to spend some time looking at the community's supercloud definition and he felt that it needed to be simplified. So in near real time he came up with the following definition that we're showing here. I'll read it. "A Supercloud is a platform that provides programmatically consistent services hosted on heterogeneous cloud providers." So not only did Bob simplify the initial definition he's stressed that the Supercloud is a platform versus an architecture implying that the platform provider eg Snowflake, VMware, Databricks, Cohesity, et cetera is responsible for determining the architecture. Now interestingly in the shared Google doc that the working group uses to collaborate on the supercloud de definition, Dr. Nelu Mihai who is actually building a Supercloud responded as follows to Bob's assertion "We need to avoid creating many Supercloud platforms with their own architectures. If we do that, then we create other proprietary clouds on top of existing ones. We need to define an architecture of how Supercloud interfaces with all other clouds. What is the information model? What is the execution model and how users will interact with Supercloud?" What does this seemingly nuanced point tell us and why does it matter? Well, history suggests that de facto standards will emerge more quickly to resolve real world practitioner problems and catch on more quickly than consensus-based architectures and standards-based architectures. But in the long run, the ladder may serve customers better. So we'll be exploring this topic in more detail in Supercloud 2, and of course we'd love to hear what you think platform, architecture, both? Now one of the real technical gurus that we'll have in studio at Supercloud two is David Flynn. He's one of the people behind the the movement that enabled enterprise flash adoption, that craze. And he did that with Fusion IO and he is now working on a system to enable read write data access to any user in any application in any data center or on any cloud anywhere. So think of this company as a Supercloud enabler. Allow me to share an excerpt from a conversation David Flore and I had with David Flynn last year. He as well gave a lot of thought to the Supercloud definition and was really helpful with an opinionated point of view. He said something to us that was, we thought relevant. "What is the operating system for a decentralized cloud? The main two functions of an operating system or an operating environment are one the process scheduler and two, the file system. The strongest argument for supercloud is made when you go down to the platform layer and talk about it as an operating environment on which you can run all forms of applications." So a couple of implications here that will be exploring with David Flynn in studio. First we're inferring from his comment that he's in the platform camp where the platform owner is responsible for the architecture and there are obviously trade-offs there and benefits but we'll have to clarify that with him. And second, he's basically saying, you kill the concept the further you move up the stack. So the weak, the further you move the stack the weaker the supercloud argument becomes because it's just becoming SaaS. Now this is something we're going to explore to better understand is thinking on this, but also whether the existing notion of SaaS is changing and whether or not a new breed of Supercloud apps will emerge. Which brings us to this really interesting fellow that George Gilbert and I RIFed with ahead of Supercloud two. Tristan Handy, he's the founder and CEO of DBT Labs and he has a highly opinionated and technical mind. Here's what he said, "One of the things that we still don't know how to API-ify is concepts that live inside of your data warehouse inside of your data lake. These are core concepts that the business should be able to create applications around very easily. In fact, that's not the case because it involves a lot of data engineering pipeline and other work to make these available. So if you really want to make it easy to create these data experiences for users you need to have an ability to describe these metrics and then to turn them into APIs to make them accessible to application developers who have literally no idea how they're calculated behind the scenes and they don't need to." A lot of implications to this statement that will explore at Supercloud two versus Jamma Dani's data mesh comes into play here with her critique of hyper specialized data pipeline experts with little or no domain knowledge. Also the need for simplified self-service infrastructure which Kit Colbert is likely going to touch upon. Veronica Durgin of SAKS and her ideal state for data shearing along with Harveer Singh of Western Union. They got to deal with 200 locations around the world in data privacy issues, data sovereignty how do you share data safely? Same with Nick Taylor of Ionis Pharmaceutical. And not to blow your mind but Thomas Hazel and Bob Muglia deposit that to make data apps a reality across the Supercloud you have to rethink everything. You can't just let in memory databases and caching architectures take care of everything in a brute force manner. Rather you have to get down to really detailed levels even things like how data is laid out on disk, ie flash and think about rewriting applications for the Supercloud and the MLAI era. All of this and more at Supercloud two which wouldn't be complete without some data. So we pinged our friends from ETR Eric Bradley and Darren Bramberm to see if they had any data on Supercloud that we could tap. And so we're going to be analyzing a number of the players as well at Supercloud two. Now, many of you are familiar with this graphic here we show some of the players involved in delivering or enabling Supercloud-like capabilities. On the Y axis is spending momentum and on the