(upbeat music) >> Okay, welcome back everyone. The cube coverage of AWS re:Mars, 2022. I'm John Furrier, host of theCUBE. We got Eric Foellmer, vice president of marketing at Boston Dynamics. Famous for Spot. We all know, we've seen the videos, zillion views. Mega views all over the internet. The dog robotics, it's famous. Rolls over, bounces up and down. I mean, how many TikTok videos are out there? Probably a ton. >> Oh, Spot is- Spot is world famous (John laughs) at this point, right? So it's the dance videos, and all the application videos that we have out there. Spot is become has become world famous. >> Eric, thanks for joining us on theCUBE here at re:Mars. This show really is back. There was still a pandemic hiatus there. But it's not a part of the re's. It's re Mars, reinforcement of security, and then reinvent the flagship show for AWS. But this show is different. It brings together a lot of disciplines. But it's converging in on what we see as the next general- Industrial space is a big poster child for that. Obviously in space, it's highly industrial, highly secure. Machine learning's powering all the devices. You guys have been in this, I mean a leader, in a robotics area. What's this show about? I mean, what's really happening here. What if you had to boil the essence of the top story of what's happening here? What would it be? >> So the way that I look at this show is it really is a convergence of innovation. Like this is really just the cutting edge of the innovation that's really happening throughout robotics, but throughout technology in general. And you know, part of this cultural shift will be to adopt these types of technologies in our everyday life. And I think if you ask any technology specialist here or any innovator here or entrepreneur. They'll tell you that they want their technologies to become ubiquitous in society, right? I mean, that's really what everyone is sort of driving towards from the perspective of- >> And we, and we got some company behind it. Look at this. >> Oh, there we go. >> All right. >> There's a (Eric laughs) There's one of our Spots. >> It's got one of those back there. All right so sorry to interrupt, got a little distracted by the beautiful thing there. >> So they're literally walking around and literally engulfing the show. So when I look at the show, that's what I see. >> Let's see the picture of- >> I see the future of technology. >> Get a camera on our photo bomb here going on. Get a photo bomb action. (Eric chuckles) It's just super exciting because it really, it humanizes, it makes you- Everyone loves dogs. And, you know, I mean, people have more empathy if you kicked Spot than, you know, a human. Because there's so much empathy for just the innovation. But let's get into the innovation because let's- The IOT tech scene has been slow. Cloud computing Amazon web services, the leader hyper scaler. They dominated the back office you know, data centers, all the servers, digital transformation. Now that's coming to the edge. Where robotics is now in play. Space, material handling, devices for helping people who are sick or in healthcare. >> Eric: Mhm. >> So a whole surge of revolutionary or transitionary technologies coming. What's your take on that? >> So I think, you know, data has become the driving force behind technology innovation. And so robotics are an enabler for the tech, for the data collection that is going to drive IOT and manufacturing 4.0 and other important edge related and, you know, futuristic technology innovations, right? So the driver of all of that is data. And so robots like Spot are collectors of data. And so instead of trying to retrofit a manufacturing plant, you know, with 30, 40, 50 year old equipment in some cases. With IOT sensors and, you know, fixed sensors throughout the network. We're bringing the sensors to the equipment in the form of an agile mobile robot that brings that technology forward and is able to assess. >> So explain that a little slower for me. So the one method would be retrofitting all the devices. Or the hardware currently installed. >> Eric: Sure. >> Versus almost like having a mobile unit next to it, kind of thing. Or- >> Right. So, I mean, if you're looking at antiquated equipment which is what most, you know, manufacturing plants are running off of. It's not really practical or feasible to update them with fixed sensors. So sensors that specifically take measurements from that machine. So, we enable Spot with a variety of sensors from audio sensors to listen for audio anomalies. Thermal detectors, to look for thermal hotspots in equipment. Or visual detectors, where it's reading analog gauges, that sort of thing. So by doing that, we are bringing the sensors to the machines. >> Yeah. >> And to be able to walk anywhere where a human can walk throughout a manufacturing plant. To inspect the equipment, take that reading. And then most importantly upload that to the cloud, to the users >> It's a service dog. >> you can apply some- >> It's a service dog. >> It really is. And it serves data for the understanding of how that equipment is operated. >> This is big agility for the customer. Get that data, agile. Talk about the cost impact of that, just alone. What the alternative would be versus say, deploying that scenario. Because I'd imagine the time and cost would be huge. >> Well, if you think, you know, about how much manufacturing facilities put into the predictive maintenance and being able to forecast when their equipment needs maintenance. But also when pieces of equipment are going to fail. Unexpected downtime is one of the biggest money drains of any manufacturing facility. So the ability to be able to forecast and get some insight into when that equipment is starting to perform less than optimally and start to degrade. The ability to forecast that in advance is massive. >> Well I think you just win on just in retrofit cost alone, nevermind the downside scenarios of manufacturing problems. All right, let's zoom out. You guys have been pioneers for a long time. What's changed in your mind now versus just a few years ago. I mean, look at even 5, 10 years ago. The evolution, cost and capability. What's changed the most? >> Yeah, I think the accessibility of robots has really changed. And we're just on the beginning stages of that evolution. We really are. We're at the precipice right now of robots becoming much more ubiquitous in people's lives. And that's really our foundation as a company. Is we really want to bring robots to mankind for the good of humanity, right? So if you think about, you know, taking humans out of harm's way. Or, you know, putting robots in situations where, you know, where it's assessing damage for a building, for example, right. You're taking people out of the, out of that harm's way and really standardizing what you're able to do with technology. So we see it as really being on the very entry point of having not only robotics, but technology in general to become much more prevalent in people's lives. >> Yeah. >> I mean, what, you know. 30 years ago, did you ever think that you would have the power of a supercomputer in your pocket to, you know. Which also happens to allow you to talk to people but it is so much more, right? So the power of a cell phone has changed our lives forever. >> A computer that happens to be a phone. You know, it's like, come on. >> Right. >> What's going on with that. >> That's almost secondary at this point. (John laughing) It really is. So, I mean, when you think about that transition from you know, I think we're at the cusp of that right now. We're at the beginning stages of it. And it's really, it's an exciting time to be part of this. An entire industry. >> Before I get your views on integration and scale. Because that's the next level. We're seeing a lot of action and growth. Talk about the use case. You've mentioned a few of them, take people out of harms way. What have you guys seen as use cases within Boston Dynamics customer base and or your partner network around use cases. That either you knew would happen, or ones that might have surprised you? >> Yeah. One of the biggest use cases for us right now is what we're demonstrating here at re:MARS. Which is the ability to walk through a manufacturing plant and collect data off various pieces of equipment. Whether that's pump or a gauge or seeing whether a valve is open or closed. These are all simple mundane tasks that people are, that manufacturers are having difficulty finding people to be able to perform. So the ability for a robot to go over and do that and standardize that process is really valuable. As companies are trying to collect that data in a consistent way. So that's one of the most prevalent use cases that we're seeing right now. And certainly also in cases where, you know, Spot is going into buildings that have been structurally damaged. Or, you know, assessing situations where we don't want people to be in harm's way. >> John: Yeah. >> You know- >> Bomb scares, or any kind of situation with police or, you know, threatening or danger situations. >> Sure. And fire departments as well. I mean, fire departments are becoming a huge, you know, a huge user of the robots themselves. Fire department in New York recently just adopted some of our robots as well. For that purpose, for search and rescue applications. >> Yeah. Go in, go see what's in there. See what's around the corner. It gives a very tactical edge capability for say the firefighter or law enforcement. I see that- I see the military applications must be really insane. >> Sure. From a search and rescue perspective. Absolutely. I mean, Spot helps you put eyes on situations that will allow a human to be operating at a safe distance. So it's really a great value for protecting human life and making sure that people stay out of harm's way. >> Well Eric, I really appreciate you coming on theCUBE and sharing your insight. One other question I'd like to ask if you don't mind is, you know. The one of the things I see next to your booth is the university piece. And then you see the Amazon, you know, material management. I don't know what to call it, but it's pretty impressive. And then I saw some of the demos on the keynotes. Looking at the scale of synthetic data. Just it's mind blowing what's going on in manufacturing. Amazon is pretty state of the art. I'm sure there are a customer of yours already. But they look complex these manufacturing sites. I mean, it looks like a maze. So how do you... I mean, I could see the consequences of something breaking, to be catastrophic. Because it's almost like, it's so integrated. Is this where you guys see success and how do these manufacturers deal with this? What's the... Is it like one big OS? >> Yeah, so the robots, because the robots are able to act independently. They can traverse difficult terrain and collect data on their own. And then, you know, what happens to that data afterwards is really up to the manufacturing. It can be delivered from the cloud and you can, it can be delivered via the edge. You know, edge devices and really that's where some of the exciting work is being done right now. Because that's where data can scale. And that's where robot deployments can scale as well, right? So you've got instead of a single robot. Now you have an operator deploying multiple robots. Monitoring, controlling, and assessing the data from multiple robots throughout a facility. And it really helps to scale that investment. >> All right, final question for you. This is personal question. Okay, I know- Saw your booth over there. And you have a lot of fan base. Spot's got a huge fan base. What are some of the crazy things that these nerd fans do? I mean, everyone get selfies with the Spot. They want to- I jump over the fence. I see, "Don't touch the dog." signs everywhere. The fan base is off the charts. What are the crazy things that people do to get either access to it. There's probably, been probably some theft, probably. Attempts, or selfies. Share some funny stories. >> I'll say this. My team is responsible for fielding a lot of the inbound inquiries that we get. Much of which comes from the entertainment industry. And as you've seen Spot has been featured in some really prominent, you know, entertainment pieces. You know, we were in that Super Bowl ad with Sam Adams. We were on Jimmy Kimmel, you know, during the Super Bowl time period. So the amount of entertainment... >> Value >> Pitches. Or the amount of entertainment value is immeasurable. But the number of pitches that we turn down is staggering. And when you can think about how most companies would probably pull out all the stops to take, you know. To be able to execute half the things that we're just, from a time perspective, from a resource perspective >> Okay, so Spots an A- not always able to do. >> So Spots an A-lister, I get that. Is there a B-lister now? I mean, that sounds like there's a market developing for Spot two. Is there a Spot two? The B player coming in? Understudy? >> So, I mean, Spot is always evolving. I think, you know, the physical- the physical statue that you see of Spot right now, Is where we're going to be in terms of the hardware, but we continue to move the robot forward. It becomes more and more advanced and more and more capable to do more and more things for people. So. >> All right. Well, we'll roll some B roll on this, on theCUBE. Thanks for coming on theCUBE. Really appreciate it. Boston Dynamics here in theCUBE, famous for Spot. And then here, the show packed here in re:MARS featuring, you know, robotics. It's a big feature hall. It's a set piece here in the show floor. And of course theCUBE's covering it. Thanks for watching. More coverage. I'm John Furrier, your host. After the short break. (upbeat music)

Hi, I'm Hideo Mabuchi from Stanford University. This is my presentation on coherent nonlinear dynamics, and combinatorial optimization. This is going to be a talk, to introduce an approach, we are taking to the analysis, of the performance of Coherent Ising Machines. So let me start with a brief introduction, to ising optimization. The ising model, represents a set of interacting magnetic moments or spins, with total energy given by the expression, shown at the bottom left of the slide. Here the cigna variables are meant to take binary values. The matrix element jij, represents the interaction, strength and sign, between any pair of spins ij, and hi represents a possible local magnetic field, acting on each thing. The ising ground state problem, is defined in an assignment of binary spin values, that achieves the lowest possible value of total energy. And an instance of the easing problem, is specified by given numerical values, for the matrix j and vector h, although the ising model originates in physics, we understand the ground state problem, to correspond to what would be called, quadratic binary optimization, in the field of operations research. And in fact, in terms of computational complexity theory, it can be established that the, ising ground state problem is NP complete. Qualitatively speaking, this makes the ising problem, a representative sort of hard optimization problem, for which it is expected, that the runtime required by any computational algorithm, to find exact solutions, should asyntonically scale, exponentially with the number of spins, and four worst case instances at each end. Of course, there's no reason to believe that, the problem instances that actually arise, in practical optimization scenarios, are going to be worst case instances. And it's also not generally the case, in practical optimization scenarios, that we demand absolute optimum solutions. Usually we're more interested in, just getting the best solution we can, within an affordable cost, where costs may be measured in terms of time, service fees and or energy required for computation. This focus is great interest on, so-called heuristic algorithms, for the ising problem and other NP complete problems, which generally get very good, but not guaranteed optimum solutions, and run much faster than algorithms, that are designed to find absolute Optima. To get some feeling for present day numbers, we can consider the famous traveling salesman problem, for which extensive compilations, of benchmarking data may be found online. A recent study found that, the best known TSP solver required median runtimes, across a library of problem instances, that scaled as a very steep route exponential, for an up to approximately 4,500. This gives some indication of the change, in runtime scaling for generic, as opposed to worst case problem instances. Some of the instances considered in this study, were taken from a public library of TSPs, derived from real world VLSI design data. This VLSI TSP library, includes instances within ranging from 131 to 744,710, instances from this library within between 6,880 and 13,584, were first solved just a few years ago, in 2017 requiring days of runtime, and a 48 core two gigahertz cluster, all instances with n greater than or equal to 14,233, remain unsolved exactly by any means. Approximate solutions however, have been found by heuristic methods, for all instances in the VLSI TSP library, with, for example, a solution within 0.014% of a known lower bound, having been discovered for an instance, with n equal 19,289, requiring approximately two days of runtime, on a single quarter at 2.4 gigahertz. Now, if we simple-minded the extrapolate, the route exponential scaling, from the study yet to n equal 4,500, we might expect that an exact solver, would require something more like a year of runtime, on the 48 core cluster, used for the n equals 13,580 for instance, which shows how much, a very small concession on the quality of the solution, makes it possible to tackle much larger instances, with much lower costs, at the extreme end, the largest TSP ever solved exactly has n equal 85,900. This is an instance derived from 1980s VLSI design, and this required 136 CPU years of computation, normalized to a single core, 2.4 gigahertz. But the 20 fold larger, so-called world TSP benchmark instance, with n equals 1,904,711, has been solved approximately, with an optimality gap bounded below 0.0474%. Coming back to the general practical concerns, of applied optimization. We may note that a recent meta study, analyze the performance of no fewer than, 37 heuristic algorithms for MaxCut, and quadratic binary optimization problems. And find the performance... Sorry, and found that a different heuristics, work best for different problem instances, selected from a large scale heterogeneous test bed, with some evidence, the cryptic structure, in terms of what types of problem instances, were best solved by any given heuristic. Indeed, there are reasons to believe, that these results for MaxCut, and quadratic binary optimization, reflect to general principle, of a performance complementarity, among heuristic optimization algorithms, and the practice of solving hard optimization problems. There thus arises the critical pre processing issue, of trying to guess, which of a number of available, good heuristic algorithms should be chosen, to tackle a given problem instance. Assuming that any one of them, would incur high cost to run, on a large problem of incidents, making an astute choice of heuristic, is a crucial part of maximizing overall performance. Unfortunately, we still have very little conceptual insight, about what makes a specific problem instance, good or bad for any given heuristic optimization algorithm. This is certainly pinpointed by researchers in the field, as a circumstance and must be addressed. So adding this all up, we see that a critical frontier, for cutting edge academic research involves, both the development of novel heuristic algorithms, that deliver better performance with lower costs, on classes of problem instances, that are underserved by existing approaches, as well as fundamental research, to provide deep conceptual insight, into what makes a given problem instance, easy or hard for such algorithms. In fact, these days, as we talk about the end of Moore's law, and speculate about a so-called second quantum revolution, it's natural to talk not only about novel algorithms, for conventional CPUs, but also about highly customized, special purpose hardware architectures, on which we may run entirely unconventional algorithms, for common tutorial optimizations, such as ising problem. So against that backdrop, I'd like to use my remaining time, to introduce our work on, analysis of coherent using machine architectures, and associated optimization algorithms. Ising machines in general, are a novel class of information processing architectures, for solving combinatorial optimization problems, by embedding them in the dynamics, of analog, physical, or a cyber-physical systems. In contrast to both more traditional engineering approaches, that build ising machines using conventional electronics, and more radical proposals, that would require large scale quantum entanglement the emerging paradigm of coherent ising machines, leverages coherent nominal dynamics, in photonic or optical electronic platforms, to enable near term construction, of large scale prototypes, that leverage posting as information dynamics. The general structure of current of current CIM systems, as shown in the figure on the right, the role of the easing spins, is played by a train of optical pulses, circulating around a fiber optical storage ring, that beam splitter inserted in the ring, is used to periodically sample, the amplitude of every optical pulse. And the measurement results, are continually read into an FPGA, which uses then to compute perturbations, to be applied to each pulse, by a synchronized optical injections. These perturbations are engineered to implement, the spin-spin coupling and local magnetic field terms, of the ising hamiltonian, corresponding to a linear part of the CIM dynamics. Asynchronously pumped parametric amplifier, denoted here as PPL and wave guide, adds a crucial nonlinear component, to the CIM dynamics as well. And the basic CIM algorithm, the pump power starts very low, and is gradually increased, at low pump powers, the amplitudes of the easing spin pulses, behave as continuous complex variables, whose real parts which can be positive or negative, by the role of soft or perhaps mean field spins. Once the pump power crosses the threshold, for perimetric self oscillation in the optical fiber ring, however, the amplitudes of the easing spin pulses, become effectively quantized into binary values, while the pump power is being ramped up, the FPGA subsystem continuously applies, its measurement based feedback implementation, of the using hamiltonian terms. The interplay of the linearized easing dynamics, implemented by the FPGA , and the thresholds quantization dynamics, provided by the sink pumped parametric amplifier, result in a final state, of the optical plus amplitudes, at the end of the pump ramp, that can be read as a binary strain, giving a proposed solution, of the ising ground state problem. This method of solving ising problems, seems quite different from a conventional algorithm, that runs entirely on a digital computer. As a crucial aspect, of the computation is performed physically, by the analog continuous coherent nonlinear dynamics, of the optical degrees of freedom, in our efforts to analyze CA and performance. We have therefore turn to dynamical systems theory. Namely a study of bifurcations, the evolution of critical points, and typologies of heteroclitic orbits, and basins of attraction. We conjecture that such analysis, can provide fundamental insight, into what makes certain optimization instances, hard or easy for coherent ising machines, and hope that our approach, can lead to both improvements of the course CIM algorithm, and the pre processing rubric, for rapidly assessing the CIM insuibility of the instances. To provide a bit of intuition about how this all works. It may help to consider the threshold dynamics, of just one or two optical parametric oscillators, in the CIM architecture just described. We can think of each of the pulse time slots, circulating around the fiber ring, as are presenting an independent OPO. We can think of a single OPO degree of freedom, as a single resonant optical mode, that experiences linear dissipation, due to coupling loss, and gain in a pump near crystal, as shown in the diagram on the upper left of the slide, as the pump power is increased from zero. As in the CIM algorithm, the non-linear gain is initially too low, to overcome linear dissipation. And the OPO field remains in a near vacuum state, at a critical threshold value, gain equals dissipation, and the OPO undergoes a sort of lasing transition. And the steady States of the OPO, above this threshold are essentially coherent States. There are actually two possible values, of the OPO coherent amplitude, and any given above threshold pump power, which are equal in magnitude, but opposite in phase, when the OPO cross this threshold, it basically chooses one of the two possible phases, randomly, resulting in the generation, of a single bit of information. If we consider two uncoupled OPOs, as shown in the upper right diagram, pumped at exactly the same power at all times, then as the pump power is increased through threshold, each OPO will independently choose a phase, and thus two random bits are generated, for any number of uncoupled OPOs, the threshold power per OPOs is unchanged, from the single OPO case. Now, however, consider a scenario, in which the two appeals are coupled to each other, by a mutual injection of their out coupled fields, as shown in the diagram on the lower right. One can imagine that, depending on the sign of the coupling parameter alpha, when one OPO is lasing, it will inject a perturbation into the other, that may interfere either constructively or destructively, with the field that it is trying to generate, via its own lasing process. As a result, when can easily show that for alpha positive, there's an effective ferromagnetic coupling, between the two OPO fields, and their collective oscillation threshold, is lowered from that of the independent OPO case, but only for the two collective oscillation modes, in which the two OPO phases are the same. For alpha negative, the collective oscillation threshold, is lowered only for the configurations, in which the OPO phases are opposite. So then looking at how alpha is related to the jij matrix, of the ising spin coupling hamilitonian, it follows the, we could use this simplistic to OPO CIM, to solve the ground state problem, of the ferromagnetic or antiferromagnetic angles, to ising model, simply by increasing the pump power, from zero and observing what phase relation occurs, as the two appeals first start to lase. Clearly we can imagine generalizing the story to larger, and, however, the story doesn't stay as clean and simple, for all larger problem instances. And to find a more complicated example, we only need to go to n equals four, for some choices of jij for n equals four, the story remains simple, like the n equals two case. The figure on the upper left of this slide, shows the energy of various critical points, for a non frustrated n equals for instance, in which the first bifurcated critical point, that is the one that, by forgets of the lowest pump value a, this first bifurcated critical point, flows asyntonically into the lowest energy using solution, and the figure on the upper right, however, the first bifurcated critical point, flows to a very good, but suboptimal minimum at large pump power. The global minimum is actually given, by a distinct critical point. The first appears at a higher pump power, and is not needed radically connected to the origin. The basic CIM algorithm, is this not able to find this global minimum, such non-ideal behavior, seems to become more common at margin end, for the n equals 20 instance show in the lower plots, where the lower right pod is just a zoom into, a region of the lower left block. It can be seen that the global minimum, corresponds to a critical point, that first appears that of pump parameter a around 0.16, at some distance from the adriatic trajectory of the origin. That's curious to note that, in both of these small and examples, however, the critical point corresponding to the global minimum, appears relatively close, to the adiabatic trajectory of the origin, as compared to the most of the other, local minimum that appear. We're currently working to characterise, the face portrait typology, between the global minimum, and the adiabatic trajectory of the origin, taking clues as to how the basic CIM algorithm, could be generalized, to search for non-adiabatic trajectories, that jumped to the global minimum, during the pump up, of course, n equals 20 is still too small, to be of interest for practical optimization applications. But the advantage of beginning, with the study of small instances, is that we're able to reliably to determine, their global minima, and to see how they relate to the idea, that trajectory of the origin, and the basic CIM algorithm. And the small land limit, We can also analyze, for the quantum mechanical models of CAM dynamics, but that's a topic for future talks. Existing large-scale prototypes, are pushing into the range of, n equals, 10 to the four, 10 to the five, 10 to the six. So our ultimate objective in theoretical analysis, really has to be, to try to say something about CAM dynamics, and regime of much larger in. Our initial approach to characterizing CAM behavior, in the large end regime, relies on the use of random matrix theory. And this connects to prior research on spin classes, SK models, and the tap equations, et cetera, at present we're focusing on, statistical characterization, of the CIM gradient descent landscape, including the evolution of critical points, And their value spectra, as the pump powers gradually increase. We're investigating, for example, whether there could be some way, to explain differences in the relative stability, of the global minimum versus other local minima. We're also working to understand the deleterious, or potentially beneficial effects, of non-ideologies such as asymmetry, in the implemented using couplings, looking one step ahead, we plan to move next into the direction, of considering more realistic classes of problem instances, such as quadratic binary optimization with constraints. So in closing I should acknowledge, people who did the hard work, on these things that I've shown. So my group, including graduate students, Edwin Ng, Daniel Wennberg, Ryatatsu Yanagimoto, and Atsushi Yamamura have been working, in close collaboration with, Surya Ganguli, Marty Fejer and Amir Safavi-Naeini. All of us within the department of applied physics, at Stanford university and also in collaboration with Yoshihisa Yamamoto, over at NTT-PHI research labs. And I should acknowledge funding support, from the NSF by the Coherent Ising Machines, expedition in computing, also from NTT-PHI research labs, army research office, and ExxonMobil. That's it. Thanks very much.