horizontal accesses market presence or pervasiveness in the data. So netscore versus what they call overlap or end in the data. And the table insert shows how the dots are plotted now not to steal ETR's thunder but the first point is you really can't have supercloud without the hyperscale cloud platforms which is shown on this graphic. But the exciting aspect of Supercloud is the opportunity to build value on top of that hyperscale infrastructure. Snowflake here continues to show strong spending velocity as those Databricks, Hashi, Rubrik. VMware Tanzu, which we all put under the magnifying glass after the Broadcom announcements, is also showing momentum. Unfortunately due to a scheduling conflict we weren't able to get Red Hat on the program but they're clearly a player here. And we've put Cohesity and Veeam on the chart as well because backup is a likely use case across clouds and on-premises. And now one other call out that we drill down on at Supercloud two is CloudFlare, which actually uses the term supercloud maybe in a different way. They look at Supercloud really as you know, serverless on steroids. And so the data brains at ETR will have more to say on this topic at Supercloud two along with many others. Okay, so why should you attend Supercloud two? What's in it for me kind of thing? So first of all, if you're a practitioner and you want to understand what the possibilities are for doing cross-cloud services for monetizing data how your peers are doing data sharing, how some of your peers are actually building out a Supercloud you're going to get real world input from practitioners. If you're a technologist, you're trying to figure out various ways to solve problems around data, data sharing, cross-cloud service deployment there's going to be a number of deep technology experts that are going to share how they're doing it. We're also going to drill down with Walmart into a practical example of Supercloud with some other examples of how practitioners are dealing with cross-cloud complexity. Some of them, by the way, are kind of thrown up their hands and saying, Hey, we're going mono cloud. And we'll talk about the potential implications and dangers and risks of doing that. And also some of the benefits. You know, there's a question, right? Is Supercloud the same wine new bottle or is it truly something different that can drive substantive business value? So look, go to Supercloud.world it's January 17th at 9:00 AM Pacific. You can register for free and participate directly in the program. Okay, that's a wrap. I want to give a shout out to the Supercloud supporters. VMware has been a great partner as our anchor sponsor Chaos Search Proximo, and Alura as well. For contributing to the effort I want to thank Alex Myerson who's on production and manages the podcast. Ken Schiffman is his supporting cast as well. Kristen Martin and Cheryl Knight to help get the word out on social media and at our newsletters. And Rob Ho is our editor-in-chief over at Silicon Angle. Thank you all. Remember, these episodes are all available as podcast. Wherever you listen we really appreciate the support that you've given. We just saw some stats from from Buzz Sprout, we hit the top 25% we're almost at 400,000 downloads last year. So really appreciate your participation. All you got to do is search Breaking Analysis podcast and you'll find those I publish each week on wikibon.com and siliconangle.com. Or if you want to get ahold of me you can email me directly at David.Vellante@siliconangle.com or dm me DVellante or comment on our LinkedIn post. I want you to check out etr.ai. They've got the best survey data in the enterprise tech business. This is Dave Vellante for theCUBE Insights, powered by ETR. Thanks for watching. We'll see you next week at Supercloud two or next time on breaking analysis. (light music)

(upbeat music) >> Welcome back to Supercloud two where we're gathering a number of industry luminaries to discuss the future of cloud services. And we'll be focusing on various real world practitioners today, their challenges, their opportunities with an emphasis on data, self-service infrastructure and how organizations are evolving their data and cloud strategies to prepare for that next era of digital innovation. And we really believe that support for multiple cloud estates is a first step of any Supercloud. And in that regard Oracle surprise some folks with its Azure collaboration the Oracle database and exit database services. And to discuss the challenges of developing a mission critical Supercloud we welcome Juan Loaiza, who's the executive vice president of Mission Critical Database Technologies at Oracle. Juan, you're many time CUBE alums so welcome back to the show. Great to see you. >> Great to see you, and happy to be here with you. >> Yeah, thank you. So a lot of people felt that Oracle was resistant to multicloud strategies and preferred to really have everything run just on the Oracle cloud infrastructure, OCI and maybe that was a misperception maybe you guys were misunderstood or maybe you had to change your heart. Take us through the decision to support multiple cloud platforms >> Now we've supported multiple cloud platforms for many years, so I think that was probably a misperception. Oracle database, we partnered up with Amazon very early on in their cloud when they had kind of the the first cloud out there. And we had Oracle database running on their cloud. We have backup, we have a lot of stuff running. So, yeah, part of the philosophy of Oracle has always been we partner with every platform. We're very open we started with SQL and APIs. As we develop new technologies we push them into the SQL standard. So that's always been part of the ecosystem at Oracle. That's how we think we get an advantage by being more open. I think if we try to create this isolated little world it actually