>> Live from Las Vegas, it's theCUBE. Covering Adobe Summit 2019. Brought to you by Accenture Interactive. >> Welcome back everyone to our live coverage, CUBE coverage here in Las Vegas for Adobe Summit 2019. I'm John Furrier, my cohost Jeff Frick, our next guest Mishel Justesen, Group Manager, Dynamics 365 and Marketing Technology at Avanade. Welcome to theCUBE, thanks for joining us. >> Thank you, thank you for having me. >> So we were just talking before you came on camera that you're in charge of Global Marketing Practice for Avanade. >> Yeah, so I'm what you called a Global Marketing COP Lead at Avanade and so basically what that means is I'm in charge of our marketing technology community, our marketing technology community at Avanade. >> A lot of relationships forming in the industry, a lot of discussions around open data, open APIs. How has the landscape shifted in the marketing technology realm over the past three years? Because you're seeing a lot of cloud computing like vibe going on, you're seeing agility, real time, AI themes kind of creeping into content development marketing. >> Yes, yes. >> It's changed a lot, how do you see it? >> It has changed a lot and I've been in the marketing technology industry before Marketing Technologist even existed. So I've seen a lot of change and I think the thing that I'm most excited about is the way I'm looking at things right now is as a Marketing Technologist, you don't have to integrate anything anymore. You can put your data in the cloud and marketers have a specific need for a specific type of data, right? So I don't have to integrate my marketing technology anymore, I can put that data in the cloud, I can enable it with some AI, and then I can send it wherever I need to go. >> So data's been the big flashpoint, in terms of inflection point and changing the direction of the industry, it's how people are handling their data and the thinking around it almost is from an architecture standpoint or use cases. What are the key trends there around the data? What are the big moving parts? >> Well, I mean one of the things that's always a pain point for marketers is all of those data silos that happen from all the different marketing tools that you'll have to use, right? So it's painful, so how do you report on that, what do you do, right? So what I really love is I love seeing how as markers, we can now put data into a single source of truth, along with all the other data that we can use to enable our reporting. For me, as a marketer, I've always wanted to be able to get access to my ERP data so I can really see the ROI on my campaigns and how they're actually doing. And if I can marry that up with the sales data as well and I can pull all that data from one place, I'm a happy camper. >> I got to ask you about being a marketing technologist because also we've been doing theCUBEs, our tenth year, covering thousands of events we've done over the years. First time ever, someone yesterday came on, a guest, and their title was Marketing CIO. >> Wow, that's fabulous. >> And we think that's going to be a big spring but it brings up the conversation of what does IT do, what does systems people do, because the notion of systems and data is not so much just in IT, information technology department problem or opportunity. There's new roles changing and coming together. How do you, what's your take on-- >> I thought you were going to ask me hard questions, this is an easy one, right? (chuckling) >> We'll get to the hard ones later. >> Okay good, so what I've found is really interesting is the transformation of the IT department versus the Marketing IT department, right? So IT has always spoken a certain language, right? But marketing and the marketing lingo, it requires a certain amount of expertise and when you have marketing technology you need to understand the lingo of marketing and what type of data and what kind of strategies to go after. You can't expect an IT department to understand that. So that's why you're seeing a Marketing CIO, because they speak the language of technology, right, Marketing Technologists, marketing technology, and they understand how to implement that technology. So that's where there's a nice shift in that going on, I love to hear this. >> Okay so now the hard question. >> Okay. >> So all the people that are here with Adobe, Adobe's got an ecosystem, you're in it, Accenture Interactive, everyone else, they're out there to try to sell services and products and experiences to the customer, the consumer, or B to B brands. Who's their buyer now? Who actually, who are they selling to? Is the personas the same, who is the person who writes the checks and makes the decision? >> The CMO. >> CMO? >> The Marketing CIO, right? (John laughing) I actually look at that from a different angle, personally. What I am after is actually the marketing team, right? So of course as marketers we understand what the customer journey is, right? And we have to be able to, as marketers, I'm putting myself in that persona of course, right? As marketers we have to make sure that we can get to those potential customers, right? But one thing that I'd like to just bring up, if I may, is that I'm more concerned about how does the marketer get their job done, right? So for me, at Avanade, I'm super excited about how I can help them get their job done better. So there's two markets there now. >> Yeah, yeah, and the roles are changing radically-- >> They totally do. >> You're seeing a lot of new things happening. >> So Mishel, curious to get your take, you've been at this for a while, how things have changed from kind of everything lining up in a funnel type situation to get to the sale, to now the sale is just part of an ongoing relationship-- >> It's a part of an ongoing experience-- >> That people are trying to establish so how does that change kind of the things that marketers need to think about, the KPIs that they need to measure beyond simply correlating a campaign back to the ERP system to see if they got a good ROI on that effort? >> Well, I think what's really exciting about marketing now is that we have a bigger seat at the table, right, at that table for the business. And with the ability to report and really show the value of what we do, we're not just top of the funnel. Traditionally what happens is we can do all the work we do to brings leads into a sales ecosystem and then we're like okay there you go. Sales, do what you need to do, right? We don't have to stop there anymore. We can help with the entire sales process. And once that sales process is done and we have a customer, we can continue to help the business engage with that customer. So we're part of the entire journey. >> Right, and I'm curious too, your take, which I think is driven a lot by mobile where your touch points are shorter but more frequent, right, more diverse but a lot more of them, all different stages of that funnel. Cause they can get a lot of information on their own. So how has that kind of changed from a marketer perspective, how to think about content, how to think about that journey, not just as a simple funnel that drives to a transaction. >> Yeah, our jobs are not easy anymore. Yeah, we really have to be more strategic as marketers. So what's interesting about that is across that entire journey, we have to somehow be able to provide an experience in the moment, right? And the good news is, is that we have lots of marketing technology that can help us do that, right? It requires a lot of data, it requires a lot of engagement, and then being able to ingest that information and react to it as close to real time a we can is, I think it's a huge challenge, but that's what we have to be ready for. >> One of the things we heard from a lot of the practitioners that come on, customers of Adobe, and the ecosystem is getting more diverse data so they can get the blind spots identified, where they think they don't have any visibility and the-- >> The white space? >> In the white space, well they don't have enough, well they don't know what's going on. So what they were mentioning was is that okay funnel's great but they're going into this other journey past non-linear progressions, new-organic or in other channels and they want to try to identify what's going on there. So they need to instrument it, right? >> Yeah. So the challenging is how do I get that silo data that might be somewhere else? Or if it's new data, new first-party data, or third-party data, getting more data exposed into these new progressions is a real challenge. >> It is. And they want to keep iterating on it. So that seems to come up a lot. What's your reaction to that and how does this new kind of, let's say horizontal or horizontally scalable experience users are having? How do you guys view that? >> Well I, again I would love as a marketer to have access to all my data in one place, right? And not just my data, cause we have, marketers have special data, right? I would like to make sure I have all my data in one place. So, adjure, put it in the cloud on my data service, right? Put it there for me so I can then enable it, I can start throwing some AI at it so that I can have AI working for me, right? So I can help-- >> Talk about that dynamic, take a minute to explain why it's important to put the data in the cloud, because there's benefits to that-- >> Sure. >> You were mentioning earlier in the interview. Why is it important? Just take a minute to explain why it's important to put the data in the cloud. >> Well, because it gets rid of the data silos that you have, right? So if you can put your data in one place and then pull it into the systems, just the amount of data you need you can get to it in bite size pieces, right? So let me just inform the sales team with the information that just they need, right? And for the marketing team, let me give them just the data they care about, right? Cause it's very different. But if we have all of that in the same place then we can pull it in wherever we need it. >> Talk about your business and how you guys are doing in marketing. What's going on in the global landscape? What are some of the big trends that you're seeing? What wave are you riding? What's the big business benefits you guys are going after right now? >> Well right now at Avanade, we're really focused on this Adobe and Microsoft partnership. Right, for me, it's a really exciting time to be a marketer because well, to be a Marketing Technologist, to be at Avanade and helping with this whole new partnership. We now have the power of a whole marketing experience platform, Adobe experience platform, right, and the partnership with Microsoft and we can bring these two platforms together, right so-- >> And LinkedIn too, although technically Microsoft-- >> And LinkedIn, yeah. >> Still part of Microsoft, but you got the Dynamics 365 and LinkedIn which are kind of different groups, right? But still Microsoft. >> Yeah. Yeah and LinkedIn's a great example too. So LinkedIn has two places for marketers and sales to work. So marketers can do the LinkedIn lead gen, right? And then Sales can look at the LinkedIn profiles and the company profiles right on that lead record on Dynamics 365, right? So Marketing and Sales can work together. I can bring the leads in as a marketer and a sales person, and I can look at that lead on LinkedIn. So that's super exciting. >> What content types do you see as working, obviously videos, hot right now. I was just at the RSH Show, Jeff and I were there. We saw, everyone's doing videos from video blogging to full sets. Obviously we're streaming here. Video seems to be a hot format. >> What are, what other-- >> Video has been a hot format forever, I mean YouTube came into existence and all of a sudden you've got citizen videographers, right? And then you can put content out there like crazy. I see that it's still a very relevant platform but I personally would like to see how we can use AI to start targeting content to people who are doing some sort of activity online, it doesn't matter where you're at, to engage them, right? >> I think the machine learning is a big point for the AI. And you mentioned earlier, you don't have to worry about connecting stuff and I think if you look at the experience platform that they announced yesterday, they have all these connectors on the sides of their architecture cause that's where you guys are also connecting in, right, This is where you guys see that automation happening. >> Yes, yes. >> Is that what you meant by auto-integrating? >> Yes, exactly, yeah so as someone that builds marketing technology stacks, right, using Dynamics 365 as the hub of that, one of the biggest pain points back in the day, as in a couple years ago, right, was does this integrate with my CRM? Because that's a pain point, how am I going to integrate? I don't have to worry about that anymore, right? Again, going back to putting data in the cloud, I don't have to integrate technology directly into D365 anymore, right, and that-- >> What's the table stakes in the mar-tech stack, what's changed on the table stakes because it's funny as evolution comes, these new capabilities become table stakes like integration. You can't integrate, you're out. What new things are going on in the marketing technology field that was an exception or a luxury just a few months ago or years ago that are now table stakes for marketers? >> Table stakes in the marketing technology landscape, I think Adobe is really, let me shamelessly plug that cause I'm so excited about it, right, Adobe's really a leader in that. So how do you take an entire marketing technology platform, right, and it's not just, it's email marketing, it's your web space, it's your whatever other tool you have, right in your marketing technology stack. How do you aggregate them together in a way that makes sense for the marketer to use. So I think what you're going to see is things need to be really easy for the marketers to use on their own, right? Sometimes you need developers to do a lot of things, right? These pieces of technology can be really tech heavy in that respect, and I think you're going to see a lot of drag and drop capability, let's enable the marketer, the citizen marketer as I like to call them, to actually build what they need more on the fly. And you're seeing that a lot right now-- >> Well it's funny-- >> Marketo's very similar like that. >> Cause when you said the good news is the marketers have all these tools, I thought you were then going to say and the bad news is the marketers have all these tools. (John laughing) >> That's so true, yeah. >> Cause there's so many of them, right? >> There's such a, I know, influx of possibility, right? >> Right, so to have an integrated platform that pulls a lot of the core pieces together, you don't necessarily have to worry about the laundry list of potential tools that you might-- >> Exactly, exactly. >> That you might leverage. Already pre-integrated, ready to roll, super. Final thoughts on seeing the Satya on stage, that's got to help your enthusiasm for the partnership. >> 100%. (John and Jeff laughing) >> Good. >> I'm super happy to be here and I'm a huge advocate of the partnership so I'm really excited to see this happening. >> I think Adobe's done a great job. We're tough customers to please in terms of the tech but on the cloud side, the way they laid it out. The got all the things we think right, the first party-- >> Yeah, it's brilliant. >> Module, the data pipe lining and semantics was those are two, I think, beautiful architectural pieces. >> I agree. >> I think it's going to be, if they can get this thing automated and getting going, no more integration-- >> Thank you for making my life easier. (all laughing) I know, right? >> We'll see some acceleration on your end, with technologists. >> Yes, yup, I'll help, I'm here. >> Mishel, thank you for sharing the data and insights on theCUBE. >> Of course. >> Thanks. >> Of course. >> Great insights here on theCUBE, Adobe Summit, I'm John Furrier, Jeff Frick, stay with us for more Day Two coverage after this short break. (techno music)

(upbeat music) >> Hello, everyone. Welcome to theCUBE's special presentation of International Women's Day. I'm John Furrier, host of theCUBE. Jenni Troutman is here, Director of Products and Services, and Training and Certification at AWS, and Heather Ruden, Director of Education Programs, Training and Certification. Thanks for coming on theCUBE and for the International Women's Day special program. >> Thanks so much for having us. >> So, I'll just get it out of the way. I'm a big fan of what you guys do. I've been shouting at the top of my lungs, "It's free. Get cloud training and you'll have a six figure job." Pretty much. I'm over amplifying. But this is really a big opportunity in the industry, education and the skills gap, and the skill velocities that's changing. New roles are coming on around cloud native, cloud native operators, cybersecurity. There's so much excitement going on around the industry, and all these open positions, and they need new talent. So you can't get a degree for some of these things. So, nope, it doesn't matter what school you went to, everyone's kind of level. This is a really big deal. So, Heather, share with us your thoughts as well on this topic. Jenni, you too. Like, where are you guys at? 'Cause this is a big opportunity for women and anyone to level up in the industry. >> Absolutely. So I'll jump in and then I'll hand it over to Jenni. We're your dream team here. We can talk about both sides of this. So I run a set of programs here at AWS that are really intended to help build the next generation of cloud builders. And we do that with a variety of programs, whether it is targeting young learners from kind of 12 and up. We have AWS GetIT that is designed to get women ambassadors or women mentors in front of girls 12 to 14 and get them curious about a career in STEM. We also have a program that is all digital online. It's available in 11 languages. It's got hundreds of courses. That's called AWS Educate that is designed to do exactly what you just talked about, expose the opportunities and start building cloud skills for learners at age 13 and up. They can go online and register with an email and start learning. We want them to understand not only what the opportunity is for them, but the ways that they can help influence and bring more diversity and more inclusion and into the cloud technology space, and just keep building all those amazing builders that we need here for our customers and partners. And those are the programs that I manage, but Jenni also has an amazing program, a set of programs. And so I'll hand it over to her as you get into the professional side of this things. >> So Jenni, you're on the product side. You've got the keys to the kingdom on all the materials and shaping it. What's your view on this? 'Cause this is a huge opportunity and it's always changing. What's the latest and greatest? >> It is a massive opportunity and to give you a sense, there was a study in '21 where IT executives said that talent availability is the biggest challenge to emerging tech adoption. 64% of IT executives said that up from only 4% the year before. So the challenge is growing really fast, which for everyone that's ready to go out there and learn and try something new is a massive opportunity. And that's really why I'm here. We provide all kinds of learning experiences for people across different cloud technologies to be able to not only gain the knowledge around cloud, but also the confidence to be able to build in the cloud. And so we look across different learner levels, different roles, different opportunities, and we provide those experiences where people can actually get hands-on in a totally risk-free environment and practice building in the cloud so they can go and be ready to get their certifications, their AWS certifications, give them the credentials to be able to show an employer they can do it, and then go out and get these jobs. It's really exciting. And we go kind of end to end from the very beginning. What is cloud? I want to know what it is all the way through to I can prove that I can build in the cloud and I'm ready for a job. >> So Jenni, you nailed that confidence word. I think I want to double click on that. And Heather, you talked about you're the dream team. You guys, you're the go to market, you bring this to the marketplace. Jenni, you get the products. This is the key, but to me the the international women days angle is, is that what I hear over and over again is that, "It's too technical. I'm not qualified." It can be scary. We had a guest on who has two double E degrees in robotics and aerospace and she's hard charging. She almost lost her confidence twice she said in her career. But she was hard charging. It can get scary, but also the ability to level up fast is just as good. So if you can break through that confidence and keep the curiosity and be a builder, talk about that dynamic 'cause you guys are in the middle of it, you're in the industry, how do you handle that? 'Cause I think that's a big thing that comes up over and over again. And confidence is not just women, it's men too. But women can always, that comes up as a theme. >> It is. It is a big challenge. I mean, I've struggled with it personally and I mentor a lot of women and that is the number one challenge that is holding women back from really being able to advance is the confidence to step out there and show what they can do. And what I love about some of the products we've put out recently is we have AWS Skill Builder. You can go online, you can get all kinds of free core training and if you want to go deeper, you can go deeper. And there's a lot of different options on there. But what it does is not only gives you that based knowledge, but you can actually go in. We have something called AWS Labs. You can go in and you can actually practice on the AWS console with the services that people are using in their jobs every day without any risk of doing something that is going to blow up in your face. You're not going to suddenly get this big AWS bill. You're not going to break something that's out there running. You just go in. It's your own little environment that gets wiped when you're done and you can practice. And there's lots of different ways to learn as well. So if you go in there and you're watching a video and to your point you're like, "Oh my gosh, this is too technical. I can't understand it. I don't know what I'm going to go do." You can go another route. There's something called AWS Cloud Quest. It's a game. You go in and it's like you're gaming and it walks you through. You're actually in a virtual world. You're walking through and it's telling you, "Hey, go build this and if you need help, here's hints and here's tips." And it continues to build on itself. So you're learning and you're applying practical skills and it's at your own pace. You don't have to watch somebody else talking that is going at a pace that maybe accelerates beyond what you're ready. You can do it at your own pace, you can redo it, you can try it again until you feel confident that you know it and you're really ready to move on to the next thing. Personally, I find that hugely valuable. I go in and do these myself and I sit there and I have a lot of engineers on my team, very smart people. And I have my own imposter syndrome. I get nervous to go talk to them. Like, are they going to think I'm totally lost? And so I go in and I learn some of this myself by experiment. And then I feel like, okay, now I can go ask them some intelligent questions and they're not going to be like, "Oh gosh, my leader is totally unaware of what we're doing." And so I think that we all struggle with confidence. I think everybody does, but I see it especially in women as I mentor them. And that's what I encourage them to do is go and on your own time, practice a bit, get a little bit of experience and once you feel like you can throw a couple words out there that you know what they mean and suddenly other people look at you like, "Oh, she knows what she's talking about." And you can kind of get past that feeling. >> Well Jenni, you nailed it. Heather, she just mentioned she's in the job and she's going and she's still leveling up. That's the end when you're in, but it's also the barriers to entry are lowering. You guys are doing a good job of getting people in, but also growing fast too. So there's two dynamics at play here. How do people do this? What's the playbook? Because I think that's really key, easy to get in. And then once you're in, you can level up fast at your own pace to ride the wave. And then there's new stuff coming. I mean, every re:Invent there's 5,000 announcements. So it's like zillion new things and AI taught now. >> re:Invent is a perfect example of that ongoing imposter syndrome or confidence check for all of us. I think something that that Jenni said too is we really try and meet learners where they are and make sure that we have the support, whether it's accessibility requirements or we have the content that is built for the age that we're talking to, or we have a workforce development program called re/Start that is for people that have very little tech experience and really want to talk about a career in cloud, but they need a little bit more handholding. They need a combination of instructor-led and digital. But then we have AWS educators, I mentioned. If you want to be more self-directed, all of these tools are intended to work well together and to be complimentary and to take you on a journey as a learner. And the more skills you have, the more you increase your knowledge, the more you can take on more. But meeting folks where they are with a variety of programs, tools, languages, and accessibility really helps ensure that we can do that for learners throughout the world. >> That's awesome. Let's get into it. Let's get into the roadmaps of people and their personas. And you guys can share the programs that you have and where people could fit in. 'Cause this comes up a lot when I talk to folks. There's the young person who's I'm a gamer or whatever, I want to get a job. I'm in high school or an elementary or I want to tinker around or I'm in college or I'm learning, I'm an entry level kind of entry. Then you have the re-skilling. I'm going to change my careers, I'm kind of bored, I want to do something compelling. How do I get into the cloud game? And then the advanced re-skill is I want to get into cyber and AI and then there's other. Could you break down? Did I get that right or did I miss anything? And then what's available for those kind of lanes? So those persona lanes? >> Well, let's see, I could start with maybe the high schooler stuff and then we can bring Jenni in as well. I would say a great place to start for anyone is aws.amazon.com/training. That's going to give them the full suite of options that they could take on. If you're in high school, you can go onto AWS Educate. All you need is an email. And if you're 13 years and older, you can start exploring the types of jobs that are available in the cloud and you could start taking some introductory classes. You can do some of those labs in a safe environment that Jenni mentioned. That's a great place to start. If you are in an environment where you have an educator that is willing to go on this with you, this journey with you, we have this AWS GetIT program that is, again, educator-led. So it's an afterschool or it's an a program where we match mentors and students up with cloud professionals and they do some real-time experimentation. They build an app, they work on things together, and do a presentation at the end. The other thing I would say too is that if you are in a university, I would double check and see if the AWS Academy curriculum is already in your university. And if so, explore some of those classes there. We have instructor-led, educator-ready. course curriculum that we've designed that help people get to those certifications and get closer to those jobs and as well as hopefully then lead people right into skill builder and all the things that Jenni talked about to help them as they start out in a professional environment. >> So is the GetIT, is that an instructor-led that the person has to find someone for? Or is this available for them? >> It is through teachers. It's through educators. We are in, we've reached over 19,000 students. We're available in eight countries. There are ways for educators to lead this, but we want to make sure that we are helping the kids be successful and giving them an educator environment to do that. If they want to do it on their own, then they can absolutely go through AWS Educate or even and to explore where they want to get started. >> So what about someone who's educated in their middle of their career, might want to switch from being a biologist to a cloud cybersecurity guru or a cloud native operator? >> Yeah, so in that case, AWS re/Start is one of the great program for them to explore. We run that program with collaborating organizations in 160 cities in 80 countries throughout the world. That is a multi-week cohort-based program where we do take folks through a very clear path towards certification and job skilling that will help them get into those opportunities. Over 98% of the cohorts, the graduates of those cohorts get an interview and are hopefully on their path to getting a job. So that really has global reach. The partnership with collaborating organizations helps us ensure that we find communities that are often unreached by cloud skills training and we really work to keep a diverse focus on those cohorts and bring those folks into the cloud. >> Okay. Jenni, you've got the Skill Builder action here. What's going on on your side? Because you must have to manage all the change. I mean, AI is hot right now. I'm sure you're cranking away on curriculum and content for SageMaker, large language models, computer vision, cybersecurity. >> We do. There are a lot of options. >> How is your world? Tell us about what people can take out of way from your side. >> Yeah. So a great way to think about it is if they're already out in the workforce or they're entering the workforce, but they are technical, have technical skills is what are the roles that are interesting in the technologies that are interesting. Because the way we put out our training and our certifications is aligned to paths. So if you're look interested in a specific role. If you're interested in architecting a cloud environment or in security as you mentioned, and you want to go deep in security, there are AWS certifications that give you that. If you achieve them, they're very difficult. But if you work to them and achieve them, they give you the credential that you can take to an employer and say, "Look, I can do this job." And they are in very high demand. In fact that's where if you look at some of the publications that have come out, they talk about, what are people making if they have different certifications? What are the most in-demand certifications that are out there? And those are what help people get jobs. And so you identify what is that role or that technology area I want to learn. And then you have multiple options for how you build those skills depending on how you want to learn. And again, that's really our focus, is on providing experiences based on how people learn and making it accessible to them. 'Cause not everybody wants to learn in the same way. And so there is AWS Skill Builder where people can go learn on their own that is really great particularly for people who maybe are already working and have to learn in the evenings, on the weekends. People who like to learn at their own pace, who just want to be hands-on, but are self-starters. And they can get those whole learning plans through there all the way aligned to the certification and then they can go get their certification. There's also classroom training. So a lot of people maybe want to do continuous learning through an online, but want to go really deep with an expert in the room and maybe have a more focused period of time if they can go for a couple days. And so they can do classroom training. We provide a lot of classroom training. We have partners all over the globe who provide classroom training. And so there's that and what we find to be the most powerful is when you couple the two. If you can really get deep, you have an expert, you can ask questions, but first before you go do that, you get some of that foundational that you've kind of learned on your own. And then after you go back and reinforce, you go back online, you try out things that maybe you learned in the classroom, but you didn't quite, you hadn't used it enough yet to quite know how to do it. Now you can go back and actually use it, experiment and play around. And so we really encourage that kind of, figure out what are some areas you're interested in, go learn it and then go get a job and continue to learn because then once you learn that first area, you start to build confidence in it. Suddenly other areas become interesting. 'Cause as you said, cloud is changing fast. And once you learn a space, first of all you have to keep going back to stay up on it as it changes. But you quickly find that there are other areas that are really interesting too. >> I've observed that the training side, it's just like cloud itself, it's very agile. You can get hands-on quickly, you don't need to take a class, and then get in weeks later. You're in it like it's real time. So you're immersed in gamification and all kinds of ways to funnel into the either advanced tracks and certification. So you guys do a great job and I want to give you props for that and a shout out. The question I have for you guys is can you scope the opportunity for these certifications and opportunities for women in particular? What are some of the top jobs pulling down? Scope out the opportunity because I think when people hear that they really fall out of their chair, they go, "Wow, I didn't know I could make $200,000 doing cybersecurity." Well, yeah or maybe more. I just made the number, I don't actually know, but like I know people do make that much in cyber, but there are huge financial opportunities with certifications and education. Can you scope that order of magnitude? Can you share any data? >> Yeah, so in the US they certainly are. Certifications on average aligned to six digit type jobs. And if you go out and do a search, there are research studies out there that are refreshed every year that say what are the top IT industry certifications and how much money do they make? And the reason I don't put a number out there is because it's constantly changing and in fact it keeps going up, >> It's going up, not going down. >> But I would encourage people to do that quick search. What are the top IT industry certifications. Again, based on the country you're in, it makes a difference. But if you're US, there's a lot of data out there for the US and then there is some for other countries as well around how much on average people make. >> Do you list like the higher level certifications, stack rank them in terms of order? Like say, I'm a type A personnel, I want to climb Mount Everest, I want to get the highest level certification. How do I know that? Is it like laddered up or is like how do you guys present that? >> Yeah, so we have different types of certifications. There is a foundational, which we call the cloud practitioner. That one is more about just showing that you know something about cloud. It's not aligned to a specific job role. But then we have what we call associate level certifications, which are aligned to roles. So there's the solutions architect, cloud developer, so developer operations. And so you can tell by the role and associate is kind of that next level. And then the roles often have a professional level, which is even more advanced. And basically that's saying you're kind of an Uber expert at that point. And then there are technology specialties, which are less about a specific role, although some would argue a security technology specialty might align very well to a security role, but they're more about showing the technology. And so typically, it goes foundational, advanced, professional, and then the specialties are more on the side. They're not aligned, but they're deep. They're deep within that area. >> So you can go dig and pick your deep dive and jump into where you're comfortable. Heather, talk about the commitment in terms of dollars. I know Amazon's flaunted some numbers like 30 million or something, people they want to have trained, hundreds of millions of dollars in investment. This is key, obviously, more people trained on cloud, more operators, more cloud usage, obviously. I see the business connection. What's the women relationship to the numbers? Or what the experience is? How do you guys see that? Obviously International Women's Day, get the confidence, got the curiosity. You're a builder, you're in. It's that easy. >> It doesn't always feel that way, I'm sure to everybody, but we'd like to think that it is. Amazon and AWS do invest hundreds of millions of dollars in free training every year that is accessible to everyone out there. I think that sometimes the hardest obstacles to get overcome are getting started and we try and make it as easy as possible to get started with the tools that we've talked about already today. We run into plenty of cohorts of women as part of our re/Start program that are really grateful for the opportunity to see something, see a new way of thinking, see a new opportunity for them. We don't necessarily break out our funding by women versus men. We want to make sure that we are open and diverse for everybody to come in and get the training that they need to. But we definitely want to make sure that we are accessible and available to women and all genders outside of the US and inside the US. >> Well, I know the number's a lot lower than they should be and that's obviously why we're promoting this heavily. There's a lot more interest I see in tech. So digital transformation is gender neutral. I mean, it's like the world eats software and uses software, uses the cloud. So it has to get 50/50 in my opinion. So you guys do a great job. Now that we're done kind of promoting Amazon, which I wanted to do 'cause I think it's super important. Let's talk about you guys. What got you guys involved in tech? What was the inspiration and share some stories about your experiences and advice for folks watching? >> So I've always been in traditionally male dominated roles. I actually started in aviation and then moved to tech. And what I found was I got a mentor early on, a woman who was senior to me and who was kind of who I saw as the smartest person out there. She was incredibly smart, she was incredibly kind, and she was always lifting women up. And I kind of latched onto her and followed her around and she was such an amazing mentor. She brought me from throughout tech, from company to company, job to job, was always positioning me in front of other people as the go-to person. And I realized, "Wow, I want to be like her." And so that's been my focus as well in tech is you can be deeply technical in tech or you can be not deeply technical and be in tech and you can be successful both ways, but the way you're going to be most successful is if you find other people, build them up and help put them out in front. And so I personally love to mentor women and to put them in places where they can feel comfortable being out in front of people. And that's really been my career. I have tried to model her approach as much as I can. >> That's a really interesting observation. It's the pattern we've been seeing in all these interviews for the past two years of doing the International Women's Day is that networking, mentoring and sponsorship are one thing. So it's all one thing. It's not just mentoring. It's like people think, "Oh, just mentoring. What does that mean? Advice?" No, it's sponsorship, it's lifting people up, creating a keiretsu, creating networks. Really important. Heather, what's your experience? >> Yeah, I'm sort of the example of somebody who never thought they'd be in tech, but I happened to graduate from college in the Silicon Valley in the early nineties and next thing you know, it's more than a couple years later and I'm deeply in tech and I think it when we were having the conversation about confidence and willingness to learn and try that really spoke to me as well. I think I had to get out of my own way sometimes and just be willing to not be the smartest person in the room and just be willing to ask a lot of questions. And with every opportunity to ask questions, I think somebody, I ended up with good mentors, male and female, that saw the willingness to ask questions and the willingness to be humble in my approach to learning. And that really helped. I'm also very aware that nobody's journey is the same and I need to create an environment on my team and I need to be a role model within AWS and Amazon for allowing people to show up in the way that they're going to be most successful. And sometimes that will mean giving them learning opportunities. Sometimes that will be hooking them up with a mentor. Sometimes that will be giving them the freedom to do what they need for their family or their personal life. And modeling that behavior regardless of gender has always been how I choose to show up and what I ask my leaders to do. And the more we can do that, I've seen the team been able to grow and flourish in that way and support our entire team. >> I love that story. You also have a great leader, Maureen Lonergan, who I've met many conversations with, but also it starts at the top. Andy Jassy who can come across, he's kind of technical, he's dirty, he's a builder mentality. He has first principles and you're bringing up this first principles concept and whether that's passing it forward, what you've learned, having first principles helps in an organization. Can you guys talk about what that's like at your company? 'Cause everyone's different. And sometimes whether, and I sometimes I worry about what I say, but I also have my first principles. So talk about how principles matter in how you guys interface with others and letting people be their authentic self. >> Yeah, I'll jump in Jenni and then you can. The Amazon leadership principles are super important to how we interact with each other and it really does provide a set of guidelines for how we work with each other and how we work for our customers and with our partners. But most of all it gives us a common language and a common set of expectations. And I will be honest, they're not always easy. When you come from an environment that tends to be less open to feedback and less open to direct conversations than you find at Amazon, it could take a while to get used to that, but for me at least, it was extremely empowering to have those tools and those principles as guidance for how to operate and to gain the confidence in using them. I've also been able to participate in hundreds and hundreds of interviews in the time that I've been here as part of an interview team of bar raisers. I think that really helps us understand whether or not folks are going to be successful at AWS and at Amazon and helps them understand if they're going to be able to be successful. >> Bar raising is an Amazon term and it's gender neutral, right Jenni? >> It is gender neutral. >> Bar is a bar, it raises. >> That's right. And it's funny, we say that our culture here is peculiar. And when I started, I had been in consulting for several years, so I worked with a lot of different companies in tech and so I thought I'd seen everything and I came here and I went, "Hmm." I see what they mean by peculiar. It is very different environment. >> In the fullness of time, it'll all work out. >> That's right, that's right. Well and it's funny because when you first started, it's a lot to figure out to how to operate in an environment where people do use a 16 leadership principles. I've worked at a lot of companies with three or four core values and nobody can state those. We could state all 16 leadership principles and we use them in our regular everyday dialogue. That is an awkward thing when you first come to have people saying, "Oh, I'm going to use bias for action in this situation and I'm going to go move fast. And they're actually used in everyday conversations. But after a couple years suddenly you realize, "Oh, I'm doing that." And maybe even sometimes at the dinner table I'm doing that, which can get to be a bit much. But it creates an environment where we can all be different. We can all think differently. We can all have different ways of doing things, but we have a common overall approach to what we're trying to achieve. And that's really, it gives us a good framework for that. >> Jenni, it's great insight. Heather, thank you so much for sharing your stories. We're going to do this not once a year. We're going to continue this Women in Tech program every quarter. We'll check in with you guys and find out what's new. And thank you for what you do. We appreciate that getting the word out and really is an opportunity for everyone with education and cloud and it's only going to get more opportunities at the edge in AI and so much more tech. Thank you for coming on the program. >> Thank you for having us. >> Thanks, John. >> Thank you. That's the International Women's Day segment here with leaders from AWS. I'm John Furrier. Thanks for watching. (upbeat musiC)

Upbeat music plays >> Voice Over: TheCUBE presents Ignite 22, brought to you by Palo Alto Networks. >> Good morning everyone. Welcome to theCUBE. Lisa Martin here with Dave Vellante. We are live at Palo Alto Networks Ignite. This is the 10th annual Ignite. There's about 3,000 people here, excited to really see where this powerhouse organization is taking security. Dave, it's great to be here. Our first time covering Ignite. People are ready to be back. They.. and security is top. It's a board level conversation. >> It is the other Ignite, I like to call it cuz of course there's another big company has a conference name Ignite, so I'm really excited to be here. Palo Alto Networks, a company we've covered for a number of years, as we just wrote in our recent breaking analysis, we've called them the gold standard but it's not just our opinion, we've backed it up with data. The company's on track. We think to do close to 7 billion in revenue by 2023. That's double it's 2020 revenue. You can measure it with execution, market cap M and A prowess. I'm super excited to have the CEO here. >> We have the CEO here, Nikesh Arora joins us from Palo Alto Networks. Nikesh, great to have you on theCube. Thank you for joining us. >> Well thank you very much for having me Lisa and Dave >> Lisa: It was great to see your keynote this morning. You said that, you know fundamentally security is a data problem. Well these days every company has to be a data company. Grocery stores, gas stations, car dealers. How is Palo Alto networks making customers, these data companies, more secure? >> Well Lisa, you know, (coughs) I've only done cybersecurity for about four, four and a half years so when I came to the industry I was amazed to see how security is so reactive as opposed to proactive. We should be able to stop bad threats, right? as they're happening. But I think a lot of threats get through because we don't have the right infrastructure and the right tooling and right products in there. So I think we've been working hard for the last four and a half years to turn it around so we can have consistent data flow across an enterprise and then mine that data for threats and anomalous behavior and try and protect our customers. >> You know the problem, I wrote this, this weekend, the problem in cybersecurity is well understood, you put up that Optiv graph and it's like 8,000 companies >> Yes >> and I think you mentioned your keynote on average, you know 30 to 40 tools, maybe 50, at least 20, >> Yes. >> from the folks that I talked to. So, okay, great, but actually solving that problem is not trivial. To be a consolidator, I mean, everybody wants to consolidate tools. So in your three to four years and security as you well know, it's, you can't fake security. It's a really, really challenging topic. So when you joined Palo Alto Networks and you heard that strategy, I know you guys have been thinking about this for some time, what did you see as the challenges to actually executing on that and how is it that you've been able to sort of get through that knot hole. >> So Dave, you know, it's interesting if you look at the history of cybersecurity, I call them the flavor of the decade, a flare, you know a new threat vector gets created, very large market gets created, a solution comes through, people flock, you get four or five companies will chase that opportunity, and then they become leaders in that space whether it's firewalls or endpoints or identity. And then people stick to their swim lane. The problem is that's a very product centric approach to security. It's not a customer-centric approach. The customer wants a more secure enterprise. They don't want to solve 20 different solutions.. problems with 20 different point solutions. But that's kind of how the industry's grown up, and it's been impossible for a large security company in one category, to actually have a substantive presence in the next category. Now what we've been able to do in the last four and a half years is, you know, from our firewall base we had resources, we had intellectual capability from a security perspective and we had cash. So we used that to pay off our technical debt. We acquired a bunch of companies, we created capability. In the last three years, four years we've created three incremental businesses which are all on track to hit a billion dollars the next 12 to 18 months. >> Yeah, so it's interesting on Twitter last night we had a little conversation about acquirers and who was a good, who was not so good. It was, there was Oracle, they came up actually very high, they'd done pretty, pretty good Job, VMware was on the list, IBM, Cisco, ServiceNow. And if you look at IBM and Cisco's strategy, they tend to be very services heavy, >> Mm >> right? How is it that you have been able to, you mentioned get rid of your technical debt, you invested in that. I wonder if you could, was it the, the Cloud, even though a lot of the Cloud was your own Cloud, was that a difference in terms of your ability to integrate? Because so many companies have tried it in the past. Oracle I think has done a good job, but it took 'em 10 to 12 years, you know, to, to get there. What was the sort of secret sauce? Is it culture, is it just great engineering? >> Dave it's a.. thank you for that. I think, look, it's, it's a mix of everything. First and foremost, you know, there are certain categories we didn't play in so there was nothing to integrate. We built a capability in a category in automation. We didn't have a product, we acquired a company. It's a net new capability in instant response. We didn't have a capability. It was net new capability. So there was, there was, other than integrating culturally and into the organization into our core to market processes there was no technical integration needed. Most of our technical integration was needed in our Cloud platform, which we bought five or six companies, we integrated then we just bought one recently called cyber security as well, which is going to get integrated in the Cloud platform. >> Dave: Yeah. >> And the thing is like, the Cloud platform is net new in the industry. We.. nobody's created a Cloud security platform yet, so we're working hard to create it because we don't want to replicate the mistakes of the past, that were made in enterprise security, in Cloud security. So it's a combination of cultural integration it's a combination of technical integration. The two things we do differently I think, than most people in the industry is look, we have no pride of, you know of innovations. Like, if somebody else has done it, we respect it and we'll acquire it, but we always want to acquire number one or number two in their category. I don't want number three or four. There's three or four for a reason and there still leaves one or two out there to compete with. So we've always acquired one or two, one. And the second thing, which is as important is most of these companies are in the early stage of development. So it's very important for the founding team to be around. So we spend a lot of time making sure they stick around. We actually make our people work for them. My principle is, listen, if they beat us in the open market with all our resources and our people, then they deserve to run this as opposed to us. So most of our new product categories are run by founders of companies required. >> So a little bit of Jack Welch, a little bit of Franks Lubens is a, you know always deference to the founders. But go ahead Lisa. >> Speaking of cultural transformation, you were mentioning your keynote this morning, there's been a significant workforce transformation at Palo Alto Networks. >> Yeah >> Talk a little bit about that, cause that's a big challenge, for many organizations to achieve. Sounds like you've done it pretty well. >> Well you know, my old boss, Eric Schmidt, used to say, 'revenue solves all known problems'. Which kind of, you know, it is a part joking, part true, but you know as Dave mentioned, we've doubled or two and a half time the revenues in the last four and a half years. That allows you to grow, that allows you to increase headcount. So we've gone from four and a half thousand people to 14,000 people. Good news is that's 9,500 people are net new to the company. So you can hire a whole new set of people who have new skills, new capabilities and there's some attrition four and a half thousand, some part of that turns over in four and a half years, so we effectively have 80% net new people, and the people we have, who are there from before, are amazing because they've built a phenomenal firewall business. So it's kind of been right sized across the board. It's very hard to do this if you're not growing. So you got to focus on growing. >> Dave: It's like winning in sports. So speaking of firewalls, I got to ask you does self-driving cars need brakes? So if I got a shout out to my friend Zeus Cararvela so like that's his line about why you need firewalls, right? >> Nikesh: Yes. >> I mean you mentioned it in your keynote today. You said it's the number one question that you get. >> and I don't get it why P industry observers don't go back and say that's, this is ridiculous. The network traffic is doubling or tripling. (clears throat) In fact, I gave an interesting example. We shut down our data centers, as I said, we are all on Google Cloud and Amazon Cloud and then, you know our internal team comes in, we'd want a bigger firewall. I'm like, why do you want a bigger firewall? We shut down our data centers as well. The traffic coming in and out of our campus is doubled. We need a bigger firewall. So you still need a firewall even if you're in the Cloud. >> So I'm going to come back to >> Nikesh: (coughs) >> the M and A strategy. My question is, can you be both best of breed and develop a comprehensive suite number.. part one and part one A of that is do you even have to, because generally sweets win out over best of breed. But what, how do you, how do you respond? >> Well, you know, this is this age old debate and people get trapped in that, I think in my mind, and let me try and expand the analogy which I tried to do up in my keynote. You know, let's assume that Oracle, Microsoft, Dynamics and Salesforce did not exist, okay? And you were running a large company of 50,000 people and your job was to manage the customer process which easier to understand than security. And I said, okay, guess what? I have a quoting system and a lead system but the lead system doesn't talk to my coding system. So I get leads, but I don't know who those customers. And I write codes for a whole new set of customers and I have a customer database. Then when they come as purchase orders, I have a new database with all the customers who've bought something from me, and then when I go get them licensing I have a new database and when I go have customer support, I have a fifth database and there are customers in all five databases. You'll say Nikesh you're crazy, you should have one customer database, otherwise you're never going to be able to make this work. But security is the same problem. >> Dave: Mm I should.. I need consistency in data from suit to nuts. If it's in Cloud, if you're writing code, I need to understand the security flaws before they go into deployment, before they go into production. We for somehow ridiculously have bought security like IT. Now the difference between IT and security is, IT is required to talk to each other, so a Dell server and HP server work very similarly but a Palo Alto firewall and a Checkpoint firewall Fortnight firewall work formally differently. And then how that transitions into endpoints is a whole different ball game. So you need consistency in data, as Lisa was saying earlier, it's a data problem. You need consistency as you traverse to the enterprise. And that's why that's the number one need. Now, when you say best of breed, (coughs) best of breed, if it's fine, if it's a specific problem that you're trying to solve. But if you're trying to make sure that's the data flow that happens, you need both best of breed, you know, technology that stops things and need integration on data. So what we are trying to do is we're trying to give people best to breed solutions in the categories they want because otherwise they won't buy us. But we're also trying to make sure we stitch the data. >> But that definition of best of breed is a little bit of nuance than different in security is what I'm hearing because that consistency >> Nikesh: (coughs) Yes, >> across products. What about across Cloud? You mentioned Google and Amazon. >> Yeah so that's great question. >> Dave: Are you building the security super Cloud, I call it, above the Cloud? >> It's, it's not, it's, less so a super Cloud, It's more like Switzerland and I used to work at Google for 10 years, not a secret. And we used to sell advertising and we decided to go into pub into display ads or publishing, right. Now we had no publishing platform so we had to be good at everybody else's publishing platform >> Dave: Mm >> but we never were able to search ads for everybody else because we only focus on our own platform. So part of it is when the Cloud guys they're busy solving security for their Cloud. Google is not doing anything about Amazon Cloud or Microsoft Cloud, Microsoft's Azure, right? AWS is not doing anything about Google Cloud or Azure. So what we do is we don't have a Cloud. Our job in providing Cloud securities, be Switzerland make sure it works consistently across every Cloud. Now if you try to replicate what we offer Prisma Cloud, by using AWS, Azure and GCP, you'd have to first of all, have three panes of glass for all three of them. But even within them they have four panes of glass for the capabilities we offer. So you could end up with 12 different interfaces to manage a development process, we give you one. Now you tell me which is better. >> Dave: Sounds like a super Cloud to me Lisa (laughing) >> He's big on super Cloud >> Uber Cloud, there you >> Hey I like that, Uber Cloud. Well, so I want to understand Nikesh, what's realistic. You mentioned in your keynote Dave, brought it up that the average organization has 30 to 50 tools, security tools. >> Nikesh: Yes, yes >> On their network. What is realistic for from a consolidation perspective where Palo Alto can come in and say, let me make this consistent and simple for you. >> Well, I'll give you your own example, right? (clears throat) We're probably sub 10 substantively, right? There may be small things here and there we do. But on a substantive protecting the enterprise perspective you be should be down to eight or 10 vendors, and that is not perfect but it's a lot better than 50, >> Lisa: Right? >> because don't forget 50 tools means you have to have capability to understand what those 50 tools are doing. You have to have the capability to upgrade them on a constant basis, learn about their new capabilities. And I just can't imagine why customers have two sets of firewalls right. Now you got to learn both the files on how to deploy both them. That's silly because that's why we need 7 million more people. You need people to understand, so all these tools, who work for companies. If you had less tools, we need less people. >> Do you think, you know I wrote about this as well, that the security industry is anomalous and that the leader has, you know, single digit, low single digit >> Yes >> market shares. Do you think that you can change that? >> Well, you know, when I started that was exactly the observation I had Dave, which you highlighted in your article. We were the largest by revenue, by small margin. And we were one and half percent of the industry. Now we're closer to three, three to four percent and we're still at, you know, like you said, going to be around $7 billion. So I see a path for us to double from here and then double from there, and hopefully as we keep doubling and some point in time, you know, I'd like to get to double digits to start with. >> One of the things that I think has to happen is this has to grow dramatically, the ecosystem. I wonder if you could talk about the ecosystem and your strategy there. >> Well, you know, it's a matter of perspective. I think we have to get more penetrated in our largest customers. So we have, you know, 1800 of the top 2000 customers in the world are Palo Alto customers. But we're not fully penetrated with all our capabilities and the same customers set, so yes the ecosystem needs to grow, but the pandemic has taught us the ecosystem can grow wherever they are without having to come to Vegas. Which I don't think is a bad thing to be honest. So the ecosystem is growing. You are seeing new players come to the ecosystem. Five years ago you didn't see a lot of systems integrators and security. You didn't see security offshoots of telecom companies. You didn't see the Optivs, the WWTs, the (indistinct) of the world (coughs) make a concerted shift towards consolidation or services and all that is happening >> Dave: Mm >> as we speak today in the audience you will find people from Google, Amazon Microsoft are sitting in the audience. People from telecom companies are sitting in the audience. These people weren't there five years ago. So you are seeing >> Dave: Mm >> the ecosystem's adapting. They're, they want to be front and center of solving the customer's problem around security and they want to consolidate capability, they need. They don't want to go work with a hundred vendors because you know, it's like, it's hard. >> And the global system integrators are key. I always say they like to eat at the trough and there's a lot of money in security. >> Yes. >> Dave: (laughs) >> Well speaking of the ecosystem, you had Thomas Curry and Google Cloud CEO in your fireside chat in the keynote. Talk a little bit about how Google Cloud plus Palo Alto Networks, the Zero Trust Partnership and what it's enable customers to achieve. >> Lisa, that's a great question. (clears his throat) Thank you for bringing it up. Look, you know the, one of the most fundamental shifts that is happening is obviously the shift to the Cloud. Now when that shift fully, sort of, takes shape you will realize if your network has changed and you're delivering everything to the Cloud you need to go figure out how to bring the traffic to the Cloud. You don't have to bring it back to your data center you can bring it straight to the Cloud. So in that context, you know we use Google Cloud and Amazon Cloud, to be able to carry our traffic. We're going from a product company to a services company in addition, right? Cuz when we go from firewalls to SASE we're not carrying your traffic. When we carry our traffic, we need to make sure we have underlying capability which is world class. We think GCP and AWS and Azure run some of the biggest and best networks in the world. So our partnership with Google is such that we use their public Cloud, we sit on top of their Cloud, they give us increased enhanced functionality so that our customers SASE traffic gets delivered in priority anywhere in the world. They give us tooling to make sure that there's high reliability. So you know, we partner, they have Beyond Corp which is their version of Zero Trust which allows you to take unmanaged devices with browsers. We have SASE, which allows you to have managed devices. So the combination gives our collective customers the ability for Zero Trust. >> Do you feel like there has to be more collaboration within the ecosystem, the security, you know, landscape even amongst competitors? I mean I think about Google acquires Mandiant. You guys have Unit 42. Should and will, like, Wendy Whitmore and maybe they already are, Kevin Mandia talk more and share more data. If security's a data problem is all this data >> Nikesh: Yeah look I think the industry shares threat data, both in private organizations as well as public and private context, so that's not a problem. You know the challenge with too much collaboration in security is you never know. Like you know, the moment you start sharing your stuff at third parties, you go out of Secure Zone. >> Lisa: Mm >> Our biggest challenge is, you know, I can't trust a third party competitor partner product. I have to treat it with as much suspicion as anything else out there because the only way I can deliver Zero Trust is to not trust anything. So collaboration in Zero Trust are a bit of odds with each other. >> Sounds like another problem you can solve >> (laughs) >> Nikesh last question for you. >> Yes >> Favorite customer or example that you think really articulates the value of what Palo Alto was delivering? >> Look you know, it's a great question, Lisa. I had this seminal conversation with a customer and I explained all those things we were talking about and the customer said to me, great, okay so what do I need to do? I said, fun, you got to trust me because you know, we are on a journey, because in the past, customers have had to take the onus on themselves of integrating everything because they weren't sure a small startup will be independent, be bought by another cybersecurity company or a large cybersecurity company won't get gobbled up and split into pieces by private equity because every one of the cybersecurity companies have had a shelf life. So you know, our aspiration is to be the evergreen cybersecurity company. We will always be around and we will always tackle innovation and be on the front line. So the customer understood what we're doing. Over the last three years we've been working on a transformation journey with them. We're trying to bring them, or we have brought them along the path of Zero Trust and we're trying to work with them to deliver this notion of reducing their meantime to remediate from days to minutes. Now that's an outcome based approach that's a partnership based approach and we'd like, love to have more and more customers of that kind. I think we weren't ready to be honest as a company four and a half years ago, but I think today we're ready. Hence my keynote was called The Perfect Storm. I think we're at the right time in the industry with the right capabilities and the right ecosystem to be able to deliver what the industry needs. >> The perfect storm, partners, customers, investors, employees. Nikesh, it's been such a pleasure having you on theCUBE. Thank you for coming to talk to Dave and me right after your keynote. We appreciate that and we look forward to two days of great coverage from your executives, your customers, and your partners. Thank you. >> Well, thank you for having me, Lisa and Dave and thank you >> Dave: Pleasure >> for what you guys do for our industry. >> Our pleasure. For Nikesh Arora and Dave Vellante, I'm Lisa Martin, you're watching theCUBE live at MGM Grand Hotel in Las Vegas, Palo Alto Ignite 22. Stick around Dave and I will be joined by our next guest in just a minute. (cheerful music plays out)

(soft music) >> We're in Las Vegas at The Venetian for our continued coverage here of re:Invent '22, AWS's big show going on. Great success off to a wonderful start. We're in the Executive Summit sponsored by Accenture. And we're going to talk about public health and the cloud, how those have come together in the great state of North Carolina. Charles Carter is going to help us do that. He's assistant secretary for technology services with the state of North Carolina's Department of Health and Human Services. Charles, good to see you. Thanks for joining us here on "theCUBE". >> Thank you very much for having me. >> Yeah, thanks for making the time. So first off, let's talk about what you do on the homefront before what you're doing here and where you're going. But in terms of kind of what your plan has been, what your journey has been from a cloud perspective and how you've implemented that and where you are right now in your journey. >> Sure, so we started. When I got there, we didn't have a cloud footprint at all. There was a- >> Host: Which was how long ago? >> I got there in 2016, so about six years. >> Host: Six, seven years, yeah. >> Yeah, five, six years. So anyways, we started off with our first module within our Medicaid expansion. And that was the first time that we went into the cloud. We worked with AWS to do our encounter processing system. And it was an incredible success. I think the ease of use was really kind of something that people weren't quite ready for. But it was really exciting to see that. And the scalability, to be able to turn that on and cover the entirety of North Carolina was awesome. So once we saw that and get a little taste of it, then we really wanted to start implementing it throughout DHHS. And we marshaled in a cloud-only cloud-first strategy where you had to actually get an exemption not to go to the cloud. And that was a first for our state. So that was really kind of the what launched us. But then COVID hit. And once COVID came in, that took us to a new level. COVID forced us to build technologies that enabled a better treatment, a better care, a better response from our team. And so we were able to stand up platforms in 48 hours. We were able to stand up COVID vaccine management systems in six weeks. And none of that would've been possible without the cloud. >> So forced your hand in a way because all of a sudden you've got this extraordinarily remote workforce, right, and people trying to- And you're doing different tasks that were totally unexpected, right, prior to that. What kind of a shock to the system was that from I get from an IT perspective? >> Yeah, so from a state government perspective, for example, you never hear you have all the money you need and you have to do it quickly. It just doesn't work like that. But this was a rare moment in time where you had this critical need. The entire country and our state population was kind of on edge. How do we move through this? How do we factor our lives into this new integration? What is this virus? Is it spreading in my county, in my city, my zip code? Where is it? And that kind of desperation really kind of focused everybody in on build me technologies that can get me the data that I need to make good healthcare decisions, good clinical decisions. And so that was our challenge. Cloud enabled it because it can scale so quickly. We can set up things, we can exchange data. We can move data around a lot easier. And the security is better from our perspective. So that COVID experience really kind of pushed us, you know, if you will, out the door. And we're never going back because it's just too good. >> Yeah, was that the aha moment then in a way because you had to do so much so fast and before capabilities that maybe you didn't have or maybe hadn't tapped? >> Yeah, yeah. >> I mean what was the accelerant there? Was COVID that big, or was it somebody who had to make a decision to say, this is where we're going with this, somebody in your shoes or somebody with whom you work? >> Yeah, no, I mean cloud at the end of the day, we knew that in order to do what we needed to do we couldn't do it on-prem. It wasn't an option. So if we wanted to build these capabilities, if we wanted to bring in technologies that really brought data to our key, our governor, our secretary, to make good decisions on behalf of our residents in North Carolina, then we were going to have to build things quickly. And the only way you can do that is in the cloud. So it was when they came back and said, "We need these things," there's only one answer. That's a good thing about technology. It's pretty binary, so it was either go with what we had, which wasn't adequate, or build to what we knew we could do and pretty short order. And because of that, we were able to actually usher in a huge expansion of cloud footprint within DHHS. And now we've actually been able to implement it in other departments simply because of our expertise. And that's been a huge asset for the state of North Carolina as a whole. >> So what's your measuring stick then for value in terms of identifying benefit? 'Cause it's not really about cost. This is about service, I assume, right? >> Right. >> So, you know, how do you quantify the values and the benefits that you're deriving from this migration over to the cloud? >> So from our perspective, it hits several different areas. I mean, you can start in security. We know that if we're in the cloud the tools that can manage and give us visibility in the cloud are 10 times better than an on-prem environment. And so if we can take a lot of these legacy systems and move them to the cloud, we'll be in a better security posture. So we have that piece of it. The other part of it is the data aspect of it, being able to- We're 33 divisions strong, right? We have a large footprint. We have a lot of siloed data elements. And cloud allows us to start integrating those data sets in a much more usable fashion so that we can see that if Charles Carter's in one area in division, a specific division with DHHS, is he somewhere else? And if he is somewhere else, then how do we provide a better clinical care for that individual? And those are conversations that we can't really have if we don't move to the cloud. So those types of- And of course there's always the OKRs, the actual measurements that you apply to things that we're doing. But at the end of the day, can we get the requirements from our business partners, bring those requirements to bear in technology, and really enable the indoctrination of these requirements throughout our clinical and healthcare kills? >> What about they're always pillars here, right? Governance, huge pillar, security, huge pillar, especially in your world, right? >> Yeah. >> So making that move over to the cloud and still recognizing that these are essentials that you have to have in place, I wouldn't say adjustments, but what kind of, I guess, recognition have you had toward that and making sure that you're still very true to those principles that are vital in the terms of public health? >> It is a great question because our secretary at the time and our governor, Roy Cooper, were very focused on enabling transparency. We had to be very transparent with what we were doing because the residents in North Carolina were just really kind of, "What's going on?" It was a scary time for a lot of us. So transparency was a key element towards our success. And in order to do that, you've got to have proper security. You got to have proper governance. You've got to have proper builds within technology that really enable that kind of visibility. One of the things that we did very early on was we set up a governance structure for our cloud environments so that as we wanted to and stand up an easy-to environment or we wanted to do some sort of work within a cloud or stand up in a different environment, we were able actually to set up a framework for how do you introduce that. Are you doing it correctly? Do you have the proper security on it? Do you have the funding for it? Like all the steps that you need to really kind of build into the scaffolding around a lot of these efforts we had to put in place and pretty quickly to get them going. But once we did that, the acceptance and the adoption of it was just tremendous. I mean, it was a light on for all of our business partners 'cause they understood I can either build on-prem, in which case I won't be able to get what I want in any kind of reasonable time period. Or I can build on cloud. And I can have it in some cases in 48 hours. >> Right, tomorrow. >> Yeah, exactly. >> You know, it was a huge difference. >> So where are you there? I mean, this is just not like a really big old lift and shift and we're all done and this is great. Cloud's taken care of all of our needs. Where are you in terms of the journey that you're undertaking? And then ultimately where do you want to go, like how far? What kind of goals have you set for yourself for the next two, three years down the road? >> Yeah, so this is an exciting part because we have actually- Like I mentioned earlier, we are a cloud-first cloud-only strategy, right? There's no reasons for us to be on-prem. It's just a matter of us kind of sunsetting legacy systems and bringing on cloud performance. We hope to be a 60% of our applications, which we have over 400 applications. So it's pretty large footprint. But we're wanting to migrate all of that to the cloud by 2025. So if we can achieve that, I think we'll be well on our way. And the momentum will carry forward for us to do that. We've actually had to do a reorganization of our whole IT structure. I think this is an important part to maintain that momentum because we've reorganized our staff, reorganized ourselves so that we can focus more on how do you adopt cloud, how do you bring in platforms which are all cloud-based, how do you use data within those systems? And that has allowed us to kind of think differently about our responsibilities, who's accountable for what, and to kind of keep those, that momentum going. So we've got some big projects that are on right now. Some of them are lift and shift, like you mentioned. We have a project with kind of a clumsy, monolithic system. It's called (indistinct). We're trying to migrate that to the cloud. We're in the process of doing that. And it's an excellent demonstration of capability once we pull that off. And then of course any new procurement that we put out there no one's making anything for on-prem anymore. Everyone's making their SaaS products for cloud-based experiences. Or if we're going to build or just use integrators then we'll build that in house. But all of it's based on cloud. >> And you mentioned SaaS. How much of this stuff are you doing on your own? And how much are you doing through managed services? >> Yeah, so like I mentioned, we have over 400 applications. So we had a pretty large footprint, right? >> Big, it's huge, right. >> So we're only who we are, and we can only build so much. So we're kind of taking- We did a application rationalization effort, which kind of identified some threats to our systems. Like maybe they're older things, FoxPro, kind of older languages that we're using. And in some cases we got people who are retiring. And there's not many people who can support that anymore. So how do we take those and migrate them to the cloud, either put them on a Salesforce or ServiceNow or Microsoft Dynamics platform and really kind of upgrade those systems? So we're in the process of kind of analyzing those elements. But yeah, that's kind of the exciting launch, if you will, of kind of taking the existing visibility of our applications and then applying it to what we're capable of with the cloud. >> And if you had advice that you could give to your colleagues who are in public health or just in public, the public sector- And your resources, they're finite. This is kind of what you have to deal with. And yet you have needs, and you're trying to stay current. You've got talent challenges, right? You've got rev or spending challenges. So if you could sit down your colleagues in a room and say, "Okay, this has been our experience. Here's what I would keep an eye out for," what kind of headlights would you beat for them? >> Yeah, so I think the biggest aha that I'd like to share with my contemporaries out there is that you've got a great ability to lower your costs, to excite your own personnel because they want to work on the new stuff. We've actually set up a whole professional development pathway within our organization to start getting people certified on AWS, certified on other platforms, to get them ready to start working in those environments. And so all of that work that we're been doing is coming together and allowing us to maintain the momentum. So what I'd recommend to people is, A, look at your own individual staff. I don't think you need to go outside to find the talent. I think you can train the talent that you have interior. I think you've got to aggressively pursue modernization because modernization enables a lot more. It's less expensive. It enables quicker adoption of business requirements and modern business requirements. And then lastly, focus on your data sharing because what you're going to find in the platforms and in the clouds is that there is a lot more opportunities for data integrations and conjoining disparate data sources. So if you can do those elements, you'll find that your capabilities on the business side are much more, much greater on the other end. >> Don't be scared, right, jump in? (laughing) >> Definitely don't be scared. Don't be, the water's warm. (host laughing) Come on in, you're fine, you're fine. (laughing) >> No little toe dipping in there. You're going to dive into the deep end, let her rip. >> Exactly, just go right in, just go right in. >> Well, it sounds like you've done that with great success. >> I'm very happy with it. >> Congratulations on that. And wish you success down the road. >> Thank you very much, I appreciate it. >> Yeah, thank you, Charles. All right, back with more. You are watching theCUBE here in Las Vegas. theCUBE of course the leader, as you know, in tech coverage. (soft music)