hurts us and hurts customers. So for us it's a win-win to be open across the clouds. >> So Supercloud is this concept that we put forth to describe a platform or some people think it's an architecture if you have an opinion, and I'd love to hear it but it provides a programmatically consistent set of services that hosted on heterogeneous cloud providers. And so we look at the Oracle database service for Azure as fitting within this definition. In your view, is this accurate? >> Yeah, I would broaden it. I'd see a little bit more than that. We just think that services should be available from everywhere, right? So, I mean, it's a little bit like if you go back to the pre-internet world, there was things like AOL and CompuServe and those were kind of islands. And if you were on AOL, you really didn't have access to anything on CompuServe and vice versa. And the cloud world has evolved a little bit like that. And we just think that's the wrong model. They shouldn't these clouds are part of the world and they need to be interconnected like all the rest of the world. It's been a long time with telephones internet, everything, everything's interconnected. Everything should work seamlessly together. So that's how we believe if you're running in one cloud and you're running let's say an application, one cloud you want to use a service from another cloud should be completely simple to do that. It shouldn't be, I can only use what's in AOL or CompuServe or whatever else. It should not be isolated. >> Well, we got a long way to go before that Nirvana exists but one example is the Oracle database service with Azure. So what exactly does that service provide? I'm interested in how consistent the service experience is across clouds. Did you create a purpose-built PaaS layer to achieve this common experience? Or is it off the shelf Terraform? Is there unique value in the PaaS layer? Let's dig into some of those questions. I know I just threw six at you. >> Yeah, I mean, so what this is, is what we're trying to do is very simple. Which is, for example, starting with the Oracle database we want to make that seamless to use from anywhere you're running. Whether it's on-prem, on some other cloud, anywhere else you should be able to seamlessly use the Oracle database and it should look like the internet. There's no friction. There's not a lot of hoops you got to jump just because you're trying to use a database that isn't local to you. So it's pretty straightforward. And in terms of things like Azure, it's not easy to do because all these clouds have a lot of kind of very unique technologies. So what we've done is at Oracle is we've said, "Okay we're going to make Oracle database look exactly like if it was running on Azure." That means we'll use the Azure security systems, the identity management systems, the networking, there's things like monitoring and management. So we'll push all these technologies. For example, when we have monitoring event or we have alerts we'll push those into the Azure console. So as a user, it looks to you exactly as if that Oracle database was running inside Azure. Also, the networking is a big challenge across these clouds. So we've basically made that whole thing seamless. So we create the super high bandwidth network between Azure and Oracle. We make sure that's extremely low latency, under two milliseconds round trip. It's all within the local metro region. So it's very fast, very high bandwidth, very low latency. And we take care establishing the links and making sure that it's secure and all that kind of stuff. So at a high level, it looks to you like the database is--even the look and feel of the screens. It's the Azure colors, it's the Azure buttons it's the Azure layout of the screens so it looks like you're running there and we take care of all the technical details underlying that which there's a lot which has taken a lot of work to make it work seamlessly. >> In the magic of that abstraction. Juan, does it happen at the PaaS layer? Could you take us inside that a little bit? Is there intelligence in there that helps you deal with latency or are there any kind of purpose-built functions for this service? >> You could think of it as... I mean it happens at a lot of different layers. It happens at the identity management layer, it happens at the networking layer, it happens at the database layer, it happens at the monitoring layer, at the management layer. So all those things have been integrated. So it's not one thing that you just go and do. You have to integrate all these different services together. You can access files in Azure from the Oracle database. Again, that's completely seamless. You, it's just like if it was local to our cloud you get your Azure files in your kind of S3 equivalent. So yeah, the, it's not one thing. There's a whole lot of pieces to the ecosystem. And what we've done is we've worked on each piece separately to make sure that it's completely seamless and transparent so you don't have to think about it, it just works. >> So you kind of answered my next question which is one of the technical hurdles. It sounds like the technical hurdles are that integration across the entire stack. That's the sort of architecture that you've built. What was the catalyst for this service? >> Yeah, the catalyst is just fulfilling our vision of an open cloud world. It's really like I said, Oracle, from the very beginning has been believed in open standards. Customers should be able to have choice customers should be able to use whatever they want from wherever they want. And we saw that, you know in the new world of cloud that had broken down everybody had their own authentication system management system, monitoring system networking system, configuration system. And it became very difficult. There was a lot of friction to using services across cloud. So we