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

>>Hello everyone and welcome back to The Cube's Continuing coverage of AWS Reinvent. My name is Savannah Peterson and I am absolutely thrilled for this segment. We are joined by leaders at Cisco App Dynamics, as well as Royal Caribbean. The two have been working together for over five years, leveraging full stack observability. We're gonna dig in, but first of all, please welcome Alice from Royal Caribbean and Greg from Cisco App, app Dynamics to the show. Hey friends. >>Hi. How are you doing? >>I'm excited, clearly. How are you doing, Greg? >>I'm doing fantastic. Thanks for having me on the show today. >>Hey, it's our, it is absolutely our pleasure. Alice, I have to start with you. I don't think there are too many industries that have gotten as much coverage as cruising has over the last couple of years. You've been working with Royal Caribbean for over a decade, so you've seen it through the stormy seas of the pandemic, if you will. What has the last few years and the last few months been like for you? >>You know, it's, it's really been a wild ride. To your point, we were sailing high and then I don't think any other industry experience what we did in Covid, that you walked in one day and then that day the whole industry shut down. So it was a, it was a big challenge for us. And then as soon as we shut down and we weathered the storm with Covid, then we have what we called our healthy and return to service. So as quickly as it stopped, we had to start sailing again. So it's, it's really been a challenge, but we're happy to be back on our feet and heading in the right direction now. >>I, I really hope we can continue the sailing metaphors throughout the course of this interview. And you, you nailed that for a segment. Alice, I'm, I'm, I'm so, I'm so here for it. I, I, I wanna talk about how you've worked together, but I wanna give Greg a second to chime in here. So Greg, you're the executive CTO at Cisco App Dynamics. How, how have you and the team, whether the last two and a half years? >>Well, you, you know, it's interesting, the, the pandemic really brought together an interesting conundrum, right? So on, on one hand, you had, you know, the, the, the consumers, the end users that became very reliant on digital services. They had a function in a way that was very performing, right? So, 84% of the respondents that we had come back through a report called the App Attention Index, came back and said that digital services were, were really instrumental for them to, to get back to some level of normalcy. But the interesting part that came about that is that out of those respondents, 60% of them blame the brand if the, if the application did not work the way they expected it. So they didn't really care about the, it's in the back end, right? So when you look at, yeah, you look at the shift in the IT department, the IT department had to go out and, and quickly innovate, quickly start to introduce new services, which ultimately brought together a, a sprawl in their technology stack. So when you're adding to it, you're not taking things away, you're continuously growing. So finding that that, that the problems or the, the root cause of an application issue became more difficult. So that's where, you know, from an app, Cisco AppDynamics perspective, you know, we're one of the leading observability and app application performance monitoring tools. So we help customers like Ro Caribbean to be able to zero in on root cause and ensure that their end users have that best experience. It's, >>It's, it's, I I'm smiling as someone who was a, a former waitress and I can remember the amount of times I was scolded for something that happened that was far out of my control and the complex layers of the kitchen. And I think that, that anyone who's, who's had a, a poor customer experience while interacting with a brand may or may not intentional, I think it's actually sometimes very unintentional to your point, get frustrated with said brand. I can imagine that is an experience and a priority that you have at Royal Caribbean. Alice, how, how has Full Stack Observability played a role in your, in your team's ability to, to serve the customers and your, and keep your community engaged during this, this very kind of wobbly time? >>Yeah, you know, we have, have really worked hard to improve and remove friction from our guest vacation. And we wanna keep them on vacation and having a great time. You know, we say we don't really sell a cruise. We sell an experience. So we use App AppDynamics to monitor those key applications that our guests are interacting with to ensure that they're having that experience that we expect, you know, we've learned that just because a system or a server says, Hey, I'm up 99% of the time, that doesn't mean that my guests are experiencing that same type of stability, you know? So once again, we really worked well with App Dynamics. They've partnered with us to ensure that, you know, our guests are getting that vacation experience they're looking for. >>Do you think, just a follow up there, do you think that you would have advanced in the ways that you have working with Cisco App Dynamics and across functions over the last few years without this crunch, was necessity the mother of invention for you to any degree? >>You know, I don't, I don't think that the Crunch brought it on cuz we, like I said, we started this journey back in 2017 and we're not unlike a lot of companies where we're on this maturity ride where we wanna go from being reactive, where our guests are telling us something is broken to being preventive. Definitely, you know, COVID played into this because I think we learned to do less, you know, more with less. So, you know, we, you know, it's very hard in the cruise industry. We did take a hit, but we were able to use the app dynamics tools to ensure that our systems were running with having less people also watching those systems. So less eyes on glass, more automation, >>And that's a more, with more, more stability, more credibility, and more transparency is definitely something that we're all looking forward. And, and it's nice to see that implemented, especially at scale when you're dealing with so many customers from all over the world trying to access your service and, and wanting that personalized experience. Greg, what does it feel like for you as a leader to hear someone like Alice say how powerful your tool has been in ensuring that customer experience? >>Yeah, that's, you know, it's absolutely fantastic and especially, you know, Alice is absolutely right. You know, the, the, the cruise industry was really, had a very unique challenge in front of them, and I, I really applaud the folks at Royal Caribbean for stepping up to make sure that when the pandemic eased, so to speak, that they, that the experience to the customer was actually even better, right? So when we were able to work and partner together to make sure that, you know, the, the, the user experience is topnotch, the availability is there, the, the, the, the resiliency of their platform is there. So by, by working with customers like Royal CRI and is really one of the, the, the shining stars that we can talk about that really help make a big difference in, you know, that post pandemic era to be able to really do what's right for the customer. >>How often are you engaging with customers like Alice as a team? How big is that feedback in your product roadmap? >>Oh, personally, I, I'm, I'm engaged with customers on a daily basis and I see it fr across the map from many different industries. And, you know, a lot of folks had different challenges, but the, the ultimate commonality that I've seen across, you know, multiple industries is that, you know, when you, when we're in that pandemic state, digital services were the only way that they, their customers were interacting with, with them. So, you know, when you, when you're looking at a, at a bank or you're looking at a, you know, different types of travel agencies and organizations that, you know, like rural Caribbean as well, that, that really had that opportunity to, to focus on what's the most valuable thing to them, which is user experience. It's a very, very common common trend that we saw. And, you know, you see an expedited path of, of, of digital transformation happen. And really that's where we partner with, you know, customers like Royal Caribbean and, and many others across different industries to make sure that that, that the, the business outcomes were being driven towards the, the proper direction. As well as that, you know, the, the user experience, and I don't think I can emphasize user experience as being so critically important anymore than I've already have, but it's really the, one of the most valuable currencies most organizations have. >>I, one of my favorite lines is, is community is your first defensible asset. And you know, I, you can, you can talk about user experience as much as you want on here. At the end of the day, if people aren't having a positive interaction with your brand or your product, it's probably not going to last super long unless it's legacy. And we won't have to go down that rabbit hole today, >>Especially if I can add there's a lot of competition there. Course, right? There's a lot of competition out there. So if your applications do not perform, or your digital services do not perform, the end user has the quick ability to just quickly delete and move on. And, and the same thing with, with what Alice sees in the, in the cruise industry, you know, you have an opportunity to rise to the top and I, I really applaud them for taking advantage of that, that opportunity. Community. >>Community. Yeah. Well, I'm, I'm here for both of you cheering each other on certainly the, the water level rises together. That's >>Right. Alice, >>What sort of, what sort of challenges are you taking on currently that you're able to disclose? What, what sort of leaps do you think, or doesn't have to be leaps, but what, what kind of experience are you hoping to continue to enhance for Royal Caribbean customers? >>So I think, you know, one of our big challenges that we've, you know, we've announced that we do have a relationship with starlink, so that's going to improve our satellite connectivity, and it really is a game changer for our industry. It's very exciting and, and, but it puts the, it puts the user back in the forefront once again. You know, right now, you know, with our current connectivity, it's all about managing that bandwidth. You know, we're hoping to go to that state where bandwidth isn't at a high cost, so now we're gonna be even able to watch our user interaction more from ship to shore, you know, and you're, and you're, we're maybe moving to that area where we're thinking cloud first from a shift. If you think about it, we've got 50 plus data centers floating around the world, so that connectivity is key. Now we're opening up that bandwidth now I need to see how that, how the transactions are performing as we come off ship. You know, with that, once again, that cloud first mentality, it's a super exciting time for us. And I really see, you know, AppD is gonna play a role in that. >>I, I I, I love that visual just for a second of 50 data centers with also surrounded by people having a very wonderful time on board. What a, what a nice spot. I, I can't say that every data center I've ever been to is, is glamorous, fun or sexy as being on a Royal Caribbean ship. However, I, I hope that we move perhaps in that direction. We were just at super computing a few weeks ago and it was great to see all the hardware there. So you never know. What role do you see yourself in the team and, and Cisco app Dynamics playing in that future for companies like Royal Caribbean, Greg? >>You know, it's really, it's really staying right lockstep with our customers as they move through that digital transformation efforts. The key piece is that we look at it from that full stack view. So we offer full stack observability, which, you know, if you look at the challenges that we want to go after is traditional IT departments were historically siloed pretty significantly between, you know, network and infrastructure security app dev. So ensuring that we can get our customers to, to be able to have that common view that shows what's the real important pieces across all domains. So when they start moving down the path of digital transformation, that's an opportunity to also revamp how their processes are that people interact and the technology that they use to be able to deliver the proper business outcomes. So we talk a lot with our customers around full stack observability, but the key part is business context. >>So if you have a big effort for digital transformation, you're starting to add new services to it, how do you know if it's actually impacting the business in a positive or negative way? So by us implementing the, the business context to ensure that you understand the investments being made that you can show to your business leaders is showing an uptick and the business outcomes you're, you're going after, it's really, really about a strong partnership with our customers, but also ensuring that their business is being positively impacted by our technology to be able to help them really align the teams and be able to have the right desired outcomes. >>I love that Greg and I love that customer first. That community first attitude, it's something that you both share. Final question for the two of you, and I'm gonna start with you, Alice, since I suspect you've probably been on more cruises than Greg and I combined, though I could be making a wild assumption. Where are you cruising to next? >>You know, I just got off the cruise, so next up I wanna revisit the Galapagos. I think the Galapagos is the best place to go, and if you haven't done it, that's absolutely where you should go. >>Oh, it's a beautiful trip. Greg, have you ever done the Galapagos? Is that gonna be your next Royal Caribbean cruise? >>I have never done the Galapagos, but I may just have made it to my list. >>Fantastic. Well, I second Alice's endorsement on that. I, I had the pleasure of going about a decade ago. Very magical place that teaches you a lot about nature, much like the two of you have taught us very extensively about full stack absorbability, how it applies to user experience, customer experience, and the ocean that I am currently staring at here in Pacifica, California. Alice, thank you so much for joining us from Miami Greg to you in Colorado. I hope that you both continue to work in harmony together and that we can all see each other on the friendly sees soon. Thank you all for tuning in to our AWS reinvent coverage. This is the cube. My name's Savannah Peterson, and we look forward to seeing you for our next segment.

>>Hey everyone. Welcome back to Chicago. The Cube is excited to be live on day two of Ansible Fest, 2022. Lisa Martin and John Fur. You're here having some great conversations, a lot of cube alumni, a lot of wisdom from the Ansible community coming at you on this program this week. You know, John, we've been, we've been hearing stories about the power and the capabilities and the collective wisdom of the Ansible community. You can feel it here. Yeah, there's no doubt about that. It's, Ansible is nothing, as Stephanie Chair said yesterday, if not a community and the significant contributions that it makes over and over again, or it's fuel. >>I mean the power of the community is what drives Ansible is gonna drive the future of, I think, cloud in our next generation modern application environment. And it's collective intelligence. It's a production system at the end of the day. And I think these guys have harnessed it. So it should be a really great segment to talk about all the contributor work that's been done. So I'm looking forward to it. >>We've got two great alumni here to talk about the contributor work, how you can get involved. Please welcome back to the cube. Carol Chen, principal community architect at Red Hat. Adam Miller joins us as well, fresh from the keynote stage senior principal software engineer at Red Hat. Guys, great to have you on the cube. Great to be here. Yeah, thank you. So we, we talked, we enjoyed your keynotes, Adam, and what you were talking about on stage, the Ansible contributor summit. That's, you guys have been doing what, this is the seven you've had seven so far in just a couple of years. >>Well, we had seven virtual contributor summits. >>Seven virtual. This is the first Monday was the first in person in. >>First in person since the pandemic and actually the 15th contributor summit overall >>15th overall. Talk about the contributor summits, what the contributors are able to do and the influence that it's having on Ansible Red Hat and what people are able to do with cloud. At the Edge automation. Yeah. >>So our community contributors have always had ways to influence and contribute to the project. But the contributor Summit is really a place where we can get people together, preferably in the same place so that we can, you know, have a really great dynamic conversations and interactions. But we also want to make sure that we don't leave out people who have been constantly online joining us. So this year we are so happy to be here in Chicago in person. We've had about 60 to 70 here joining us. And at first I thought maybe we'll have one third of the attendees joining online because about 30 to 40 people signed up to join online. But in the end, we have more than 100 per people watching our live stream. So that's more than half of the attendees overall, were joining us online. So that really shows where, you know, the contributors are interested in participating for >>Develop. Right. Yeah, it's been, it's been interesting. It's been since 2019, since the in-person Ansible Fest in Atlanta. Now we're in Chicago, we had the pandemic. Couple interesting observations from our side that I wanna get your reaction to Adam Carol. And that is one Ansible's relevance has grown significantly since then. Just from a cloud growth standpoint, developer open source standpoint, and how people work and collaborate has changed. So your contributor based in your community is getting more powerful in scope, in my opinion. Like in, as they become, have the keys to the kingdom in the, in their respective worlds as it gets bigger and larger. So the personas are changing, the makeup of the community's changing and also how you guys collaborate is changing. Can you share your, what's going on with those two dynamics? Cause I think that power dynamic is, is looking really good. How are you guys handling >>That? Yeah, so I mean, I, I had the opportunity to represent the community on stage yesterday as part of the keynote and talk to this point specifically is one of the things that we've seen is the project has had the opportunity to kind of grow and evolve. There's been certain elements that have had to kind of decompose from a technology perspective. We actually had to kind of break it apart and change the architecture a little bit and move things into what are called Ansible collections, which, you know, folks here are very familiar with No One Love. And we've seen a lot of community work in the form of working groups coalesce around those organically. However, they've done so in kind of different ways. They, they pick tools and collaboration platforms that are popular to their subject matter expertise audience and things like that. So we find ourselves in a place where kind of the, the community itself had more or less segmented naturally in a way. And we needed to find ways to, you know, kind of ke that >>Fragmentation by demographics or by expertise or both as >>A Mostly, mostly expertise. Yeah. And so there was a open source technology called Matrix. It is a open source, standardized, federated messaging platform that we're able to use to start to bridge back some of those communities that have kind of broken off and, and made their their own home elsewhere on the internet. So now we're able to, for example, the right, the docs organization, they had a, a group of people who was very interested in contributing to the Ansible documentation, but they'd already self-organized on Discord. And what was interesting there is the existing team for the Ansible documentation, they were already on internet Relay Chat, also known as irc. And Matrix allowed us to actually bring those two together and bridge that into the other matrix cha chat channels that we had. So now we're able to have people from all over the world in different areas and different platforms, coalesce and, and cross. It's like a festival cross pollinate. Yeah. >>And you're meeting the contributors exactly where they are and where they want to be, where they're comfortable. >>Yes. Yeah, we always say we, we reach out to where they are. So, >>And, and, and much in the way that Ansible has the capability to reach out to things in their own way, Right. And allow that subject matter expertise to, you know, cause the technology has the potential and possibility and capability to talk to anything over any protocol. We're able to do, you know, kind of the same thing with Matrix, allowing us to bridge into any chat platform that it has support for bridging and, and we're able to bring a lot of people >>Together. Yeah. And how's that, how's the feedback been on that so far? >>I, I think it has been very positive. For example, I want to highlight that the technical writers that we have contributing via Discord is actually a group from Nigeria. And Dave also participated in the contributor summit online virtually joining us in, in, you know, on the matrix platform. So that, that bridge that really helps to bring together people from different geographical regions and also different topics and arenas like that. >>So what were some of the outcomes of the contributor summit? The, the first in person in a while, great. That you guys were able to do seven virtually during the pandemic. That's hard. It's hard to get people together. You, there's so much greatness and innovation that comes when we're all together in person that just can't replicate by video. You can do a lot. Right. But talk about some of the outcomes from Monday. What were some of the feedback? What were some of the contributions that you think are really going to impact the community? >>I think for a lot of us, myself included, the fact that we are in person and meeting people face to face, it helps to really build the connections. And when we do talk about contribution, the connection is so important that you understand, well this person a little bit about their background, what they've done for the SPO project and or just generally what, what they're interested in that builds the rapport and connection that helps, you know, further, further collaboration in the future. Because maybe on that day we did not have any, you know, co contributions or anything, but the fact that we had a chance to sit together in the same place to discuss things and share new ideas, roadmaps is really the, the kind of a big step to the future for our community. Yes, >>Yes. And in a lot of ways we often online the project has various elements that are able to function asynchronously. So we work very well globally across many time zones. And now we were able to get a lot of people in the same place at the same time, synchronously in the same time zone. And then we had breakout sessions where the subject matter, you know, working groups were able to kind of go and focus on things that maybe have been taking a little while to discuss in, in that asynchronous form of communication and do it synchronously and, you know, be in the same room and work on things. It's been, it's been fantastic >>Developers there, like they, they take to asynchronous like fish to water. It's not a problem. But I do want to ask if there's any observations that you guys have had now that we're kind of coming out of that one way, but the pandemic, but the world's changed. It's hybrid, hybrid work environment, steady state. So we see that. Any observations on your end on what's new that you observed that people are gravitating to? Is there a pattern of styles is or same old self-governing, or what's new? What do you see that's coming out of the pandemic that might be a norm? >>I I think that even though people are excited to get back in person, there are, things have changed, like you said, and we have to be more aware of, there are people who think that not be in person, it's okay. And that's how they want to do it. And we have to make sure that they, they are included. So we, we did want to make a high priority for online participation in this event. And like I said, even though only 4 30, 40 people signed up to join us online initially, so that it was what we were expecting, but in the end, more than 100 people were watching us and, and joining participation in >>Actually on demand consumption be good too, >>Right? Yeah. So, you know, I think going forward that is probably the trend. And as, as much as we, we love being in person, we, we want this to continue that we, we take care of people who are, has been constantly participating online and contributing you >>Meaning again, meaning folks where they are, but also allowing the, the, those members that want to get together to, to collaborate in person. I can only imagine the innovation that's gonna come even from having part of the back, Right. >>And, and not to continue to harp on the matrix point, but it, it's been very cool because Matrix has the ability to do live video sessions using open source another to open source technology called jy. So we're able to actually use the same place that we normally find ourselves, you know, congregating and collaborating for the project itself in an asynchronous and, you know, somewhat synchronous way to also host these types of things that are, are now hybrid that used to be, you know, all one way or all the other. Yeah. And it's been, it's >>Been incredible. Integration is, the integration is have been fascinating to watch how you guys do that. And also, you know, with q we've been virtual too. It's like, it's like people don't want another microsite, but they want a more of a festival vibe, a hub, right? Like a place to kind of check in and have choice, not get absolutely jammed into a, you know, forum or, you know, or whatever. Hey, if you wanna be on Discord, be on Discord, right? Why >>Not? And we still, you know, we do still have our asynchronous forms of >>Work through >>Our get GitHub. We have our projects, we have our issues, we have our, you know, wiki, we have various elements there that everybody can continue to collaborate on. And it's all been, it's all been very good. >>Speaking of festivals, octoberfest that's going on, not to be confused with Octoberfest, that was last month. Talk about how the Ansible project and the Ansible community is involved in Octoberfest. Give us the dates, Carol. So >>YesTo Fest is a annual thing in October. So October Octoberfest, I think it's organized by Digital Ocean for the past eight or nine years. And it's really a, a way to kind of encourage people to contribute to open source projects. So it's not anal specific, but we as an Ansible project encourage people to take this opportunity to, you know, a lot of them doing their first contributions during this event. And when, when we first announced, we're participating in Octoberfest within the first four days of October, which is over a weekend actually. We've had 24 contributions, it, 24 issues fixed, which is like amazing, like, you know, just the interest and the, the momentum that we had. And so far until I just checked with my teammates this morning that we've had about 35 contributions so far during the month, which is, and I'm sorry, I forgot to mention this is only for Ansible documentation. So yeah, specifically. And, and that's also one thing we want to highlight, that contributions don't just come in code in, you know, kind of software side, but really there's many ways to contribute and documentation is such a, a great way for first time users, first time contributors to get involved. So it's really amazing to see these contributions from all over the world. And also partly thanks to the technical writers in Nigeria kind of promoting and sharing this initiative. And it's just great to see the, the results from that. Can >>You double click on the different ways of contribution? You mentioned a couple documentation being one, code being the other, but what is the breadth of opportunities that the contributors have to contribute to the project? >>Oh, there's, there's so many. So I actually take care more of outreach efforts in the community. So I helped to organize events and meetups from around the world. And now that we're slowly coming out of the pandemic, I've seen more and more in person meetups. I was just talking to someone from Minneapolis, they're trying to get, get people back together again. They have people in Singapore, in Netherlands from pretty much, you know, all corners of the globe wanting to form not just for the Ansible project, but the local kind of connection with the re people in the region, sometimes in their own language, in their local languages to really work together on the project and just, >>You know, you to create a global Yeah. Network, right? I mean it's like Ansible Global. >>Exactly. >>Create local subnets not to get all networking, >>Right? >>Yeah. >>Yeah. One, one quick thing I want to touch on Theto Fest. I think it's a great opportunity for existing contributors to mentor cause many people like to help bring in new contributors and this is kind of a focal point to be able to focus on that. And then to, to the the other point we, you know, it, it's been, it's been extremely powerful to see as we return these sub communities pop up and, and kind of work with themselves, so on different ways to contribute. So code is kind of the one that gets the most attention. I think documentation I think is a unsung hero, highly important, great way. The logistical component, which is invaluable because it allows us to continue with our adoption and evangelization and things like that. So specifically adoption and evangelize. Evangelization is another place that contributors can join and actually spawn a local meetup and then connect in with the existing community and try to, you know, help increase the network, create a new subject. Yeah. >>Yeah. Network affects huge. And I think the thing that you brought up about reuse is, is part of that whole things get documented properly. The leverage that comes out of that just feeds into the system that flywheel. Absolutely. I mean it's, that's how communities are supposed to work, right? Yep. Yes. >>That's what I was just gonna comment on is the flywheel effect that it's clearly present and very palpable. Thank you so much for joining John, me on the program, talking about the contributors summit, the ways of contribution, the impacts that are being made so far, what Octoberfest is already delivering. And we're, we still have about 10 days or so left in October, so there's still more time for contributors to get involved. We thank you so much for your insights and your time. Thank >>You. Thank you so much for having us. >>Our pleasure. For our guests and John Purer, I'm Lisa Martin. You're watching The Cube Live from Chicago, day two of our coverage of Red Hat Ansible Summit 22. We will see you right n after this short break with our next guest.

(soft electronic music) >> Hey, everyone. Welcome to Miami. I feel like I should be singing that song. Lisa Martin here live with theCUBE at IFS Unleashed. We've been here all day having great conversations with IFS executives, their customers, their partners, lots a... You can hear probably the buzz behind me at the vibe here. Lot of great folks, 1500 plus here. People are excited to be back and to see what IFS has been up to the last few years. I'm pleased to welcome back one of our alumni who was here with us last time we covered IFS, Marne Martin joins us. The president, Service Management, EAM and Global Industry at IFS. Marne, it's great to have you back on theCUBE. >> Yeah, I'm so happy to be here, and thanks for joining us in Miami. Last time it was Boston. >> That's right. >> So definitely much warmer climate this time. >> Much warmer. (Marne laughs) Yes, much warmer. And people here are just smiles on faces. People are excited to be back. There's... But I shouldn't elude that IFS slow down at all during the pandemic. You did not. I was looking at the first half, 2022 financials that came out over the summer and AR are up 33%. So much recurring revenue as well. So your... The business is doing incredibly well. You've pivoted beautifully during the pandemic. Customers are happy. There's a lot of customers here. You guys talk a lot about the moment of service. I love that. Talk to the audience about what that is, and how you're enabling your customers to deliver that to their customers. >> Definitely. So, you know, it's amazing when you have these inflection points and it's a good opportunity, world conference to world conference to celebrate that. We've grown a lot, and the number of customers we've brought in, in tier one global customers as well as in our variety of the various regions around the world and different industry verticals is amazing. And, you know, the participation is what's making IFS be a better company, a better technology vendor as we focus on these industries. So is understanding moment of service. You know, we talk a lot, and certainly CIOs and IT buyers will talk about technology, but putting the technology to work has to be meaningful, not only to the returns that go to shareholders, but what it matters, what matters to the end customers, of our customers. And when we started thinking about the new branding of IFS, because we also rebranded in this time, we thought, "How does that mission crystallize in what we're doing for our customers, and how do we really start put bringing technology to life?" And that is where moment of service came. So it's very rare in our world that you actually come up with a sort of slogan or an objective as a company that not only mobilizes what we do internally here at IFS, delivering great moments of service to our customers, but also that tells a story of the customers to the end customer. You know, service, an area that I work in a lot, it's very obvious that you... We all know when we get a great moment of service, or sometimes a bad moment of service. So if you talk to service organizations, field service organizations, they understand what a moment of service is. But it's also thinking about how we enable the people delivering that great moment of service. Not just like doing a survey or what have you, but what are the digital tools that help them to deliver better moments of service proactively. >> Right. >> One of my pet peeves was always that even like, if you have a voice of the customer program or what have you, that you may get that reactive feedback perhaps to a CMO in an organization, but the insights don't really get actioned. So here, across the line of business applications that we sell, ERP Service Management, EAM, ITSM, or ESM, we're really thinking about with that moment of service, the objective of putting the technology to work. How do we facilitate that alongside the business growth of our customers, but also how do we take the insights they get from their end customers into the business models as well as the functional design, what we develop. So moment of service has become, say the heart of IFS as well as a way of understanding our customers better. >> Really understanding them at much deeper level- >> Correct. Correct. >> And a lot of organizations. Give me some examples of some of the insights that IFS has gleaned from its customers. How you've brought them internally to really evolve the technology. >> So I think what's important is a lot of times technology vendors may say they know their customers, right? If you think about what technology vendor we know with the 360 view of the customer. You know, understanding the customer is a lot more than understanding their renewal date as a software vendor. >> Yeah. (laughs) >> So we have to really think about the moments of service on what matters most at that point of service, right? And it will vary certainly by industry, but there also will be certain things that are very much the same. Like for example, if we, as a customer, can have an asset or a piece of equipment that never breaks, we're a happier customer. If it does break, we, of course, want it to be fixed the first time someone shows up. So those are the obvious things. But how you then fix or manifest that into a different way of utilizing and implementing the technology. Thinking also about taking the operational insights that you have on driving, what we call preventative or predictive maintenance, or maximizing what's called a first time fixed resolution. You know, being able to marry best practices with at times artificial intelligence and machine learning information, with also the operational and personal insights of the people doing the work really enriches the quality of the insights you have around that moment of service and how to recreate a great moment of service, or lessen a poor moment of service. >> Yeah. >> And it also changes a view of what are often IT-driven projects into what's the user feedback that also matters most to enable that. You know, with the talent shortage that we're seeing, you know, customer expectations have only increased. >> Yes. >> So we all know, and customers want great moments of service, but how do we enable the frontline workers, whether they're field service workers or others, to deliver against these expectations when they might be harried, and you know, having to do a lot more work because of talent shortage. So we want to think about what their needs are in a way that's more focused towards delivering that moment of service, that great customer experience. And of course, that always feeds back into brand loyalty, selling more profits, but really getting into it. And you know, the advantage of IFS is that we understand the domain expertise to do things from a UI UX, a business process, but also thinking about how we're developing, to answer your question, the artificial intelligence machine learning. Even thinking about how you put IoT to work in ways that really matter, because there's a lot of money spent on IT projects that actually don't deliver great moments of service, let alone actual business value. >> Right. I love the vertical specialization that IFS has. I was interviewing Darren Roos, your CEO, a little bit earlier today and I said, "You know, we see so many companies... So many vendors, like some of your competitors in the ERP Space, which whom you're outgrowing or growing faster than, or horizontally focused. And the vertical specialization that he was kind of describing how long it's been here really allows IFS to focus on its core competencies. But another thing that I'm hearing throughout the interviews I'm having today, and you just said the same thing, is that you're not just, "We need to meet the customer where they are." Everyone talks about that. You've actually getting the... You're developing and fostering the domain expertise. >> Yes. >> So whether you're talking with an energy company, aerospace and defense company, manufacturing, there's that one to one knowledge within IFS and its customer, or based in that industry that it can only imagine is maybe part of what's leading to, you know, that big increase in ARR that I talked about, the recurring revenue being so high. That domain expertise seems to be a differentiator from my lens. >> Well, let's even talk about how people build relationships, right? You know, we're having a conversation, so we're already having a higher value relationship, right? And that comes through with how vendors engage with their customers. You know, when you have seen your executives like Darren and myself, and Michael and Christian, who still care and really focus on what is most impactful. What is that moment of service? I'm sure Darren talked about the great moment of service book that we just released. >> Yes. >> So understanding at a more visceral and may I say, intimate moment with the customers, what matters most to them. And really working with what are developing, what we call the digital dream team within these customers that understand enough of where they're going in the objective, enables us to do a better job. And it's also where then, it's not only how we're partnering in the sales process implementation in the conventional ways, but product management. What is the most meaningful? How can we prioritize what makes the most impact? Obviously, there's cool stuff we want to do too, but you know, we really think about understanding the verticals and understanding where they're going. And you see that, for example, we're an absolute leader in mobile workforce management specifically, where we have what's called real time optimization. Super hard to do. No one else does it anymore except us. Great. There's other things where you'd say that, "Hey, some of the other vendors talk about this, right?" APM as a performance management or other things, but because they lack the true vertical specialization and the use cases and the ease to put it in, the adoption rate is low. >> Yeah. >> So, you know, in that case, APM might not be something we do only, but if we can actually help commercialize this, something that has a great deal of value in a superior way in that focus verticals, that's what it means to have industry specialization. Because if you spread yourself too thin, you know then, you'll end up with an AI or machine learning platform or something like that that you know, most companies don't have five years to try and configure, build out a Watson or something like that. I mean, most companies in this day and age, with the requirements of competitive pressure and supply chain pressures have to be nimble and have to be getting results fast. So the closest with the customers, the domain expertise, the understanding of what matters most, helps us to be faster to the value outcomes that our customers needs. It helps us to be more focused in what we're developing and also how we're developing. And ultimately, that does benefit us that, you know, we want to make sure that we're not only leading today, but you know, staying ahead of the game in the next 5 to 10 years, which will help us to grow. You know, we're certainly not a small company anymore. We're at a billion in revenue looking to be 2 billion and eventually 5 billion in revenue. >> Okay. >> So that already, you know, puts us well beyond unicorn status into one of the very few. But, you know, we want to take a different track even of how a service now or a sales force or SAP or even, you know, to some degree workday grew by making sure that we remain focused on these key verticals and not lose our focus. And they're plenty big enough verticals for us to achieve our growth goals. >> Well the growth has been impressive, as I mentioned the ARR app in the first half, and I was chatting with Darren earlier as I said, and I said, "Can you gimme any nuggets for a second half?" I imagine the trajectory is up onto the right. And he alluded to the fact that things are going quite well, but the focus there that you have with customers. Also, you talked about this and I had several customers on the program today. Rolls-Royce was here. Aston Martin was here. And it's very obvious that there is a... There was a uniqueness about the relationship that I saw- >> Yes. >> Especially with Rolls-Royce that I thought was quite, I mean, you talked about kind of that customer intimacy and that personalization, which people used to tolerate fragmented experiences. We don't tolerate those anymore. >> No. >> Nobody has the patience for that. >> No. And it's also, you know, this business isn't easy for a lot of these customers to stay ahead, right? You know, especially if you think about a tier one customer that's at the top of their category. How did they continue to innovate? And Rolls Royce and Aston Martin are really cool customers. You know, but we're also thinking about, you know, what are the up-and-comers? Or you know, we also get customers that have come to us because they've started falling behind in their sector because they haven't been able to digitalize and grow forward. You know, we work a lot with SAP customers. Darren, of course, came from SAP. But in that ecosystem and especially in the areas I work in a lot with service management, SAP customers, you know, that are focusing on ERP, you know, SAP hasn't been a great enabler of service management for them. So the SAP customers have actually fallen behind. And the ability to come to a lot of these new type of digitally based value-based service offerings really make aftermarket service revenues a lifeblood of their company. So even there where, you know, we might have in a different ERP choice, we're able to provide what's really the missing link for these tier one companies that they can't get anywhere else. And we see this also, you know, you've obviously Salesforce and CRM. A lot of Salesforce CRM customers. Microsoft with Dynamics also primarily ERP. But the focus and the specialization that we have is rare in the industry, but it's so impactful. >> Yeah. >> And you know, I would even venture to say that there's not a tier one company that has a lot of aftermarket service revenue, or attention on service revenue, or even that is trying to monetize their connected asset or IoT investment that can ignore IFS. >> Yeah. >> Because we are unique enough in our focus verticals that if they want to continue growing and that is a cornerstone of their growth, their customer, their moment of service, then they definitely need to look at IFS. >> Absolutely. Does IFS care that it's not as well known of a brand? I mean, I mentioned you guys are growing. Maybe I didn't mention this, number three in ERP, you are growing faster than the top two biggest competitors, which you mentioned SAP, Oracle as well, but those implementations can be quite complex. Does IFS care that you're doing so well? Darren talked about where you're winning, how you're being competitive, where you went. Do they care about being a big name brand, or is that really kind of not as important nearly as delivering those moments of service? >> So, you know, it's a mirrored question that you asked me, and therefore, I'll give you a multifaceted answer. (Lisa laughs) You know, ERP, we're very proud to be a top three vendor and I think over time we'll continue to dislodge SAP and Oracle in ERP, where companies want to make a different ERP choice, or they're consolidating or whatever. I think already in field service management, we're by far the number one and will continue to be that. And you actually see a lot of our ERP competitors that are dropping down and you seem a... There's not really a lot of what I'd call best-of-breed options other than IFS as well. So... And then enterprise asset management, I really think the opportunity for IFS is how we put technology to work in some of these advanced capabilities in ways that can be automated that is, for example, in IBM Maximo or Watson or what have you haven't been able to be. And then you have some other best-of-breed EAM customers that have kind of not continued innovating and things like that. So the lines where we are really building the brand recognition with the largest companies in the world might be anchored for now more around field service management, enterprise asset management. But of course that brand recognition comes back into ERP. >> Yeah. >> And there will be, you know, as we continue to innovate, as people make ERP decisions every 5, 7, 10 years as those buying cycles are, then it's important that we're using the leadership positions we have. And especially, you know, thinking about these verticals where the asset centric service nature is paramount to them either to meet their moment of service, or to meet their aftermarket service revenue goals that we get the recognition of IFS as being the leader. And all the, you know... And this is where I'll go to the next layer of your question that building that is something I pride myself on and I'll say that we're building the IFS brand recognition at three different levels. >> Okay. >> There's the C-level and the board level, which I'd say my top participation in Darren's keynote this morning was more targeted to messages that would go, you know, "How are you a smarter digital business? How does IFS help you to be that?" >> Yeah. >> Okay. Then we have the operational or kind of the doers in a digital dream team that are below C-level, maybe VPs or directors or SVPs, that actually have the objective of bringing in the new business models, the operational change, the new technology, putting it to work. And there, you know, you have aspects of what do they need now versus how do they change and how do they continue innovating in a way that is easy as possible. >> Yeah. >> And then you definitely need to focus also on the people that are hands-on with those end customers. >> The practitioners. Yeah. >> The people that not only are told about the moment of service, but live the moment of service, right? The actual users in the field. Maybe the dispatchers, you know, the people that are doing the maintenance or the service or things like that. So the domain expertise in how we build the brand recognition has to be in all those three constituencies. We want to make sure that the CEO and the board members know who IFS is. We want to make sure that the operational leaders and the IT leaders who actually are delivering the project trust us to deliver. >> Right. >> And are confident in our ability to deliver with our ecosystem. And then we want to make sure that we're delighting those users of the software that they can deliver the moment of service, not just the business value that we all want from technology, but really that we're enabling them to have a solution that they love. That they can enjoy doing their job, or at least feel that they're doing their job in a way that's helpful to them. >> Right. >> And that ties into the end customers getting the moment of service that we all want. >> Absolutely. Well, very much aligned with what I heard today. It sounds like there's a rock solid strategy across the board at IFS and you... Congratulations on the work that you've done to help put that in place and how it's been evolving. I can only imagine that those second half numbers are going to be fantastic. So we'll have to have you back on the show next year (Marne laughs) to see what else is new. >> Yeah, I can't wait. It's an absolute pleasure and- >> Likewise. >> You know, and really, we're so passionate about what we do here. >> Yes. >> You know, I think just as a final note, as we grow, we want to make sure that doubling the company, doubling the number of customers, that our customers still feel that intimacy and that care. >> Yes. >> Right? >> Yes. >> That they can access senior executives that aren't clueless about their used cases and their vertical and actually have the ability to help them. You know, one of the things I pride myself on is that we... Okay, ideally people choose IFS in the first instance. We have successful projects and move on. Sometimes though, we're taking failed projects from other vendors. >> Yes, right. >> And what I pride myself on, and we all do here at IFS, is that we get those projects live, with those customers live. You know, we have the grit. We have the domain expertise, we see it through. And that even if customers have failed to get the business value or the transformation, you know, in the areas that we specialize at IFS, they can come here and we get it done. >> Right, you got a trusted partner. >> And that's something- Yes, and that, you know, I know every vendor says that- >> They do, but- >> But the reality is that we live it. >> Yeah. >> And it doesn't mean we're perfect. No vendor's perfect. But you know, we have the dedication and the focus and the domain expertise to get it done. And that's what's ultimately driving us into these leadership positions, changing how IFS is viewed. You know, we have people now that are coming to IFS that are saying, "IFS is the only choice in service management if you really want to do this work." And, you know, again, we have to keep earning it. But that's great. >> Exactly. Well, congratulations on all of that. That customer intimacy is a unique differentiator, and it's something that is... It's very... It's a flywheel, right? It's very synergistic. We appreciate your time and your insights for joining us on the program today. Thank you, Marne. >> Absolutely a pleasure. Thank you so much for coming. >> Mine as well. For Marne Martin, I'm Lisa Martin. No relation. (Marne laughs) You're watching theCUBE live from Miami at IFS Unleashed. I'll be back after a short break, so don't go too far. (soft electronic music) (soft electronic music continues)

foreign greetings from San Francisco thecube is live this is our second day of wall-to-wall coverage of VMware Explorer 2022. Lisa Martin and Dave Nicholson here we're going to be talking with some ladies from Rackspace next please welcome Adriana Bustamante VP of strategic alliances and Hannah Deuce director of strategic alliances from Rackspace it's great to have you on the program thank you so much for having us good afternoon good morning is it lunchtime already almost almost yes and it's great to be back in person we were just talking about the keynote yesterday that we were in and it was standing room only people are ready to be back they're ready to be hearing from VMware it's ecosystem its Partners it's Community yes talk to us Adriana about what Rackspace is doing with Dell and VMware particularly in the healthcare space sure no so for us Partnerships are a big foundation to how we operate as a company and um and I have the privilege of doing it for over over 16 years so we've been looking after the dell and VMware part partnership ourselves personally for the last three years but they've been long-standing partners for for us and and how do we go and drive more meaningful joint Solutions together so Rackspace you know been around since since 98 we've seen such an evolution of coming becoming more of this multi-cloud transformation agile Global partner and we have a lot of customers that fall in lots of different verticals from retail to public sector into Healthcare but we started noticing and what we're trying trying to drive as a company is how do we drive more specialized Solutions and because of the pandemic and because of post-pandemic and everyone really trying to to figure out what the new normal is addressing different clients we saw that need increasing and we wanted to Rally together with our most strategic alliances to do more Hannah talk about obviously the the pandemic created such problems for every industry but but Healthcare being front and center it still is talk about some of the challenges that Healthcare organizations are coming to Rackspace going help yeah common theme that we've heard from some of our large providers Healthcare Providers has been helped me do more with less which we're all trying to do as we navigate The New Normal but in that space we found the opportunity to really leverage some of our expertise long-term expertise and that the talent and the resource pool that we had to really help in a some of the challenges that are being faced at a resource shortage Talent shortage and so Rackspace is able to Leverage What what we've done for many many years and really tailor it to the outcomes that Health Care Providers are needing nowadays that more with less Mantra runs across the gamut but a lot of it's been helped me modernize helped me get to that next phase I can't I can't I don't have the resources to DIY it myself anymore I need to figure out a more robust business continuity program and so helping with business continuity Dr you know third copies of just all all this data that's growing so it's not just covered pandemic driven but it's that's definitely driving the the need and the requirement to modernize so much quicker it's interesting that you mentioned rackspace's history and expertise in doing things and moving that forward and leveraging that pivoting focusing on specific environments to create something net new we've seen a lot of that here if you go back 10 years I don't know if that's the perfect date to go back to but if you go back 10 years ago you think about VMware where would we have expected VMware to be in this era of cloud we may have thought of things very very differently differently Rackspace a Pioneer in creating off-premises hey we will do this for you didn't even really call it Cloud at the time right but it was Cloud yeah and so the ability for entities like Rackspace like VMware we had a NetApp talking to us about stuff they're doing in the cloud 10 years ago if you I would say no they'd be they'll be gone they'll be gone so it's really really cool to see Rackspace making this transition and uh you know being aware of everything that's going on and focusing on the best value proposition moving forward I mean am I am I you know do I sound like somebody who would who would fit into the Rackspace culture right now or do I not get it yes you sound like a rocker we'll make you an honorary record that's what we call a Rackspace employees yes you know what we've noticed too and is budgets are moving those decision makers are moving so again 10 years ago just like you said you would be talking to sometimes a completely different Persona than we do than we do today and we've seen a shift more towards that business value we have a really unique ability to bring business and Technical conversations together I did a lot of work in the past of working with a lot of CMO and and digital transformation companies and so helping bring it and business seeing the same and how healthcare because budgets are living in different places and even across the board with Rackspace people are trying to drive more business outcomes business driven Solutions so the technical becomes the back end and really the ingredients to make all of that all of that happen and that's what we're helping to solve and it's a lot it's very fast paced everyone wants to be agile now and so they're leaning on us more and more to drive more services so if you've seen Rackspace evolve we're driving more of that advisement and those transformation service type discussions where where our original history was DNA was very much always embedded in driving a great experience now they're just wanting more from us more services help us how help us figure out the how Adriana comment on the outcomes that you're helping Healthcare organizations achieve as as we as we it's such a relatable tangible topic Healthcare is Right everybody's everybody's got somebody who's sick or you've been sick or whatnot what are some of those outcomes that we can ex that customers can expect to achieve with Rackspace and VMware oh great great question so very much I can't mentioned earlier it's how do I modernize how do I optimize how do I take the biggest advantage of the budgets and the landscape that I have I want to get to the Cloud we need to help our patients and get access to that data is this ready to go into the cloud is this not ready to go into the cloud you know how do we how do we help make sure we're taking care of our patients we're keeping things secure and accessible you know what else do you think is coming up yeah and one specific one uh sequencing genetic sequencing and so we've had this come up from a few different types of providers whether it's medical devices that they may provide to their end clients and an outcome that they're looking for is how do we get how do we leverage um here's rip here's what we do but now we have so many more people we need to give this access to we need them to be able to have access to the sequencing that all of this is doing all of these different entities are doing and the outcome that they're trying to get to to is more collaboration so so that way we can speed up in the face of a pandemic we can speed up those resolutions we could speed up to you know whether it's a vaccine needed or something that's going to address the next thing that might be coming you know um so that's a specific one I've heard that from a handful of different different um clients that that we work with and so trying to give them a Consolidated not trying to we are able to deliver them a Consolidated place that their application and tooling can run in and then all of these other entities can safely and securely access this data to do what they're going to do in their own spaces and then hopefully it helps the betterment of of of us globally like as humans in the healthcare space we all benefit from this so leveraging the technology to really drive a valuable outcome helps us all so so and by the way I like trying to because it conveys the proper level of humility that we all need to bring to this because it's complicated and anybody who looks you in the eye it pretends like they know exactly how to do it you need to run from those people no it is and and look that's where our partners become so significant we we know we're Best in Class for specific things but we rely on our Partnerships with Dell and VMware to bring their expertise to bring their tried and true technology to help us all together collectively deliver something good technology for good technology for good it is inherently good and it's nice when it's used for goodness it's nice when it's yeah yeah talk about security for a second you know we've seen the threat landscape change dramatically obviously nobody wants to be the next breach ransomware becoming a household term it's now a matter of when we get a head not F where has security gone in terms of conversations with customers going help us ensure that what we're doing is delivering data access to the right folks that need it at the right time in real time in a secure fashion no uh that's another good question in hot and burning so you know I think if we think about past conversations it was that nice Insurance offering that seemed like it came at a high cost if you really need it I've never been breached before um I'll get it when I when I need it but exactly to your point it's the win and not the if so what we're finding and also working with a nice ecosystem of Partners as well from anywhere from Akamai to cloudflare to BT it's how do we help ensure that there is the security as Hannah mentioned that we're delivering the right data access to the right people and permissions you know we're able to help meet multitude of compliance and regulations obviously health care and other regulated space as well we look to make sure that from our side of the house from the infrastructure that we have the right building blocks to help them Reach those compliance needs obviously it's a mutual partnership in maintaining that compliance and that we're able to provide guidance and best practices on to make sure that the data is living in a secure place that the people that need access to it get it when they when they need it and monitor those permissions and back to your complexity comment so more and more complex as we are a global global provider so when you start to talk to our teams in the UK and our our you know clients there specializing um kind of that Sovereign Cloud mentality of hey we need to have um we need to have a cloud that is built for the specific needs that reside within Healthcare by region so it's not just even I mean you know we're we're homegrown out of San Antonio Texas so like we know the U.S and have spent time here but we've been Global for many years so we just get down into the into the nitty-gritty to customize what's needed within each region well Hannah is that part of the Rackspace value proposition at large moving forward because frankly look if I if I want if I want something generic I can I can swipe credit card and and fire up some Services sure um moving forward this is something that is going to more characterize the Rackspace experience and I and I understand that the hesitancy to say hey it's complicated it's like I don't want to hear that I want to hear that it's easy it's like well okay we'll make it easy for you yes but it's still complicated is that okay that's the honest that's that's the honest yeah that's why you need help right that's why we need to talk about that because people people have a legitimate question why Rackspace yep and we don't I don't want to put you on the spot but no yeah but why why Rackspace you've talked a little bit about it already but kind of encapsulate it oh gosh so good good question why Rackspace it's because you can stand up [Laughter] well you can you do it there's many different options out there um and if I had a PowerPoint slide I'd show you this like lovely web of options of directions that you could go and what is Rackspace value it's that we come in and simplify it because we've had experience with this this same use case whatever somebody is bringing forward to us is typically something we've dealt with at numerous times and so we're repeating and speeding up the ability to simplify the complex and to deliver something more simplified well it may be complex within us and we're like working to get it done the outcome that we're delivering is is faster it's less expensive than dedicating all the resources yourself to do it and go invest in all of that that we've already built up and then we're able to deliver it in a more simplified manner it's like the duck analogy the feet below the water yes exactly and a lot of expertise as well yes a lot talk a little bit about the solution that that Dell VMware Rackspace are delivering to customers sure so when we think about um Healthcare clouds or Cloud specific to the healthcare industry you know there's some major players within that space that you think epic we'll just use them as an example this can play out with others but we are building out a custom or we have a custom clouds able to host epic and then provide services up through the Epic help application through partnership so that is broadening the the market for us in the sense that we can tailor what the what that end and with that healthcare provider needs uh do they do they have the expertise to manage the application okay you do that and then we will build out a custom fit Cloud for that application oh and you need all the adjacent things that come with it too so then we have reference architecture you know built out already to to tailor to whatever all those other 40 80 90 hundreds of applications that need to come with that and then and then you start to think about Imaging platforms so we have Imaging platforms available for those specific needs whether it's MRIs and things like that and then the long-term retention that's needed with that so all of these pieces that build out a healthcare ecosystem and those needs we've built those we've built those out and provide those two to our clients yesterday VMware was talking about Cloud chaos yes and and it's true you talk about the complexity and Dave talks about it too like acknowledging yes this is a very complex thing to do yeah there's just so many moving parts so many Dynamics so many people involved or lack thereof people they they then talked about kind of this this the goal of getting customers from cloud chaos to Cloud smart how does that message resonate with Rackspace and how are you helping customers get from simplifying the chaos to eventually get to that cloud smart goal so a lot of it I I believe is with the power of our alliances and I was talking about this earlier we really believe in creating those powerful ecosystems and Jay McBain former for Forester analyst talks about you know the people are going to come ahead really are serve as that orchestration layer of bringing everybody together so if you look at all of that cloud chaos and all of the different logos and the webs and which decisions to make you know the ones that can help simplify that bring it all together like we're going to need a little bit of this like baking a cake in some ways we're going to need a little bit of sugar we'll need this technology this technology and whoever is able to put it together in a clean and seamless way and as Hannah said you know we have specific use cases in different verticals Healthcare specifically and talking from the Imaging and the Epic helping them get hospitals and different you know smaller clinics get to the edge so we have all of the building blocks to get them what they need and we can't do that without Partners but we help simplify those outcomes for those customers yep so there's where they're Cloud smart so then they're like I want I want to be agile I want to work on my cost I want to be able to leverage a multi-cloud fashion because some things may may inherently need to be on Azure some things we inherently need to be on VMware how do we make them feel like they still have that modernized platform and Technology but still give the secure and access that they need right yeah we like to think of it as are you multi-cloud by accident or multi-cloud by Design and help you get to that multi-cloud by Design and leveraging the right yeah the right tools the right places and Dell was talking about that just that at Dell Technologies world just a couple months ago that most most organizations are multi-cloud by default not designed are you seeing any customers that are are able or how are you able to help customers go from that we're here by default for whatever reason acquisition growth.oit line of business and go from that default to a more strategic multi-cloud approach yes it takes planning and commitment you know you really need the business leaders and the technical leaders bought in and saying this is what I'm gonna do because it is a journey because exactly right M A is like inherited four different tools you have databases that kind of look similar but they're a little bit different but they serve four different things so at Rackspace we're able to help assess and we sit down with their teams we have very amazing rock star expertise that will come in and sit with the customers and say what are we trying to drive for it let's get a good assessment of the landscape and let's figure out what are you trying to get towards in your journey and looking at what's the best fit for that application from where it is now to where it is where it wants to be because we saw a lot of customers move to the cloud very quickly you know they went Cloud native very fast some of it made sense retailers who had the spikiness that completely made sense we had some customers though that we've seen move certain workloads they've been in the public Cloud now for a couple years but it was a static website it doesn't make as much sense anymore for certain things so we're able to help navigate all of those choices for them so it's interesting you just you just said something sort of offhand about having experts having them come in so if I am a customer and I have some outcome I want to achieve yes the people that I'm going to be talking to from Rackspace or from Rackspace and the people from Rackspace who are going to be working with the actual people who are deploying infrastructure are also Rackspace people so the interesting contrast there between other circumstances oftentimes is you may have a Global Systems integrator with smart people representing what a cloud provider is doing the perception if they try to make people perceive that okay everybody is working in lockstep but often there are disconnects between what the real capabilities are and what's being advertised so is that I mean I I know it's like a leading question it's like softball get your bats out but I mean isn't that an advantage you've got a single you know the saying used to be uh one throat to show now it's one back to pack because it's kind of Contour friendly yeah yeah but talk about that is that a real Advantage it does it really helps us because again this is our our this is our expertise this is where we where we live we're really close to the infrastructure we're great at the advisement on it we can help with those ongoing and day two management and Opera in operations and what it feels like to grow and scale so we lay this out cleanly and and clearly as possible if this is where we're really good we can we can help you in these areas but we do work with system integrators as well and part of our partner Community because they're working on sometimes the bigger overall Transformations and then we're staying look we understand this multi-cloud but it helps us because in the end we're doing that end to end for for them customer knows this is Rackspace and on hand and we we really strive to be very transparent in what it is that we want to drive and outcomes so sometimes at the time where it's like we're gonna talk about a certain new technology Dell might bring some of their Architects to the table we will say here is Dell with us we're doing that actively in the healthcare space today and it's all coming together but you know at the end of the day this is what Rackspace is going to drive and deliver from an end to end and we tap those people when needed so you don't have to worry about picking up the phone to call Dell or VMware so if I had worded the hard-hitting journalist question the right way it would have elicited the same responses that yeah yeah it drives accountability at the end of the day because what we advised on what we said now we got to go deliver yeah and it's it's all the same the same organization driving accountability so from a customer perspective they're engaging Rackspace who will then bring in dell and VMware as needed as we find the solution exactly we have all of the certification I mean the team the team is great on getting all of the certs because we're getting to handling all of the level one level two level three business they know who to call they have their dedicated account teams they have engagement managers that help them Drive what those bigger conversations are and they don't have to worry about the experts because we either have it on hand or we'll pull them in as needed if it's the bat phone we need to call awesome ladies thank you so much for joining Dave and me today talking about what Rackspace is up to in the partner ecosystem space and specifically what you're doing to help Healthcare organizations transform and modernize we appreciate your insights and your thoughts yeah thank you for having us thank you pleasure for our guests and Dave Nicholson I'm Lisa Martin you're watching thecube live from VMware Explorer 2022 we'll be back after a short break foreign [Music]