said, "Well, okay we can fix that." It's work, it's significant amount of work but we know how to do it and let's just go do it and make it easy for customers. >> So given Oracle is really your main focus is on mission critical workloads. You talked about this low latency network, I mean but you still have physical distances, so how are you managing that latency? What's the experience been for customers across Azure and OCI? >> Yeah, so it, it's a good point. I mean, latency can be an issue. So the good thing about clouds is we have a lot of cloud data centers. We have dozens and dozens of cloud data centers around the world. And Azure has dozens and dozens of cloud data centers. And in most cases, they're in the same metro region because there's kind of natural metro regions within each country that you want to put your cloud data centers in. So most of our data centers are actually very close to the Azure data centers. There's the kind of northern Virginia, there's London, there's Tokyo I mean, there's natural places where everybody puts their data centers Seoul et cetera. And so that's the real key. So that allows us to put a very high bandwidth and low latency network. The real problems with latency come when you're trying to go along physical distance. If you're trying to connect, you know across the Pacific or you know across the country or something like that, then you can get in trouble with latency within the same metro region. It's extremely fast. It tends to be around one, you know the highest two millisecond that's roundtrip through all the routers and connections and gateways and everything else. With everything taken into consideration, what we guarantee is it's always less than two millisecond which is a very low latency time. So that tends to not be a problem because it's extremely low latency. >> I was going to ask you less than two milliseconds. So, earlier in the program we had Jack Greenfield who runs architecture for Walmart, and he was explaining what we call their Supercloud, and it's runs across Azure, GCP, and they're on-prem. They have this thing called the triplet model. So my question to you is, are you in situations where you guaranteeing that less than two milliseconds do you have situations where you're bringing, you know Exadata Cloud, a customer on-prem to achieve that? Or is this just across clouds? >> Yeah, in this case, we're talking public cloud data center to public cloud data center. >> Oh okay. >> So add your public cloud data center to Oracle Public Cloud data center. They're in the same metro region. We set up the connections, we do all the technology to make it seamless. And from a customer point of view they don't really see the network. Also, remember that SQL is actually designed to have very low bandwidth and latency requirements. So it is a language. So you don't go to the database and say do this one little thing for me. You send it a SQL statement that can actually access lots of data while in the database. So the real latency requirement of a SQL database is within the database. So I need to access all that data fast. So I need very fast access to storage very fast access across node. That's what exit data gives you. But you send one request and that request can do a huge amount of work and then return one answer. And that's kind of the design point of SQL. So SQL is inherently low bandwidth requirements, it was used back in the eighties when we used to have 10 megabit networks and the the biggest companies in the world ran back then. So right now we're talking over hundred hundreds of gigabits. So it's really not much of a challenge. When you're designed to run on 10 megabit to say, okay I'm going to give you 10,000 times what you were designed for it's really, it's a pretty low hurdle jump. >> What about the deployment models? How do you handle this? Is it a single global instance across clouds or do you sort of instantiate in each you got exudate in Azure and exudates in OCI? What's the deployment model look like? >> It's pretty straightforward. So customer decides where they want to run their application and database. So there's natural places where people go. If you're in Tokyo, you're going to choose the local Tokyo data centers for both, you know Microsoft and Oracle. If you're in London, you're going to do that. If you're in California you're going to choose maybe San Jose, something like that. So a customer just chooses. We both have data centers in that metro region. So they create their service on Azure and then they go to our console which looks just like an Azure console and say all right create me a database. And then we choose the closest Oracle data center which is generally a few miles away, and then it it all gets created. So from a customer point of view, it's very straightforward. >> I'm always in awe about how simple you make things sound. All right what about security? You talked a little bit before about identity access how you sort of abstracting the Azure capabilities away so that you've simplified it for your customers but are there any other specific security things that you need to do? How much did you have to abstract the underlying primitives of Azure or OCI to present that common experience to customers? >> Yeah, so there's really two big things. One is the identity management. Like my name is X on Azure and I have this set of privileges. Oracle has its own identity management system, right? So what we didn't want is that you have to kind of like bridge these things yourself. It's a giant pain to do that. So we actually what we call federate across these identity managements. So you put your credentials into Azure and then they automatically get to use the exact same credentials and identity in the Oracle cloud. So again, you don't have to think about it, it just works. And then the second part is that the whole