(upbeat music) >> Welcome back everyone to Supercloud22, I'm John Furrier, host of theCUBE here in Palo Alto. For this next ecosystem's segment we have Muddu Sudhakar, who is the co-founder and CEO of Aisera, a friend of theCUBE, Cube alumni, serial entrepreneur, multiple exits, been on multiple times with great commentary. Muddu, thank you for coming on, and supporting our- >> Also thank you for having me, John. >> Yeah, thank you. Great handshake there, I love to do it. One, I wanted you here because, two reasons, one is, congratulations on your new funding. >> Thank you. >> For $90 million, Series D funding. >> Series D funding. >> So, huge validation in this market. >> It is. >> You have been experienced software so, it's a real testament to your team. But also, you're kind of in the Supercloud vortex. This new wave that Supercloud is part of is, I call it the pretext to what's coming with multi-clouds. It is the next level. >> I see. >> Structural change and we have been reporting on it, Dave and I, and we are being challenged. So, we decided to open it up. >> Very good, I would love it. >> And have a conversation rather than waiting eight months to prove that we are right. Which, we are right, but that is a long story. >> You're always right. (both laughs) >> What do you think of Supercloud, that's going on? What is the big trend? Because its public cloud is great, so there is no conflict there. >> Right. >> It's got great business, it's integrated, IaaS, to SaaS, PaaS, all in the beginning, or the middle. All that is called good. Now you have on-premise high rate cloud. >> Right. >> Edge is right around the corner. Exploding in new capabilities. So, complexity is still here. >> That's right, I think, you nailed it. We talk about hybrid cloud, and multi cloud. Supercloud is kind of elevates the message even better. Because you still have to leave for some of our clouds, public clouds. There will be some of our clouds, still running on the Edge. That's where, the Edge cloud comes in. Some will still be on-prem. So, the Supercloud as a concept is beyond hybrid and multi cloud. To me, I will run some of our cloud on Amazon. Some could be on Aisera, some could be running only on Edge, right? >> Mm hm >> And we still have, what we call remote executors. Some leaders of service now. You have, what we call the mid-server, is what I think it was called. Where you put in a small code and run it. >> Yeah. >> So, I think all those things will be running on-prem environment and VMware cloud, et cetera. >> And if you look back at, I think it has been five years now, maybe four or five years since Andy Jassy at reInvent announced Outposts. Think that was the moment in time that Dave and I took this pause back and said "Okay, that's Amazon." who listens to their customers. Acknowledging Hybrid. >> Right. >> Then we saw the rise of Snowflakes, the Databricks, specialty clouds. You start to see people who are building on top of AWS. But at MongoDB, it is a database, now they are a full blown, large scale data platform. These companies took advantage of the public cloud to build, as Jerry Chen calls it, "Castles in the cloud." >> Right. >> That seems to be happening in all areas. What do you think about that? >> Right, so what is driving the cloud? To me, we talk about machine learning in AI, right? Versus clouded options. We used to call it lift and shift. The outposts and lift and shift. Initially this was to get the data into the cloud. I think if you see, the vendor that I like the most, is, I'm not picking any favorite but, Microsoft Azure, they're thinking like your Supercloud, right? Amazon is other things, but Azure is a lot more because they run on-prem. They are also on Azure CloudFront, Amazon CloudFront. So I think, Azure and Amazon are doing a lot more in the area of Supercloud. What is really helping is the machine learning environment, needs Superclouds. Because I will be running some on the Edge, some compute, some will be running on the public cloud, some could be running on my data center. So, I think the Supercloud is really suited for AI and automation really well. >> Yeah, it is a good point about Microsoft, too. And I think Microsoft's existing install base saved Azure. >> Okay. >> They brought Office 365, Sequel Server, cause their customers weren't leaving Microsoft. They had the productivity thing nailed down as well as the ability to catch up >> That's right. >> To AWS. So, natural extension to on-premise with Microsoft. >> I think... >> Tell us- >> Your Supercloud is what Microsoft did. Right? Azure. If you think of, like, they had an Office 365, their SharePoint, their Dynamics, taking all of those properties, running on the Azure. And still giving the migration path into a data center. Is Supercloud. So, the early days Supercloud came from Azure. >> Well, that's a good point, we will certainly debate that. I will also say that Snowflake built on AWS. >> That's right. >> Okay, and became a super powerhouse with the data business. As did Databricks. >> That's right. >> Then went to Azure >> That's right. >> So, you're seeing kind of the Playbook. >> Right. >> Go fast on Cloud Native, the native cloud. Get that fly wheel going, then get going, somewhere else. >> It is, and to that point I think you and me are talking, right? If you are to start at one cloud and go to another cloud, the amount of work as a vendor for us to use for implement. Today, like we use all three clouds, including the Gov Cloud. It's a lot of work. So, what will happen, the next toolkit we use? Even services like Elastic. People will not, the word commoditize, is not the word, but people will create an abstraction layer, even for S3. >> Explain that, explain that in detail. So, elastic? What do you mean by that? >> Yeah, so what that means is today, Elasticsearch, if you do an Elasticsearch on Amazon, if I go to Azure, I don't want enter another Elasticsearch layer. Ideally I want us to write an abstracted search layer. So, that when I move my services into a different cloud I don't want to re-compute and re-calculate everything. That's a lot of work. Particularly once you have a production customer, if I were to shift the workloads, even to the point of infrastructure, take S3, if I read infrastructure to S3 and tomorrow I go to Azure. Azure will have its own objects store. I don't want to re-validate that. So what will happen is digital component, Kubernetes is already there, we want storage, we want network layer, we want VPM services, elastic as well as all fundamental stuff, including MongoDB, should be abstracted to run. On the Superclouds. >> Okay, well that is a little bit of a unicorn fantasy. But let's break that down. >> Sure. >> Do you think that's possible? >> It is. Because I think, if I am on MongoDB, I should be able to give a horizontal layer to MongoDB that is optimized for all three of them. I don't want MongoDB. >> First of all, everyone will buy that. >> Sure. >> I'm skeptical that that's possible. Given where we are at right now. So, you're saying that a vendor will provide an abstraction layer. >> No, I'm saying that either MongoDB, itself will do it, or a third party layer will come as a service which will abstract all this layer so that we will write to an AP layer. >> So what do you guys doing? How do you handle multiple clouds? You guys are taking that burden on, because it makes sense, you should build the abstraction layer. Not rely on a third party vendor right? >> We are doing it because there is no third party available offer it. But if you offer a third party tomorrow, I will use that as a Supercloud service. >> If they're 100% reliable? >> That's right. That's exactly it. >> They have to do the work. >> They have to do the work because if today I am doing it because no one else is offering it- >> Okay so what people might not know is that you are an angel investor as well as an entrepreneur been very successful, so you're rich, you have a lot of money. If I were a startup and I said, Muddu, I want to build this abstraction layer. What would be funding advice that you would give me as an entrepreneur? As a company to do that? >> I would do it like an Apigee that Google acquired, you should create an Apigee-like layer, for infrastructure upfront services, I think that is a very good option. >> And you think that is viable? >> It is very much viable. >> Would that be part of Supercloud architecture, in your opinion? >> It is. Right? And that will abstract all the clouds to some level. Like it is like Kubernetes abstract, so that if I am running on Kubernetes I can transfer to any cloud. >> Yeah >> But that should go from computer into other infrastructures. >> It's seems to me, Muddu, and I want to get your thoughts about this whole Supercloud defacto standard opportunity. It feels like we are waiting for a moment where there is some sort of defacto unification, whether it is in the distraction layer, or a standards body. There is no W3C here going on. I mean, W3C was for web consortium, for world wide web. The Supercloud seems to be having the same impact the web had. Transformative, disruptive, re-factoring business operations. Is there a standardized body or an opportunity for a defacto? Like Kubernetes was a great example of a unification around something for orchestration. Is there a better version in the Supercloud model where we need a standard? >> Yes and no. The reason is because by the time you come to standard, take time to look what happened. First, we started with VMs, then became Docker and Containers then we came to Kubernetes. So it goes through a journey. I think the next few years will be stood on SuperCloud let's make customers happy, let's make enough services going, and then the standards will come. Standards will be almost 2-3 years later. So I don't think standards should happen right now. Right now, all we need is, we need enough start ups to create the super layer abstraction, with the goal in mind of AI automation. The reason, AI is because AI needs to be able to run that. Automated because running a work flow is, I can either run a workflow in the cloud services, I can run it on on-prem, I can run it on database, so you have two good applications, take AI and automation with Supercloud and make enough enough noise on that make enough applications, then the standards will come. >> On this project we have been with SuperCloud these past day we have heard a lot of people talking. The themes that developers are okay, they are doing great. Open source is booming. >> Yes >> Cloud Native's got major traction. Developers are going fast and they love it, shifting left, all these great things. They're putting a lot of data, DevOps and the security teams, they're the ones who are leveling up. We are hearing a lot of conversations around how they can be faster. What is your view on this as relative to that Supercloud nirvana getting there? How are DevOps and security teams leveling up to devs? >> A couple of things. I think that in the world of DevSecOps and security ops. The reason security is important, right? Given what is going on, but you don't need to do security the manual way. I think that whole new operation that you and me talked about, AI ops should happen. Where the AI ops is for service operation, for performance, for incident or for security. Nobody thinks of AI security. So, the DevOps people should think more world of AI ops, so that I can predict, prevent things before they happen. Then the security will be much better. So AI ops with Supercloud will probably be that nirvana. But that is what should happen. >> In the AI side of things, what you guys are doing, what are you learning, on scale, relative to data? Is there, you said machine learning needs data, it needs scale operation. What's your view on the automation piece of all this? >> I think to me, the data is the single, underrated, unsung kind of hero in the whole machine learning. Everyone talks about AI and machine learning algorithms. Algorithms are as important, but even more important is data. Lack of data I can't do algorithms. So my advice to customers is don't lose your data. That is why I see, Frank, my old boss, setting everything up into the data cloud, in Snowflake. Data is so important, store the data, analyze the data. Data is the new AI. You and me talk so many times- >> Yeah >> It's underrated, people are not anticipating how important it is. But the data is coming from logs, events, whether there is knowledge documents, any data in any form. I think keep the data, analyze the data, data patterns, and then things like SuperCloud can really take advantage of that. >> So, in the Supercloud equation one of the things that has come up is that the native clouds do great. Their IaaS to SaaS is interactions that solve a lot of problems. There is integration that is good. >> Right. >> Now when you go off cloud, you get regions, get latency issues- >> Right >> You have more complexity. So what's the trade off in the Supercloud journey, if you had to guess? And just thinking out loud here, what would be some of the architectural trade offs of how you do it, what's the sequence? What's the order of operations to get Superclouding going? >> Yeah, very good questions here. I think once you start going from the public cloud, the clouds there scale to lets say, even a regional data center onto an Edge, latency will kick in. The lack of computer function will kick in. So there I think everything should become asynchronous, right? You will run the application in a limited environment. You should anticipate for small memories, small compute, long latencies, but still following should happen. So some operations should become the old-school following, like, it's like the email. I send an email, it's an asynchronous thing, I made a sponsor, I think most of message passing should go back to the old-school architectures They should become asynchronous where thing can rely. I think, as long as algorithms can take that into Edge, I think that Superclouds can really bridge between the public cloud to the edge. >> Muddu, thanks for coming, we really appreciate your insights here. You've always been a great friend, great commentator. If you weren't the CEO and a famous angel investor, we would certainly love to have you as a theCUBE analyst, here on theCUBE. >> I am always available for you. (John laughs) >> When you retire, you can come back. Final point, we've got time left. We'll give you a chance to talk about the company. I'm really intrigued by the success of your ninety million dollar financing realm because we are in a climate where people aren't getting those kinds of investments. It's usually down-rounds. >> Okay >> 409 adjustments, people are struggling. You got an up-round and you got a big number. Why the success? What is going on with the company? Why are you guys getting such great validation? Goldman Sachs, Thoma Bravo, Zoom, these are big names, these are the next gen winners. >> It is. >> Why are they picking you? Why are they investing in you? >> I think it is not one thing, it is many things. First all, I think it is a four-year journey for us where we are right now. So, the company started late 2017. It is getting the right customers, partners, employees, team members. So it is a lot hard work went in. So a lot of thanks to the Aisera community for where we are. Why customers and where we are? Look, fundamentally there is a problem to solve. Like, what Aisera is trying to solve is can we automate customer service? Whether internal employees, external customer support. Do it for IT, HR, sales, marketing, all the way to ops. Like you talk about DevSecOps, I don't want thousands of tune ups for ops. If I can make that job better, >> Yeah >> I want to, any job I want to automate. I call it, elevate the human, right? >> Yeah. >> And that's the reason- >> 'Cause you're saying people have to learn specialty tools, and there are consequences to that. >> Right, and to me, people should focus on more important tasks and use AI as a tool to automate those things right? It's like thinking of offering Apple City as Alexa as a service, that is how we are trying to offer customer service, like, right? And if it can do that consistently, and reduce costs, cost is a big reason why customers like us a lot, we have eliminated the cost in this down economy, I will amplify our message even more, right? I am going to take a bite out of their expense. Whether it is tool expense, it's on resources. Second, is user productivity And finally, experience. People want experience. >> Final question, folks out there, first of all, what do you think about Supercloud? And if someone asks you what is this Supercloud thing? How would you answer? >> Supercloud, is, to me, beyond multi cloud and hybrid cloud. It is to bridge applications that are build in Supercloud can run on all clouds seamlessly. You don't need to compile them, re-clear them. Supercloud is one place to build, develop, and deploy. >> Great, Muddu. Thank you for coming on. Supercloud22 here breaking it down with the ecosystem commentary, we have a lot of people coming to the small group of experts in our network, bringing you in open conversation around the future of cloud computing and applications globally. And again, it is all about the next generation cloud. This is theCUBE, thanks for watching. (upbeat music)

(upbeat music) >> Welcome back, everyone, to theCUBE's coverage here live on the floor at AWS re:MARS 2022. I'm John Furrier, host for theCUBE. Great event, machine learning, automation, robotics, space, that's MARS. It's part of the re-series of events, re:Invent's the big event at the end of the year, re:Inforce, security, re:MARS, really intersection of the future of space, industrial, automation, which is very heavily DevOps machine learning, of course, machine learning, which is AI. We have Luis Ceze here, who's the CEO co-founder of OctoML. Welcome to theCUBE. >> Thank you very much for having me in the show, John. >> So we've been following you guys. You guys are a growing startup funded by Madrona Venture Capital, one of your backers. You guys are here at the show. This is a, I would say small show relative what it's going to be, but a lot of robotics, a lot of space, a lot of industrial kind of edge, but machine learning is the centerpiece of this trend. You guys are in the middle of it. Tell us your story. >> Absolutely, yeah. So our mission is to make machine learning sustainable and accessible to everyone. So I say sustainable because it means we're going to make it faster and more efficient. You know, use less human effort, and accessible to everyone, accessible to as many developers as possible, and also accessible in any device. So, we started from an open source project that began at University of Washington, where I'm a professor there. And several of the co-founders were PhD students there. We started with this open source project called Apache TVM that had actually contributions and collaborations from Amazon and a bunch of other big tech companies. And that allows you to get a machine learning model and run on any hardware, like run on CPUs, GPUs, various GPUs, accelerators, and so on. It was the kernel of our company and the project's been around for about six years or so. Company is about three years old. And we grew from Apache TVM into a whole platform that essentially supports any model on any hardware cloud and edge. >> So is the thesis that, when it first started, that you want to be agnostic on platform? >> Agnostic on hardware, that's right. >> Hardware, hardware. >> Yeah. >> What was it like back then? What kind of hardware were you talking about back then? Cause a lot's changed, certainly on the silicon side. >> Luis: Absolutely, yeah. >> So take me through the journey, 'cause I could see the progression. I'm connecting the dots here. >> So once upon a time, yeah, no... (both chuckling) >> I walked in the snow with my bare feet. >> You have to be careful because if you wake up the professor in me, then you're going to be here for two hours, you know. >> Fast forward. >> The average version here is that, clearly machine learning has shown to actually solve real interesting, high value problems. And where machine learning runs in the end, it becomes code that runs on different hardware, right? And when we started Apache TVM, which stands for tensor virtual machine, at that time it was just beginning to start using GPUs for machine learning, we already saw that, with a bunch of machine learning models popping up and CPUs and GPU's starting to be used for machine learning, it was clear that it come opportunity to run on everywhere. >> And GPU's were coming fast. >> GPUs were coming and huge diversity of CPUs, of GPU's and accelerators now, and the ecosystem and the system software that maps models to hardware is still very fragmented today. So hardware vendors have their own specific stacks. So Nvidia has its own software stack, and so does Intel, AMD. And honestly, I mean, I hope I'm not being, you know, too controversial here to say that it kind of of looks like the mainframe era. We had tight coupling between hardware and software. You know, if you bought IBM hardware, you had to buy IBM OS and IBM database, IBM applications, it all tightly coupled. And if you want to use IBM software, you had to buy IBM hardware. So that's kind of like what machine learning systems look like today. If you buy a certain big name GPU, you've got to use their software. Even if you use their software, which is pretty good, you have to buy their GPUs, right? So, but you know, we wanted to help peel away the model and the software infrastructure from the hardware to give people choice, ability to run the models where it best suit them. Right? So that includes picking the best instance in the cloud, that's going to give you the right, you know, cost properties, performance properties, or might want to run it on the edge. You might run it on an accelerator. >> What year was that roughly, when you were going this? >> We started that project in 2015, 2016 >> Yeah. So that was pre-conventional wisdom. I think TensorFlow wasn't even around yet. >> Luis: No, it wasn't. >> It was, I'm thinking like 2017 or so. >> Luis: Right. So that was the beginning of, okay, this is opportunity. AWS, I don't think they had released some of the nitro stuff that the Hamilton was working on. So, they were already kind of going that way. It's kind of like converging. >> Luis: Yeah. >> The space was happening, exploding. >> Right. And the way that was dealt with, and to this day, you know, to a large extent as well is by backing machine learning models with a bunch of hardware specific libraries. And we were some of the first ones to say, like, know what, let's take a compilation approach, take a model and compile it to very efficient code for that specific hardware. And what underpins all of that is using machine learning for machine learning code optimization. Right? But it was way back when. We can talk about where we are today. >> No, let's fast forward. >> That's the beginning of the open source project. >> But that was a fundamental belief, worldview there. I mean, you have a world real view that was logical when you compare to the mainframe, but not obvious to the machine learning community. Okay, good call, check. Now let's fast forward, okay. Evolution, we'll go through the speed of the years. More chips are coming, you got GPUs, and seeing what's going on in AWS. Wow! Now it's booming. Now I got unlimited processors, I got silicon on chips, I got, everywhere >> Yeah. And what's interesting is that the ecosystem got even more complex, in fact. Because now you have, there's a cross product between machine learning models, frameworks like TensorFlow, PyTorch, Keras, and like that and so on, and then hardware targets. So how do you navigate that? What we want here, our vision is to say, folks should focus, people should focus on making the machine learning models do what they want to do that solves a value, like solves a problem of high value to them. Right? So another deployment should be completely automatic. Today, it's very, very manual to a large extent. So once you're serious about deploying machine learning model, you got a good understanding where you're going to deploy it, how you're going to deploy it, and then, you know, pick out the right libraries and compilers, and we automated the whole thing in our platform. This is why you see the tagline, the booth is right there, like bringing DevOps agility for machine learning, because our mission is to make that fully transparent. >> Well, I think that, first of all, I use that line here, cause I'm looking at it here on live on camera. People can't see, but it's like, I use it on a couple couple of my interviews because the word agility is very interesting because that's kind of the test on any kind of approach these days. Agility could be, and I talked to the robotics guys, just having their product be more agile. I talked to Pepsi here just before you came on, they had this large scale data environment because they built an architecture, but that fostered agility. So again, this is an architectural concept, it's a systems' view of agility being the output, and removing dependencies, which I think what you guys were trying to do. >> Only part of what we do. Right? So agility means a bunch of things. First, you know-- >> Yeah explain. >> Today it takes a couple months to get a model from, when the model's ready, to production, why not turn that in two hours. Agile, literally, physically agile, in terms of walk off time. Right? And then the other thing is give you flexibility to choose where your model should run. So, in our deployment, between the demo and the platform expansion that we announced yesterday, you know, we give the ability of getting your model and, you know, get it compiled, get it optimized for any instance in the cloud and automatically move it around. Today, that's not the case. You have to pick one instance and that's what you do. And then you might auto scale with that one instance. So we give the agility of actually running and scaling the model the way you want, and the way it gives you the right SLAs. >> Yeah, I think Swami was mentioning that, not specifically that use case for you, but that use case generally, that scale being moving things around, making them faster, not having to do that integration work. >> Scale, and run the models where they need to run. Like some day you want to have a large scale deployment in the cloud. You're going to have models in the edge for various reasons because speed of light is limited. We cannot make lights faster. So, you know, got to have some, that's a physics there you cannot change. There's privacy reasons. You want to keep data locally, not send it around to run the model locally. So anyways, and giving the flexibility. >> Let me jump in real quick. I want to ask this specific question because you made me think of something. So we're just having a data mesh conversation. And one of the comments that's come out of a few of these data as code conversations is data's the product now. So if you can move data to the edge, which everyone's talking about, you know, why move data if you don't have to, but I can move a machine learning algorithm to the edge. Cause it's costly to move data. I can move computer, everyone knows that. But now I can move machine learning to anywhere else and not worry about integrating on the fly. So the model is the code. >> It is the product. >> Yeah. And since you said, the model is the code, okay, now we're talking even more here. So machine learning models today are not treated as code, by the way. So do not have any of the typical properties of code that you can, whenever you write a piece of code, you run a code, you don't know, you don't even think what is a CPU, we don't think where it runs, what kind of CPU it runs, what kind of instance it runs. But with machine learning model, you do. So what we are doing and created this fully transparent automated way of allowing you to treat your machine learning models if you were a regular function that you call and then a function could run anywhere. >> Yeah. >> Right. >> That's why-- >> That's better. >> Bringing DevOps agility-- >> That's better. >> Yeah. And you can use existing-- >> That's better, because I can run it on the Artemis too, in space. >> You could, yeah. >> If they have the hardware. (both laugh) >> And that allows you to run your existing, continue to use your existing DevOps infrastructure and your existing people. >> So I have to ask you, cause since you're a professor, this is like a masterclass on theCube. Thank you for coming on. Professor. (Luis laughing) I'm a hardware guy. I'm building hardware for Boston Dynamics, Spot, the dog, that's the diversity in hardware, it's tends to be purpose driven. I got a spaceship, I'm going to have hardware on there. >> Luis: Right. >> It's generally viewed in the community here, that everyone I talk to and other communities, open source is going to drive all software. That's a check. But the scale and integration is super important. And they're also recognizing that hardware is really about the software. And they even said on stage, here. Hardware is not about the hardware, it's about the software. So if you believe that to be true, then your model checks all the boxes. Are people getting this? >> I think they're starting to. Here is why, right. A lot of companies that were hardware first, that thought about software too late, aren't making it. Right? There's a large number of hardware companies, AI chip companies that aren't making it. Probably some of them that won't make it, unfortunately just because they started thinking about software too late. I'm so glad to see a lot of the early, I hope I'm not just doing our own horn here, but Apache TVM, the infrastructure that we built to map models to different hardware, it's very flexible. So we see a lot of emerging chip companies like SiMa.ai's been doing fantastic work, and they use Apache TVM to map algorithms to their hardware. And there's a bunch of others that are also using Apache TVM. That's because you have, you know, an opening infrastructure that keeps it up to date with all the machine learning frameworks and models and allows you to extend to the chips that you want. So these companies pay attention that early, gives them a much higher fighting chance, I'd say. >> Well, first of all, not only are you backable by the VCs cause you have pedigree, you're a professor, you're smart, and you get good recruiting-- >> Luis: I don't know about the smart part. >> And you get good recruiting for PhDs out of University of Washington, which is not too shabby computer science department. But they want to make money. The VCs want to make money. >> Right. >> So you have to make money. So what's the pitch? What's the business model? >> Yeah. Absolutely. >> Share us what you're thinking there. >> Yeah. The value of using our solution is shorter time to value for your model from months to hours. Second, you shrink operator, op-packs, because you don't need a specialized expensive team. Talk about expensive, expensive engineers who can understand machine learning hardware and software engineering to deploy models. You don't need those teams if you use this automated solution, right? Then you reduce that. And also, in the process of actually getting a model and getting specialized to the hardware, making hardware aware, we're talking about a very significant performance improvement that leads to lower cost of deployment in the cloud. We're talking about very significant reduction in costs in cloud deployment. And also enabling new applications on the edge that weren't possible before. It creates, you know, latent value opportunities. Right? So, that's the high level value pitch. But how do we make money? Well, we charge for access to the platform. Right? >> Usage. Consumption. >> Yeah, and value based. Yeah, so it's consumption and value based. So depends on the scale of the deployment. If you're going to deploy machine learning model at a larger scale, chances are that it produces a lot of value. So then we'll capture some of that value in our pricing scale. >> So, you have direct sales force then to work those deals. >> Exactly. >> Got it. How many customers do you have? Just curious. >> So we started, the SaaS platform just launched now. So we started onboarding customers. We've been building this for a while. We have a bunch of, you know, partners that we can talk about openly, like, you know, revenue generating partners, that's fair to say. We work closely with Qualcomm to enable Snapdragon on TVM and hence our platform. We're close with AMD as well, enabling AMD hardware on the platform. We've been working closely with two hyperscaler cloud providers that-- >> I wonder who they are. >> I don't know who they are, right. >> Both start with the letter A. >> And they're both here, right. What is that? >> They both start with the letter A. >> Oh, that's right. >> I won't give it away. (laughing) >> Don't give it away. >> One has three, one has four. (both laugh) >> I'm guessing, by the way. >> Then we have customers in the, actually, early customers have been using the platform from the beginning in the consumer electronics space, in Japan, you know, self driving car technology, as well. As well as some AI first companies that actually, whose core value, the core business come from AI models. >> So, serious, serious customers. They got deep tech chops. They're integrating, they see this as a strategic part of their architecture. >> That's what I call AI native, exactly. But now there's, we have several enterprise customers in line now, we've been talking to. Of course, because now we launched the platform, now we started onboarding and exploring how we're going to serve it to these customers. But it's pretty clear that our technology can solve a lot of other pain points right now. And we're going to work with them as early customers to go and refine them. >> So, do you sell to the little guys, like us? Will we be customers if we wanted to be? >> You could, absolutely, yeah. >> What we have to do, have machine learning folks on staff? >> So, here's what you're going to have to do. Since you can see the booth, others can't. No, but they can certainly, you can try our demo. >> OctoML. >> And you should look at the transparent AI app that's compiled and optimized with our flow, and deployed and built with our flow. That allows you to get your image and do style transfer. You know, you can get you and a pineapple and see how you look like with a pineapple texture. >> We got a lot of transcript and video data. >> Right. Yeah. Right, exactly. So, you can use that. Then there's a very clear-- >> But I could use it. You're not blocking me from using it. Everyone's, it's pretty much democratized. >> You can try the demo, and then you can request access to the platform. >> But you get a lot of more serious deeper customers. But you can serve anybody, what you're saying. >> Luis: We can serve anybody, yeah. >> All right, so what's the vision going forward? Let me ask this. When did people start getting the epiphany of removing the machine learning from the hardware? Was it recently, a couple years ago? >> Well, on the research side, we helped start that trend a while ago. I don't need to repeat that. But I think the vision that's important here, I want the audience here to take away is that, there's a lot of progress being made in creating machine learning models. So, there's fantastic tools to deal with training data, and creating the models, and so on. And now there's a bunch of models that can solve real problems there. The question is, how do you very easily integrate that into your intelligent applications? Madrona Venture Group has been very vocal and investing heavily in intelligent applications both and user applications as well as enablers. So we say an enable of that because it's so easy to use our flow to get a model integrated into your application. Now, any regular software developer can integrate that. And that's just the beginning, right? Because, you know, now we have CI/CD integration to keep your models up to date, to continue to integrate, and then there's more downstream support for other features that you normally have in regular software development. >> I've been thinking about this for a long, long, time. And I think this whole code, no one thinks about code. Like, I write code, I'm deploying it. I think this idea of machine learning as code independent of other dependencies is really amazing. It's so obvious now that you say it. What's the choices now? Let's just say that, I buy it, I love it, I'm using it. Now what do I got to do if I want to deploy it? Do I have to pick processors? Are there verified platforms that you support? Is there a short list? Is there every piece of hardware? >> We actually can help you. I hope we're not saying we can do everything in the world here, but we can help you with that. So, here's how. When you have them all in the platform you can actually see how this model runs on any instance of any cloud, by the way. So we support all the three major cloud providers. And then you can make decisions. For example, if you care about latency, your model has to run on, at most 50 milliseconds, because you're going to have interactivity. And then, after that, you don't care if it's faster. All you care is that, is it going to run cheap enough. So we can help you navigate. And also going to make it automatic. >> It's like tire kicking in the dealer showroom. >> Right. >> You can test everything out, you can see the simulation. Are they simulations, or are they real tests? >> Oh, no, we run all in real hardware. So, we have, as I said, we support any instances of any of the major clouds. We actually run on the cloud. But we also support a select number of edge devices today, like ARMs and Nvidia Jetsons. And we have the OctoML cloud, which is a bunch of racks with a bunch Raspberry Pis and Nvidia Jetsons, and very soon, a bunch of mobile phones there too that can actually run the real hardware, and validate it, and test it out, so you can see that your model runs performant and economically enough in the cloud. And it can run on the edge devices-- >> You're a machine learning as a service. Would that be an accurate? >> That's part of it, because we're not doing the machine learning model itself. You come with a model and we make it deployable and make it ready to deploy. So, here's why it's important. Let me try. There's a large number of really interesting companies that do API models, as in API as a service. You have an NLP model, you have computer vision models, where you call an API and then point in the cloud. You send an image and you got a description, for example. But it is using a third party. Now, if you want to have your model on your infrastructure but having the same convenience as an API you can use our service. So, today, chances are that, if you have a model that you know that you want to do, there might not be an API for it, we actually automatically create the API for you. >> Okay, so that's why I get the DevOps agility for machine learning is a better description. Cause it's not, you're not providing the service. You're providing the service of deploying it like DevOps infrastructure as code. You're now ML as code. >> It's your model, your API, your infrastructure, but all of the convenience of having it ready to go, fully automatic, hands off. >> Cause I think what's interesting about this is that it brings the craftsmanship back to machine learning. Cause it's a craft. I mean, let's face it. >> Yeah. I want human brains, which are very precious resources, to focus on building those models, that is going to solve business problems. I don't want these very smart human brains figuring out how to scrub this into actually getting run the right way. This should be automatic. That's why we use machine learning, for machine learning to solve that. >> Here's an idea for you. We should write a book called, The Lean Machine Learning. Cause the lean startup was all about DevOps. >> Luis: We call machine leaning. No, that's not it going to work. (laughs) >> Remember when iteration was the big mantra. Oh, yeah, iterate. You know, that was from DevOps. >> Yeah, that's right. >> This code allowed for standing up stuff fast, double down, we all know the history, what it turned out. That was a good value for developers. >> I could really agree. If you don't mind me building on that point. You know, something we see as OctoML, but we also see at Madrona as well. Seeing that there's a trend towards best in breed for each one of the stages of getting a model deployed. From the data aspect of creating the data, and then to the model creation aspect, to the model deployment, and even model monitoring. Right? We develop integrations with all the major pieces of the ecosystem, such that you can integrate, say with model monitoring to go and monitor how a model is doing. Just like you monitor how code is doing in deployment in the cloud. >> It's evolution. I think it's a great step. And again, I love the analogy to the mainstream. I lived during those days. I remember the monolithic propriety, and then, you know, OSI model kind of blew it. But that OSI stack never went full stack, and it only stopped at TCP/IP. So, I think the same thing's going on here. You see some scalability around it to try to uncouple it, free it. >> Absolutely. And sustainability and accessibility to make it run faster and make it run on any deice that you want by any developer. So, that's the tagline. >> Luis Ceze, thanks for coming on. Professor. >> Thank you. >> I didn't know you were a professor. That's great to have you on. It was a masterclass in DevOps agility for machine learning. Thanks for coming on. Appreciate it. >> Thank you very much. Thank you. >> Congratulations, again. All right. OctoML here on theCube. Really important. Uncoupling the machine learning from the hardware specifically. That's only going to make space faster and safer, and more reliable. And that's where the whole theme of re:MARS is. Let's see how they fit in. I'm John for theCube. Thanks for watching. More coverage after this short break. >> Luis: Thank you. (gentle music)

(upbeat music) >> Okay, welcome back everyone. CUBE's coverage of re:MARS, here in Las Vegas, in person. I'm John Furrier, host of theCUBE. This is the analyst panel wrap up analysis of the keynote, the show, past one and a half days. We got two great guests here. We got Andy Thurai, Vice President, Principal Consultant, Constellation Research. Larry Carvalho, Principal Consultant at RobustCloud LLC. Congratulations going out on your own. >> Thank you. >> Andy, great to see you. >> Great to see you as well. >> Guys, thanks for coming out. So this is the session where we break down and analyze, you guys are analysts, industry analysts, you go to all the shows, we see each other. You guys are analyzing the landscape. What does this show mean to you guys? 'Cause this is not obvious to the normal tech follower. The insiders see the confluence of robotics, space, automation and machine learning. Obviously, it's IoTs, industrials, it's a bunch of things. But there's some dots to connect. Let's start with you, Larry. What do you see here happening at this show? >> So you got to see how Amazon started, right? When AWS started. When AWS started, it primarily took the compute storage, networking of Amazon.com and put it as a cloud service, as a service, and started selling the heck out of it. This is a stage later now that Amazon.com has done a lot of physical activity, and using AIML and the robotics, et cetera, it's now the second phase of innovation, which is beyond digital transformation of back office processes, to the transformation of physical processes where people are now actually delivering remotely and it's an amazing area. >> So back office's IT data center kind of vibe. >> Yeah. >> You're saying front end, industrial life. >> Yes. >> Life as we know it. >> Right, right. I mean, I just stopped at a booth here and they have something that helps anybody who's stuck in the house who cannot move around. But with Alexa, order some water to bring them wherever they are in the house where they're stuck in their bed. But look at the innovation that's going on there right at the edge. So I think those are... >> John: And you got the Lunar, got the sex appeal of the space, Lunar Outpost interview, >> Yes. >> those guys. They got Rover on Mars. They're going to have be colonizing the moon. >> Yes. >> I made a joke, I'm like, "Well, I left a part back on earth, I'll be right back." (Larry and Andy laugh) >> You can't drive back to the office. So a lot of challenges. Andy, what's your take of the show? Take us your analysis. What's the vibe, what's your analysis so far? >> It's a great show. So, as Larry was saying, one of the thing was that when Amazon started, right? So they were more about cloud computing. So, which means is they try to commoditize more of data center components or compute components. So that was working really well for what I call it as a compute economy, right? >> John: Mm hmm. >> And I call the newer economy as more of a AIML-based data economy. So when you move from a compute economy into a data economy, there are things that come into the forefront that never existed before, never popular before. Things like your AIML model creation, model training, model movement, model influencing, all of the above, right? And then of course the robotics has come long way since then. And then some of what they do at the store, or the charging, the whole nine yards. So, the whole concept of all of these components, when you put them on re:Invent, such a big show, it was getting lost. So that's why they don't have it for a couple of years. They had it one year. And now all of a sudden they woke up and say, "You know what? We got to do this!" >> John: Yeah. >> To bring out this critical components that we have, that's ripe, mature for the world to next component. So that's why- I think they're pretty good stuff. And some of the robotics things I saw in there, like one of them I posted on my Twitter, it's about the robot dog, sniffing out the robot rover, which I thought was pretty hilarious. (All laugh) >> Yeah, this is the thing. You're seeing like the pandemic put everything on hold on the last re:Mars, and then the whole world was upside down. But a lot of stuff pulled forward. You saw the call center stuff booming. You saw the Zoomification of our workplace. And I think a lot of people got to the realization that this hybrid, steady-state's here. And so, okay. That settles that. But the digital transformation of actually physical work? >> Andy: Yeah. >> Location, the walk in and out store right over here we've seen that's the ghost store in Seattle. We've all been there. In fact, I was kind of challenged, try to steal something. I'm like, okay- (Larry laughs) I'm pulling all my best New Jersey moves on everyone. You know? >> Andy: You'll get charged for it. >> I couldn't get away with it. Two double packs, drop it, it's smart as hell. Can't beat the system. But, you bring that to where the AI machine learning, and the robotics meet, robots. I mean, we had robots here on theCUBE. So, I think this robotics piece is a huge IoT, 'cause we've been covering industrial IoT for how many years, guys? And you could know what's going on there. Huge cyber threats. >> Mm hmm. >> Huge challenges, old antiquated OT technology. So I see a confluence in the collision between that OT getting decimated, to your point. And so, do you guys see that? I mean, am I just kind of seeing mirage? >> I don't see it'll get decimated, it'll get replaced with a newer- >> John: Dave would call me out on that. (Larry laughs) >> Decimated- >> Microsoft's going to get killed. >> I think it's going to have to be reworked. And just right now, you want do anything in a shop floor, you have to have a physical wire connected to it. Now you think about 5G coming in, and without a wire, you get minute details, you get low latency, high bandwidth. And the possibilities are endless at the edge. And I think with AWS, they got Outposts, they got Snowcone. >> John: There's a threat to them at the edge. Outpost is not doing well. You talk to anyone out there, it's like, you can't find success stories. >> Larry: Yeah. >> I'm going to get hammered by Amazon people, "Oh, what're you're saying that?" You know, EKS for example, with serverless is kicking ass too. So, I mean I'm not saying Outpost was wrong answer, it was a right at the time, what, four years ago that came out? >> Yeah. >> Okay, so, but that doesn't mean it's just theirs. You got Dell Technologies want some edge action. >> Yeah. >> So does HPE. >> Yes. >> So you got a competitive edge situation. >> I agree with that and I think that's definitely not Amazon's strong point, but like everything, they try to make it easy to use. >> John: Yeah. >> You know, you look at the AIML and they got Canvas. So Canvas says, hey, anybody can do AIML. If they can do that for the physical robotic processes, or even like with Outpost and Snowcone, that'll be good. I don't think they're there yet, and they don't have the presence in the market, >> John: Yeah. >> like HPE and, >> John: Well, let me ask you guys this question, because I think this brings up the next point. Will the best technology win or will the best solution win? Because if cloud's a platform and all software's open source, which you can make those assumptions, you then say, hey, they got this killer robotics thing going on with Artemis and Moonshot, they're trying to colonize the moon, but oh, they discovered a killer way to solve a big problem. Does something fall out of this kind of re:Mars environment, that cracks the code and radically changes and disrupts the IoT game? That's my open question. I don't know the answer. I'd love to get your take on what might be possible, what wild card's out there around, disrupting the edge. >> So one thing I see the way, so when IoT came into the world of play, it's when you're digitizing the physical world, it's IoT that does digitalization part of that actually, right? >> But then it has its own set of problems. >> John: Yeah. >> You're talking about you installing sensor everywhere, right? And not only installing your own sensor, but also you're installing competitor sensors. So in a given square feet how many sensors can you accommodate? So there are physical limitations on liabilities of bandwidth and networking all of that. >> John: And integration. >> As well. >> John: Your point. >> Right? So when that became an issue, this is where I was talking to the robotic guys here, a couple of companies, and one of the use cases they were talking about, which I thought was pretty cool, is, rather than going the sensor route, you go the robot route. So if you have either a factor that you want to map out, you put as many sensors on your robot, whatever that is, and then you make it go around, map the whole thing, and then you also do a surveillance in the whole nine yards. So, you can either have a fixed sensors or you can have moving sensors. So you can have three or four robots. So initially, when I was asking them about the price of it, when they were saying about a hundred thousand dollars, I was like, "Who would buy that?" (John and Larry laugh) >> When they then explained that, this is the use case, oh, that makes sense, because if you had to install, entire factory floor sensors, you're talking about millions of dollars. >> John: Yeah. >> But if you do the moveable sensors in this way, it's a lot cheaper. >> John: Yeah, yeah. >> So it's based on your use case, what are your use cases? What are you trying to achieve? >> The general purpose is over. >> Yeah. >> Which you're getting at, and that the enablement, this is again, this is the cloud scale open question- >> Yep. >> it's, okay, the differentiations isn't going to be open source software. That's open. >> It's going to be in the, how you configure it. >> Yes. >> What workflows you might have, the data streams. >> I think, John, you're bringing up a very good point about general purpose versus special purpose. Yesterday Zoox was on the stage and when they talked about their vehicle, it's made just for self-driving. You walk around in Vegas, over here, you see a bunch of old fashioned cars, whether they're Ford or GM- >> and they put all these devices around it, but you're still driving the same car. >> John: Yeah, exactly. >> You can retrofit those, but I don't think that kind of IoT is going to work. But if you redo the whole thing, we are going to see a significant change in how IoT delivers value all the way from the industrial to home, to healthcare, mining, agriculture, it's going to have to redo. I'll go back to the OT question. There are some OT guys, I know Rockwell and Siemens, some of them are innovating faster. The ones who innovate faster to keep up with the IT side, as well as the MLAI model are going to be the winners on that one. >> John: Yeah, I agree. Andy, your thoughts on manufacturing, you brought up the sensor thing. Robotics ultimately is, end of the day, an opportunity there. Obviously machine learning, we know what that does. As we move into these more autonomous builds, what does that look like? And is Amazon positioned well there? Obviously they have big manufacturers. Some are saying that they might want to get out of that business too, that Jassy's evaluating that some are saying. So, where does this all lead for that robotics manufacturing lifestyle, walk in, grab my food? 'Cause it's all robotics and AI at the end of the day, I got sensors, I got cameras, I got non-humans moving heavy lifting stuff, fixing the moon will be done by robots, not humans. So it's all coming. What's your analysis? >> Well, so, the point about robotics is on how far it has come, it is unbelievable, right? Couple of examples. One was that I was just talking to somebody, was explaining to them, to see that robot dog over there at the Boston Dynamics one- >> John: Yeah. >> climbing up and down the stairs. >> Larry: Yeah. >> That's more like the dinosaur movie opening the doors scene. (John and Larry laugh) It's like that for me, because the coordinated things, it is able to go walk up and down, that's unbelievable. But okay, it does that, and then there was also another video which is going on viral on the internet. This guy kicks the dog, robot dog, and then it falls down and it gets back up, and the sentiment that people were feeling for the dog, (Larry laughs) >> you can't, it's a robot, but people, it just comes at that level- >> John: Empathy, for a non-human. >> Yeah. >> But you see him, hey you, get off my lawn, you know? It's like, where are we? >> It has come to that level that people are able to kind of not look at that as a robot, but as more like a functioning, almost like a pet-level, human-level being. >> John: Yeah. >> And you saw that the human-like walking robot there as well. But to an extent, in my view, they are all still in an experimentation, innovation phase. It doesn't made it in the industrial terms yet. >> John: Yeah, not yet, it's coming. >> But, the problem- >> John: It's coming fast. That's what I'm trying to figure out is where you guys see Amazon and the industry relative to what from the fantasy coming reality- >> Right. >> of space in Mars, which is, it's intoxicating, let's face it. People love this. The nerds are all here. The geeks are all here. It's a celebration. James Hamilton's here- >> Yep. >> trying to get him on theCUBE. And he's here as a civilian. Jeff Barr, same thing. I'm here, not for Amazon, I bought a ticket. No, you didn't buy a ticket. (Larry laughs) >> I'm going to check on that. But, he's geeking out. >> Yeah. >> They're there because they want to be here. >> Yeah. >> Not because they have to work here. >> Well, I mean, the thing is, the innovation velocity has increased, because, in the past, remember, the smaller companies couldn't innovate because they don't have the platform. Now Compute is a platform available at the scale you want, AI is available at the scale. Every one of them is available at the scale you want. So if you have an idea, it's easy to innovate. The innovation velocity is high. But where I see most of the companies failing, whether startup or big company, is that you don't find the appropriate use case to solve, and then don't sell it to the right people to buy that. So if you don't find the right use case or don't sell the right value proposition to the actual buyer, >> John: Mm hmm. >> then why are you here? What are you doing? (John laughs) I mean, you're not just an invention, >> John: Eh, yeah. >> like a telephone kind of thing. >> Now, let's get into next talk track. I want to get your thoughts on the experience here at re:Mars. Obviously AWS and the Amazon people kind of combined effort between their teams. The event team does a great job. I thought the event, personally, was first class. The coffee didn't come in late today, I was complaining about that, (Larry laughs) >> people complaining out there, at CUBE reviews. But world class, high bar on the quality of the event. But you guys were involved in the analyst program. You've been through the walkthrough, some of the briefings. I couldn't do that 'cause I'm doing theCUBE interviews. What would you guys learn? What were some of the key walkaways, impressions? Amazon's putting all new teams together, seems on the analyst relations. >> Larry: Yeah. >> They got their mojo booming. They got three shows now, re:Mars, re:inforce, re:invent. >> Andy: Yeah. >> Which will be at theCUBE at all three. Now we got that coverage going, what's it like? What was the experience like? Did you feel it was good? Where do they need to improve? How would you grade the Amazon team? >> I think they did a great job over here in just bringing all the physical elements of the show. Even on the stage, where they had robots in there. It made it real and it's not just fake stuff. And every, or most of the booths out there are actually having- >> John: High quality demos. >> high quality demos. (John laughs) >> John: Not vaporware. >> Yeah, exactly. Not vaporware. >> John: I won't say the name of the company. (all laugh) >> And even the sessions were very good. They went through details. One thing that stood out, which is good, and I cover Low Code/No Code, and Low Code/No Code goes across everything. You know, you got DevOps No Low-Code Low-Code. You got AI Low Code/No Code. You got application development Low Code/No Code. What they have done with AI with Low Code/No Code is very powerful with Canvas. And I think that has really grown the adoption of AI. Because you don't have to go and train people what to do. And then, people are just saying, Hey, let me kick the tires, let me use it. Let me try it. >> John: It's going to be very interesting to see how Amazon, on that point, handles this, AWS handles this data tsunami. It's cause of Snowflake. Snowflake especially running the table >> Larry: Yeah. >> on the old Hadoop world. I think Dave had a great analysis with other colleagues last week at Snowflake Summit. But still, just scratching the surface. >> Larry: Yeah. >> The question is, how shared that ecosystem, how will that morph? 'Cause right now you've got Data Bricks, you've got Snowflake and a handful of others. Teradata's got some new chops going on there and a bunch of other folks. Some are going to win and lose in this downturn, but still, the scale that's needed is massive. >> So you got data growing so much, you were talking earlier about the growth of data and they were talking about the growth. That is a big pie and the pie can be shared by a lot of folks. I don't think- >> John: And snowflake pays AWS, remember that? >> Right, I get it. (John laughs) >> I get it. But they got very unique capabilities, just like Netflix has very unique capabilities. >> John: Yeah. >> They also pay AWS. >> John: Yeah. >> Right? But they're competing on prime. So I really think the cooperation is going to be there. >> John: Yeah. >> The pie is so big >> John: Yeah. >> that there's not going to be losers, but everybody could be winners. >> John: I'd be interested to follow up with you guys after next time we have an event together, we'll get you back on and figure out how do you measure this transitions? You went to IDC, so they had all kinds of ways to measure shipments. >> Larry: Yep. >> Even Gartner had fumbled for years, the Magic Quadrant on IaaS and PaaS when they had the market share. (Larry laughs) And then they finally bundled PaaS and IaaS together after years of my suggesting, thank you very much Gartner. (Larry laughs) But that just performs as the landscape changes so does the scoreboard. >> Yep. >> Right so, how do you measure who's winning and who's losing? How can we be critical of Amazon so they can get better? I mean, Andy Jassy always said to me, and Adam Salassi same way, we want to hear how bad we're doing so we can get better. >> Yeah. >> So they're open-minded to feedback. I mean, not (beep) posting on them, but they're open to critical feedback. What do you guys, what feedback would you give Amazon? Are they winning? I see them number one clearly over Azure, by miles. And even though Azure's kicking ass and taking names, getting back in the game, Microsoft's still behind, by a long ways, in some areas. >> Andy: Yes. In some ways. >> So, the scoreboard's changing. What's your thoughts on that? >> So, look, I mean, at the end of the day, when it comes to compute, right, Amazon is a clear winner. I mean, there are others who are catching up to it, but still, they are the established leader. And it comes with its own advantages because when you're trying to do innovation, when you're trying to do anything else, whether it's a data collection, we were talking about the data sensors, the amount of data they are collecting, whether it's the store, that self-serving store or other innovation projects, what they have going on. The storage compute and process of that requires a ton of compute. And they have that advantage with them. And, as I mentioned in my last article, one of my articles, when it comes to AIML and data programs, there is a rich and there is a poor. And the rich always gets richer because they, they have one leg up already. >> John: Yeah. >> I mean the amount of model training they have done, the billion or trillion dollar trillion parametrization, fine tuning of the model training and everything. They could do it faster. >> John: Yeah. >> Which means they have a leg up to begin with. So unless you are given an opportunity as a smaller, mid-size company to compete at them at the same level, you're going to start at the negative level to begin with. You have a lot of catch up to do. So, the other thing about Amazon is that they, when it comes to a lot of areas, they admit that they have to improve in certain areas and they're open and willing and listen to the people. >> Where are you, let's get critical. Let's do some critical analysis. Where does Amazon Websters need to get better? In your opinion, what criticism would you, in a constructive way, share? >> I think on the open source side, they need to be more proactive in, they are already, but they got to get even better than what they are. They got to engage with the community. They got to be able to talk on the open source side, hey, what are we doing? Maybe on the hardware side, can they do some open-sourcing of that? They got graviton. They got a lot of stuff. Will they be able to share the wealth with other folks, other than just being on an Amazon site, on the edge with their partners. >> John: Got it. >> If they can now take that, like you said, compute with what they have with a very end-to-end solution, the full stack. And if they can extend it, that's going to be really beneficial for them. >> Awesome. Andy, final word here. >> So one area where I think they could improve, which would be a game changer would be, right now, if you look at all of their solutions, if you look at the way they suggest implementation, the innovations, everything that comes out, comes out across very techy-oriented. The persona is very techy-oriented. Very rarely their solutions are built to the business audience or to the decision makers. So if I'm, say, an analyst, if I want to build, a business analyst rather, if I want to build a model, and then I want to deploy that or do some sort of application, mobile application, or what have you, it's a little bit hard. It's more techy-oriented. >> John: Yeah, yeah. >> So, if they could appeal or build a higher level abstraction of how to build and deploy applications for business users, or even build something industry specific, that's where a lot of the legacy companies succeeded. >> John: Yeah. >> Go after manufacturing specific or education. >> Well, we coined the term 'Supercloud' last re:Invent, and that's what we see. And Jerry Chen at Greylock calls it Castles in the Cloud, you can create these moats >> Yep. >> on top of the CapEx >> Yep. >> of Amazon. >> Exactly. >> And ride their back. >> Yep. >> And the difference in what you're paying and what you're charging, if you're good, like a Snowflake or a Mongo. I mean, Mongo's, they're just as big as Snow, if not bigger on Amazon than Snowflake is. 'Cause they use a lot of compute. No one turns off their database. (John laughs) >> Snowflake a little bit different, a little nuanced point, but, this is the new thing. You see Goldman Sachs, you got Capital One. They're building their own kind of, I call them sub clouds, but Dave Vellante says it's a Supercloud. And that essentially is the model. And then once you have a Supercloud, you say, great, I'm going to make sure it works on Azure and Google. >> Andy: Yep. >> And Alibaba if I have to. So, we're kind of seeing a playbook. >> Andy: Mm hmm. >> But you can't get it wrong 'cause it scales. >> Larry: Yeah, yeah. >> You can't scale the wrong answer. >> Andy: Yeah. >> So that seems to be what I'm watching is, who gets it right? Product market fit. Then if they roll it out to the cloud, then it becomes a Supercloud, and that's pure product market fit. So I think that's something that I've seen some people trying to figure out. And then, are you a supplier to the Superclouds? Like a Dell? Or you become an enabler? >> Andy: Yeah. >> You know, what's Dell Technologies do? >> Larry: Yeah. >> I mean, how do the box movers compete? >> Larry: I, the whole thing is now hybrid and you're going to have to see just, you said. (Larry laughs) >> John: Hybrid's a steady-state. I don't need to. >> Andy: I mean, >> By the way we're (indistinct), we can't get the chips, cause Broadcom and Apple bought 'em all. (Larry laughs) I mean there's a huge chip problem going on. >> Yes. I agree. >> Right now. >> I agree. >> I mean all these problems when you attract to a much higher level, a lot of those problems go away because you don't care about what they're using underlying as long as you deliver my solution. >> Larry: Yes. >> Yeah, it could be significantly, a little bit faster than what it used to be. But at the end of the day, are you solving my specific use case? >> John: Yeah. >> Then I'm willing to wait a little bit longer. >> John: Yeah. Time's on our side and now they're getting the right answers. Larry, Andy, thanks for coming on. This great analyst session turned into more of a podcast vibe, but you know what? (Larry laughs) To chill here at re:Mars, thanks for coming on, and we unpacked a lot. Thanks for sharing. >> Both: Thank you. >> Appreciate it. We'll get you back on. We'll get you in the rotation. We'll take it virtual. Do a panel. Do a panel, do some panels around this. >> Larry: Absolutely. >> Andy: Oh this not virtual, this physical. >> No we're live right now! (all laugh) We get back to Palo Alto. You guys are influencers. Thanks for coming on. You guys are moving the market, congratulations. Take a minute, quick minute each to plug any work you're doing for the people watching. Larry, what are you working on? Andy? You go after Larry, what you're working on. >> Yeah. So since I started my company, RobustCloud, since I left IDC about a year ago, I'm focused on edge computing, cloud-native technologies, and Low Code/No Code. And basically I help companies put their business value together. >> All right, Andy, what are you working on? >> I do a lot of work on the AIML areas. Particularly, last few of my reports are in the AI Ops incident management and ML Ops areas of how to generally improve your operations. >> John: Got it, yeah. >> In other words, how do you use the AIML to improve your IT operations? How do you use IT Ops to improve your AIML efficiency? So those are the- >> John: The real hardcore business transformation. >> Yep. >> All right. Guys, thanks so much for coming on the analyst session. We do keynote review, breaking down re:Mars after day two. We got a full day tomorrow. I'm John Furrier with theCUBE. See you next time. (pleasant music)