bridging the network. So within a cloud you generally have virtual network that's private to your company. And so at Oracle, we bridge the private network that you created in, for example, Azure to the private network that we create for you in Oracle. So it is still a private network without you having to do a whole bunch of work. So it's just like if you were in your own data center other people can't get into your network. So it's secured at the network level, it's secured at the identity management, and encryption level. And again we did a lot of work to make that seamless for customers and they don't have to worry about it because we did the work. That's really as simple as it gets. >> That's what's Supercloud's supposed to be all about. Alright, we were talking earlier about sort of the misperception around multicloud, your view of Open I think, which is you run the Oracle database, wherever the customer wants to run it. So you got this database service across OCI and Azure customers today, they run Oracle database in AWS. You got heat wave, MySQL, heat wave that you announced on AWS, Google touts a bare metal offering where you can run Oracle on GCP. Do you see a day when you extend an OCI Azure like situation across multiple clouds? Would that bring benefits to customers or will the world of database generally remain largely fenced with maybe a few exceptions like what you're doing with OCI and Azure? I'm particularly interested in your thoughts on egress fees as maybe one of the reasons that there is a barrier to this happening and why maybe these stove pipes, exist today and in the future. What are your thoughts on that? >> Yeah, we're very open to working with everyone else out there. Like I said, we've always been, big believers in customers should have choice and you should be able to run wherever you want. So that's been kind of a founding principle of Oracle. We have the Azure, we did a partnership with them, we're open to doing other partnerships and you're going to see other things coming down the pipe on the topic of egress. Yeah, the large egress fees, it's pretty obvious what goes on with that. Various vendors like to have large egress fees because they want to keep things kind of locked into their cloud. So it's not a very customer friendly thing to do. And I think everybody recognizes that it's really trying to kind of course or put a lot of friction on moving data out of a particular cloud. And that's not what we do. We have very, very low egress fees. So we don't really do that and we don't think anybody else should do that. But I think customers at the end of the day, will win that battle. They're going to have to go back to their vendor and say, well I have choice in clouds and if you're going to impose these limits on me, maybe I'll make a different choice. So that's ultimately how these things get resolved. >> So do you think other cloud providers are going to take a page out of what you're doing with Azure and provide similar solutions? >> Yeah, well I think customers want, I mean, I've talked to a lot of customers, this is what they want, right? I mean, there's really no doubt no customer wants to be locked into a single ecosystem. There's nobody out there that wants that. And as the competition, when they start seeing an open ecosystem evolving they're going to be like, okay, I'd rather go there than the closed ecosystem, and that's going to put pressure on the closed ecosystems. So that's the nature of competition. That's what ultimately will tip the balance on these things. >> So Juan, even though you have this capability of distributing a workload across multiple clouds as in our Supercloud premise it's still something that's relatively new. It's a big decision that maybe many people might consider somewhat of a risk. So I'm curious who's driving the decisions for your initial customers? What do they want to get out of it? What's the decision point there? >> Yeah, I mean, this is generally driven by customers that want a specific technology in a cloud. I think the risk, I haven't seen a lot of people worry too much about the risk. Everybody involved in this is a very well known, very reputable firm. I mean, Oracle's been around for 40 years. We run most of the world's largest companies. I think customers understand we're not going to build a solution that's going to put their technology and their business at risk. And the same thing with Azure and others. So I don't see customers too worried about this is a risky move because it's really not. And you know, everybody understands networking at the end the day networking works. I mean, how does the internet work? It's a known quantity. It's not like it's some brand new invention. What we're really doing is breaking down the barriers to interconnecting things. Automating 'em, making 'em easy. So there's not a whole lot of risk here for customers. And like I said, every single customer in the world loves an open ecosystem. It's just not a question. If you go to a customer would you rather put your technology or your business to run on a closed ecosystem or an open system? It's kind of not even worth asking a question. It's a no-brainer. >> All right, so we got to go. My last question. What do you think of the term "Supercloud"? You think it'll stick? >> We'll see. There's a lot of terms out there and it's always fun to see which terms stick. It's a cool term. I like it, but the decision makers are actually the public, what sticks and what doesn't. It's very hard to predict. >> Yeah well, it's been a lot of fun having you on, Juan. Really appreciate your time and always good to see you. >> All right, Dave, thanks a lot. It's always fun to talk to you. >> You bet. All right, keep it right there. More Supercloud two content from theCUBE Community Dave Vellante for John Furrier. We'll be right back. (upbeat music)