>>Mhm. Mhm. Mhm. >>We're back with the notion there to wrap up conv all connections. 2021 the virtual edition. Okay, let's do this. You ready? >>Absolutely. >>All right. I'll get a starting .1. Data. You ain't seen nothing yet. You just wait. We're gonna look back on the big data era of the 20 tens and joke about how trivial was compared to the next 10 years. You know, what are your thoughts on data value and data exposures? >>The data has never been more valuable. Right? The new oil your most critical asset and neither has it been more vulnerable. So you kind of get these two things value increasing. Obviously it becomes more attractive to the to the bad actors and that's the era that we're living in and really, you know what organizations are needed. You know, you kind of think about business resilience and all that. You need the ability to as someone said the anti fragile right? Keep testing it. See, you know, if if your data defenses are now ready to a point where your data is not a liability, but you can make it something that becomes a business advantage. So kind of that business resilience gap that we've been talking about. The business integrity gap uh is really you know what we had focused on. So our customers can really start just taking advantage of the value equation of the data. >>And I think you know, I'm gonna I'm gonna push my community here a little bit and I'm gonna I think we need a new new metaphor because you know why? Because data minnows it's actually more valuable than oil it's not scarce like oil we're never gonna run out of data. So I'm trying to come up with a new a new one but we'll work on that. The cloud. The 2nd point is the cloud is expanding. It's moving to the data center. We got hybrid connections were going across clouds, we got edge nodes, we got new workloads, real time streaming and ai influencing microservices and containers and Ai and all this R. P. A. And hyper automation. All the crazy buzzwords that combined your digital business stack. But the point is data is not only exploding, it's exploding everywhere. You know it's not just in one place anymore. >>Absolutely. And that's that's you know part of the challenge here that our customers space you know unless you know you're a company that was born yesterday you have applications everywhere. Your your pace is different, every customer's journey and the transformation is different. So you might take different directions, different ways. What do you do you have some sass applications you might start there or you start with some public cloud. Maybe you start using some stories in public cloud. So as you transform and as you are now creating more sprawl and that sprawl as we talked about before this is like swiss cheese you got lights that you know people can take advantage of. On the other hand because of that lack of a single unified data services platform. What you lose is the ability to take advantage of all your data, your application, mobility and people die. Let's take the example of containers and kubernetes. What is the point of having you know transportation and ability to move these containers to any cloud if your data is not available in all those clocks. What's the strategy for that? So the problems are also changing their more business centric than just that, you know, what I call the active data management era is really upon us and that's really what's gonna help take it full advantage of all of the other technologies around us. Ai microservices edge, you know, IOT you need to make sure you have a unified data services and intelligent data services platform. >>So what I see is is calm vault is essentially building that that data protection cloud or you might want to call it the data management cloud that starts to get into database and some other areas but but the concept of an abstraction layer that hides that underlying complexity of all the clouds and allows you to protect your data irrespective of location. That's to me that's how you get control of your data which is kind of point number three. And we heard Sandy this morning talking about embrace, manage and protect your data properly. It can be the defining disruptive difference for an organization, which I agree. However, I want to play devil's advocate in the sense that I think the only way you can get control of your data is do you have to embrace that sprawl in that complexity and admit you're not gonna shove it all into a single monolithic source of truth that those days are over. You have to you have to realize that the world is decentralized, It's coming it's here. So we have to implement automation and software to Federated governance and policy and security and privacy and data protection across that abstraction layer that I just just describe someone. Let's talk about that. What are your thoughts? >>Yeah. And I said that earlier too and Sonya is absolutely right. You have to embrace that. You figure out how to make it a competitive advantage. No workload left behind Commonwealth customers are able to protect everything from S 400 to dynamics 3 65 in the cloud and everything in between. Right. So microservices app multi cloud today we're top solution provider for the top clouds. We talked to Microsoft order today, AWS DCP we are driving exabytes of data and protecting exabytes of data. That is our strategic advantage. As you said, you cannot leave you know, strategies behind and say you know what that workload. Not interesting anymore with your data is in there. So that that is the approach that comprehensive platform and then I'm built on that. You start seeing protection grade, not data security, how to use tackle that intelligence from data insights from data compliance challenges my e discovery challenges. So being able to tackle those things ecosystem very key. How do I build on top of this intelligence, data services platform and ecosystem to take advantage of my data. These are all the layers that we believe. You know, it's very differentiated compared to anyone else out there. We're not forcing anyone into a single architecture and saying this is the best because you know what you have learned from 25 years, there's no such thing as one single best architecture. >>Oh, I asked 401 of the most innovative systems in the day. >>Uh but at the >>point of we talked about all the sprawl, this makes ransomware more difficult because an insidious because of the expanding supply chain, the ecosystem, the threat surface. And really the sophistication of the adversary, we've kind of talked about that and and and really new techniques are the Attackers are going mainstream. So but you know, I want to give you the last word here, I want to address two things if you would. Security. Like what's the big news there? Why the big deal and why con vault bring us home with the big picture of your differentiators? >>Absolutely. So you mentioned ransomware? Bad guys always looking to find those exit drawers and break it, Break it down security. I q we're proud to launch this today. It's kind of brings together the culmination of a lot of security that we have done allows customers to be proactive in terms of, you know, we've brought in Gamification into that security i aspect like make it easy and almost make it fun to make sure you're plugging all the holes so that your last mile of defense is secure, then you figure out how you can become more proactive. I have data intelligence that the security tools don't when the bad guys start sniffing around the data or anomaly detection and machine learning the ability to bring that intelligence a highly, you know, relevant signal into the security tools, building that bridge. And lastly, what happens when the, you know, worst case scenario happens almost like a rewind button to go back on your data. Look this is where malware came in and now you're able to just go back and delete that. So that's security, I. Q. Amazing. Or you know, customers are going to try it out and the live hands on lab that's happening and you know, there are feedback has been, this is just brilliant, they love it. So, one more, you know, innovation, we keep doing this, we go we're setting the bar a year ago, we launched them CSS, you know, air gap copy in the cloud, you know, a few weeks ago now we're saying, oh we can also do it right, well we have now innovative to the next level that's combo, you know, bringing it on why combo, 25 years of innovation, you know, it is just amazing how the company had the vision to build a distributed architecture. You talked about a distributed world are beauties, we're not forcing preference customers might have self managed applications that they want, you know, to be used software, they might have the need in some locations to have everything integrated with an appliance, you know, new workloads in the cloud. Let me see if I can start shifting to the data management as a service, which is really the next wave in the industry. And then finally, you know, what about that whole distribution that's happening again. So people will be, you know, we have that unique ability to build a platform. We have amazing ecosystem partners and the biggest companies in the world. Trust us as you heard, you know, throughout the show. So that's what's comin, you know, sustain technology differentiation to make our customers really realize their vision of, you know, leveraging their data as an asset. >>Nice job knows, I love it. Okay, that's a wrap from convoked connections 2021 this is dave vellante from an ocean air and the entire conv all team and the cube team encouraging to come back and check out the on demand videos for anything that you miss tell a friend, let us know what you think for everyone here at convoked connections. 21. Thanks for watching and we'll see you next time. Yeah. >>Mhm Yeah

>> From theCUBE studios in Palo Alto and Boston, bringing you data-driven insights from theCUBE in ETR. This is Breaking Analysis with Dave Vellante. >> Every CEO is figuring out the right balance for new hybrid business models. Now, regardless of the chosen approach, which is going to vary, technology executives, they understand they have to accelerate their digital and build resilience as well as optionality into their platforms. Now, this is driving a dramatic shift in IT investments. And at the macro level, we expect total spending to increase at as much as 8% or even more in 2021, compared to last year's contraction. Investments in cybersecurity, cloud collaboration that are enabling hybrid work as well as data, including analytics, AI, and automation are at the top of the spending priorities for CXOs. Hello everyone. And welcome to this week's Wiki Bond Cube insights, powered by ETR. In this Breaking Analysis, we're pleased to welcome back Erik Bradley, who is the chief engagement strategist at our partner, ETR. Now in this segment, we're going to share some of the latest findings from ETR's surveys and provide our commentary on what it means for the markets, for sellers, and for buyers. Erik, great to see you, my friend. Welcome back to Breaking Analysis. >> Thank you for having me, always enjoy it. We've got some fresh data to talk about on this beautiful summer Friday, so I'm ready to go. >> All right. I'm excited too. Okay, last year we saw a contraction in IT spending by at least 5%. And now we're seeing a snapback to, as I said, at least 8% growth relative to last year. You got to go back to 2007 just before the financial crisis to see this type of top line growth. The shift to hybrid work, it's exposed us to new insidious security threats. And we're going to discuss that in a lot more detail. Cloud migration of course picked up dramatically last year, and based on the recent earnings results of the big cloud players, for now we got two quarters of data, that trend continues as organizations are accelerating their digital platform build-outs, and this is bringing a lot of complexity and a greater need for so-called observability solutions, which Erik is going to talk about extensively later on in this segment. Data, we think is entering a new era of de-centralization. We see organizations not only focused on analytics and insights, but actually creating data products. Leading technology organizations like JP Morgan, they're heavily leaning into this trend toward packaging and monetizing data products. And finally, as part of the digital transformation trend, we see no slow down in spending momentum for AI and automation, generally in RPA specifically. Erik, anything you want to add to that top level narrative? >> Yeah, there's a lot to take on the macro takeaways. The first thing I want to state is that that 8, 8.5% number that started off at just 3 to 4% beginning of the year. So as the year has continued, we are just seeing this trend in budgets continue to accelerate, and we don't have any reason to believe that's going to stop. So I think we're going to just keep moving on heading into 2021. And we're going to see a banner year of spend this year and probably next as well. >> All right, now we're going to bring up a chart that shows kind of that progression here of spending momentum. So Erik, I'm going to let you comment on this chart that tracks those projections over time. >> Erik: Yeah. Great. So thank you very much for pulling this up. As you can see in the beginning part of the year, when we asked people, "What do you plan to spend throughout 2021?" They were saying it would be about a 4% increase. Which we were happy with because as you said last year, it was all negative. That continues to accelerate and is only hyper accelerating now as we head into the back half of the year. In addition, after we do this data, I always host a panel of IT end users to kind of get their feedback on what we collected, to a man, every one of them expects continued increase throughout next year. There are some concerns and uncertainty about what we're seeing right now with COVID, but even with that, they're planning their budgets now for 2022 and they're planning for even further increases going forward. >> Dave: Great, thank you. So we circled that 8%. That's really kind of where we thought it was going to land. And so we're happy with that number, but let's take a look at where the action is by technology sector. This chart that we're showing you here, it tracks spending priorities back to last September. When I believe that was the point, Erik, that cyber became the top priority in the survey, ahead of cloud collaboration, analytics, and data, and the other sectors that you see there. Now, Erik, we should explain. These areas, they're the top seven, and they outrank all the other sectors. ETR tracks many, many other sectors, but please weigh in here and share your thoughts on this data. >> Erik: Yeah. Security, security, security. It hasn't changed. It had really hasn't. The hybrid work. The fact that you're behind the firewall one day and then you're outside working from home the next, switching in and out of networks. This is just a field day for bad actors. And we have no choice right now, but to continue to spend, because as you're going to talk about in a minute, hybrid's here to stay. So we have to figure out a way to secure behind the firewall on-prem. We also have to secure our employees and our assets that are not in the office. So it is a main priority. One of the things that point out on this chart, I had a couple of ITN users talk to me about customer experience and automation really need to move from the right part of that chart to the left. So they're seeing more in what you were talking about in RPA and automation, starting to creep up heading into next year. As cloud migration matures, as you know, cybersecurity spending has been ramping up. People are going to see a little bit more on the analytics and a little bit more on the automation side going forward. >> Dave: Great. Now, this next data view- well, first of all, one of the great things about the ETR dataset is that you can ask key questions and get a time series. And I will tell you again, I go back to last March, ETR hit it. They were the first on the work from home trend. And so if you were on that trend, you were able to anticipate it. And a lot of investors I think took advantage of that. Now, but we've shown this before, but there's new data points that we want to introduce. So the data tracks how CIOs and IT buyers have responded to the pandemic since last March. Still 70% of the organizations have employees working remotely, but 39% now have employees fully returning to the office and Erik, the rest of the metrics all point toward positives for IT spending, although accelerating IT deployments there at the right peaked last year, as people realized they had to invest in the future. Your thoughts? >> Erik: Yeah, this is the slide for optimism, without a doubt. Of the entire macro survey we did, this is the most optimistic slide. It's great for overall business. It's great for business travel. This is well beyond just IT. Hiring is up. I've had some people tell me that they possibly can't hire enough people right now. They had to furlough employees, they had to stop projects, and they want to re accelerate those now. But talent is very hard to find. Another point to you about your automation and RPA, another underlying trend for there. The one thing I did want to talk about here is the hybrid workplace, but I believe there's another slide on it. So just to recap on this extremely optimistic, we're seeing a lot of hiring. We're seeing increased spending, and I do believe that that's going to continue. >> Yeah I'm glad you brought that up because a session that you and I did a while ago, we pointed out, it was earlier this year, that the skill shortage is one potential risk to our positive scenario. We'll keep an eye on that, but so I want to show another set of data that we've showed previously, but ETR again, has added some new questions in here. So note here that 60% of employees still work remotely with 33% in a hybrid model currently, and the CIO's expect that to land on about 42% hybrid workforce with around 30% working remotely, which is around, it's been consistent by the way on your surveys, but that's about double the historic norm, Eric. >> Erik: Yeah, and even further to your point Dave, recently I did a panel asking people to give me some feedback on this. And three of those four experts basically said to me, if we had greed run this survey right now, that even more people would be saying remote. That they believe that that number, that's saying they're expecting that number of people to be back in office, is actually too optimistic. They're actually saying that maybe if we had- cause as a survey launched about six, seven weeks ago before this little blip on the radar, before the little COVID hiccup we're seeing now, and they're telling me that they believe if we reran this now that it would be even more remote work, even more hybrid and less returned to the office. So that's just an update I wanted to offer on this slide. >> Dave: Yeah. Thank you for that. I mean, we're still in this kind of day to day, week to week, month to month mode, but I want to do a little double click on this. We're not going to share this data, but there was so much ETR data. We got to be selective. But if you double click on the hybrid models, you'll see that 50% of organizations plan to have time roughly equally split between onsite and remote with again around 30 or 31% mostly remote, with onsite space available if they need it. And Erik, very few don't plan to have some type of hybrid model, at least. >> Yeah, I think it was less than 10% that said it was going to be exclusively onsite. And again, that was a more optimistic scenario six, seven weeks ago than we're seeing right now throughout the country. So I agree with you, hybrid is here to stay. There really is no doubt about it. from everyone I speak to when, you know, I basically make a living talking to IT end users. Hybrid is here to stay. They're planning for it. And that's really the drive behind the spending because you have to support both. You have to give people the option. You have to, from an IT perspective, you also have to support both, right? So if somebody is in office, I need the support staff to be in office. Plus I need them to be able to remote in and fix something from home. So they're spending on both fronts right now. >> Okay. Let's get into some of the vendor performance data. And I want to start with the cloud hyperscalers. It's something that we followed pretty closely. I got some Wiki bond data, that we just had earnings released. So here's data that shows the Q2 revenue shares on the left-hand side in the pie and the growth rates for the big four cloud players on the right hand side. It goes back to Q1 2019. Now the first thing I want to say is these players generated just under $39 billion in the quarter with AWS capturing 50% of that number. I said 39, it was 29 billion, sorry, with AWS capturing 50% of that in the quarter. As you're still tracking around a third in Alibaba and GCP in the, you know, eight or 9% range. But what's most interesting to me, Erik, is that AWS, which generated almost 15 billion in the quarter, was the only player to grow its revenue, both sequentially and year over year. And Erik, I think the street is missing the real story here on Amazon. Amazon announced earnings on Thursday night. The company had a 2% miss on the top line revenues and a meaningful 22% beat on earnings per share. So the retail side of the business missed its revenue targets, so that's why everybody's freaked out. But AWS, the cloud side, saw a 4% revenue beat. So the stock was off more than 70% after hours and into Friday. Now to me, a mix shift toward AWS, that's great news for investors. Now, tepid guidance is a negative, but the shift to a more profitable cloud business is a huge positive. >> Yeah, there's a lot that goes into stock price, right? I remember I was a director of research back in the day. One of my analysts said to me, "Am I crazy for putting a $1,000 target on Amazon?" And I laughed and I said, "No, you're crazy if you don't make it $2,000." (both chuckling) So, you know, at that time it was basically the mix shift towards AWS. You're a thousand percent right. I think the tough year over year comps had something to do with that reaction. That, you know, it's just getting really hard. What's that? The law of large numbers, right? It's really hard to grow at that percentage rate when you're getting this big. But from our data perspective, we're seeing no slowdown in AWS, in cloud, none whatsoever. The only slowdown we're seeing in cloud is GCP. But to, you know, to focus on AWS, extremely strong across the board and not only just in cloud, but in all their data products as well, data and analytics. >> Yeah and I think that the AWS, don't forget folks, that funds Amazon's TAM expansion into so many different places. Okay. As we said at the top, the world of digital and hybrid work, and multi-cloud, it's more complicated than it used to be. And that means if you need to resolve issues, which everybody does, like poor application performance, et cetera, what's happening at the user level, you have to have a better way to sort of see what's going on. And that's what the emergence of the observability space is all about. So Erik, let me set this up and you have a lot of comments here because you've recently had some, and you always have had a lot of round table discussions with CXOs on this topic. So this chart plots net score or spending momentum on the vertical axis, and market share or pervasiveness in the dataset on the horizontal axis. And we inserted a table that shows the data points in detail. Now that red dotted line is just sort of Dave Vellante's subjective mark in the sand for elevated spending levels. And there are three other points here. One is Splunk as well off is two-year peak, as highlighted in the red, but Signal FX, which Splunk acquired, has made a big move northward this last quarter. As has Datadog. So Erik, what can you share with us on this hot, but increasingly crowded space? >> Yeah. I could talk about the space for a long time. As you know, I've gotten some flack over the last year and a half about, you know, kind of pointing out this trend, this negative trend in Splunk. So I do want to be the first one to say that this data set is rebounding. Splunk has been horrific in our data for going back almost two years now, straight downward trend. This is the first time we're seeing any increase, any positivity there. So I do want to be fair and state that because I've been accused of being a little too negative on Splunk in the past. But I would basically say for observability right now, it's a rising tide lifts all boats, if I can use a New England phrase. The data across the board in analytics for these observability players is up, is accelerating. None more so than Datadog. And it's exactly your point, David. The complexity, the increased cloud migration is a perfect setup for Datadog, which is a cloud native. It focuses on microservices. It focuses on cloud observability. Old Splunk was just application monitoring. Don't get me wrong, they're changing, but they were on-prem application monitoring, first and foremost. Datadog came out as cloud native. They, you know, do microservices. This is just a perfect setup for them. And not only is Datadog leading the observability, it's leading the entire analytics sector, all of it. Not just the observability niche. So without a doubt, that is the strongest that we're seeing. It's leading Dynatrace new Relic. The only one that really isn't rebounding is Cisco App Dynamics. That's getting the dreaded legacy word really attached to it. But this space is really on fire, elastic as well, really doing well in this space. New Relic has shown a little bit of improvement as well. And what I heard when I asked my panelists about this, is that because of the maturity of cloud migration, that this observability has to grow. Spending on this has to happen. So they all say the chart looks right. And it's really just about the digital transformation maturity. So that's largely what they think is happening here. And they don't really see it getting, you know, changing anytime soon. >> Yeah, and I would add, and you see that it's getting crowded. You saw a service now acquired LightStep, and they want to get into the game. You mentioned, you know, last deck of the elk stack is, you know, the open source alternative, but then we see a company who's raised a fair amount of money, startup, chaos search, coming in, going after kind of the complexity of the elk stack. You've got honeycomb, which has got a really innovative approach, Jeremy Burton's company observes. So you have venture capital coming in. So we'll see if those guys could be disruptive enough or are they, you know, candidates to get acquired? We'll see how that all- you know that well. The M and A space. You think this space is ripe for M and A? >> I think it's ripe for consolidation, M and A. Something has to shake out. There's no doubt. I do believe that all of these can be standalone. So we shall see what's happened to, you mentioned the Splunk acquisition of Signal FX, just a house cleaning point. That was really nice acceleration by Signal FX, but it was only 20 citations. We'd looked into this a little bit deeper. Our data scientists did. It appears as if the majority of people are just signaling spunk and not FX separately. So moving forward for our data set, we're going to combine those two, so we don't have those anomalies going forward. But that type of acquisition does show what we should expect to see more of in this group going forward. >> Well that's I want to mention. That's one of the challenges that any data company has, and you guys do a great job of it. You're constantly having to reevaluate. There's so much M and A going on in the industry. You've got to pick the right spots in terms of when to consolidate. There's some big, you know, Dell and EMC, for example. You know, you've beautifully worked through that transition. You're seeing, you know, open shift and red hat with IBM. You just got to be flexible. And that's where it's valuable to be able to have a pipeline to guys like Erik, to sort of squint through that. So thank you for that clarification. >> Thank you too, because having a resource like you with industry knowledge really helps us navigate some of those as well for everyone out there. So that's a lot to do with you do Dave, >> Thank you. It's going to be interesting to watch Splunk. Doug Merritt's made some, you know, management changes, not the least of which is bringing in Teresa Carlson to run go to market. So if you know, I'd be interested if they are hitting, bouncing off the bottom and rising up again. They have a great customer base. Okay. Let's look at some of the same dimensions. Go ahead. You got a comment? >> A few of ETR's clients looked at our data and then put a billion dollar investment into it too. So obviously I agree. (Dave laughing) Splunk is looking like it's set for a rebound, and it's definitely something to watch, I agree. >> Not to rat hole in this, but I got to say. When I look back, cause theCUBE gives us kind of early visibility. So companies with momentum and you talk to the customers that all these shows that we go to. I will tell you that three companies stood out last decade. It was Splunk. It was Service Now and Tableau. And you could tell just from just discussions with their customers, the enthusiasm in that customer base. And so that's a real asset, and that helps them build them a moat. So we'll see. All right, let's take a look at the same dimensions now for cyber. This is cybersecurity net score in the vertical, and market share in the horizontal. And I filtered by in greater than a hundred shared in because just gets so crowded. Erik, the only things I would point out here is CrowdStrike and Zscaler continue to shine, CyberArk also showing momentum over that 40% line. Very impressively, Palo Alto networks, which has a big presence in the market. They've bounced back. We predicted that a while back. Your round table suggested people like working with Palo Alto. They're a gold standard. You know, we had reported earlier on that divergence with four to net in terms of valuation and some of the challenges they had in cloud, clearly, you know, back with the momentum. And of course, Microsoft in the upper, right. It's just, they're literally off the charts and obviously a major player here, but your thoughts on cyber? >> Erik: Yeah. Going back to the backdrop. Security, security, security. It has been the number one priority going back to last September. No one sees it changing. It has to happen. The threat vectors are actually expanding and we have no choice but to spend here. So it is not surprising to see. You did name our three favorite names. So as you know, we look at the dataset, we see which ones have the most positive inflections, and we put outlooks on those. And you did mention Zscaler, Okta and CrowdStrike, by far the three standouts that we're seeing. I just recently did a huge panel on Okta talking about their acquisition of Auth Zero. They're pushed into Sale Point space, trying to move just from single sign on and MFA to going to really privileged account management. There is some hurdles there. Really Okta's ability to do this on-prem is something that a little bit of the IT end users are concerned about. But what we're seeing right now, both Okta and Auth Zero are two of the main adopted names in security. They look incredibly well set up. Zscaler as well. With the ZTNA push more towards zero trust, Zscaler came out so hot in their IPO. And everyone was wondering if it was going to trail off just like Snowflake. It's not trailing off. This thing just keeps going up into the right, up into the right. The data supports a lot of tremendous growth for the three names that you just mentioned. >> Yeah. Yeah. I'm glad you brought up Auth Zero. We had reported on that earlier. I just feel like that was a great acquisition. You had Okta doing the belly to belly enterprise, you know, selling. And the one thing that they really lacked was that developer momentum. And that's what Auth Zero brings. Just a smart move by Todd McKinnon and company. And I mean, so this, you know, I want to, I want to pull up another chart show a quick snapshot of some of the players in the survey who show momentum and have you comment on this. We haven't mentioned Snowflake so far, but they remain again with like this gold standard of net score, they've consistently had those high marks with regard to spending velocity. But here's some other data. Erik, how should we interpret this? >> Erik: Yeah, just to harp on Snowflake for a second. Right, I mean the rich get richer. They came out- IPO was so hyped, so it was hard for us as a research company to say, "Oh, you know, well, you know, we agree." But we did. The data is incredible. You can't beat the management team. You can't beat what they're doing. They've got so much cash. I can't wait to see what they do with it. And meanwhile, you would expect something that debuted with that high of a net score, that high of spending velocity to trail off. It would be natural. It's not Dave, it's still accelerating. It's gone even higher. It's at all time highs. And we just don't see it stopping anytime soon. It's a really interesting space right now. Maybe another name to look at on here that I think is pretty interesting, kind of a play on return to business is Kupa. It's a great project expense management tool that got hit really hard. Listen, traveling stopped, business expense stopped, and I did a panel on it. And a lot of our guys basically said, "Yeah, it was the first thing I cut." But we're seeing a huge rebound in spending there in that space. So that's a name that I think might be worth being called out on a positive side. Negative, If you look down to the bottom right of that chart, unfortunately we're seeing some issues in RingCentral and Zoom. Anything that's sort of playing in this next, you know, video conferencing, IP telephony space, they seem to be having really decelerating spending. Also now with Zoom's acquisition of five nine. I'm not really sure how RingCentral's going to compete on that. But yeah, that's one where we debuted for the first time with a negative outlook on that name. And looking and asking to some of the people in our community, a lot of them say externally, you still need IP telepany, but internally you don't. Because the You Cast communication systems are getting so sophisticated, that if I have Teams, if I have Slack, I don't need phones anymore. (chuckling) That you and I can just do a Slack call. We can do a Teams call. And many of them are saying I'm truly ripping out my IP Telepany internally as soon as possible because we just don't need it. So this whole collaboration, productivity space is here to stay. And it's got wide ranging implications to some of these more legacy type of tools. >> You know, one of the other things I'd call out on this chart is Accenture. You and I had a session earlier this year, and we had predicted that that skill shortage was going to lead to an uptick in traditional services. We've certainly seen that. I mean, IBM beat its quarter on the strength of services largely. And seeing Accenture on that is I think confirmation. >> Yeah that was our New Year prediction show, right Dave? When we made top 10 predictions? >> That's right. That was part of our predictions show. Exactly, good memory. >> The data is really showing that continue. People want the projects, they need to do the projects, but hiring is very difficult. So obviously the number one beneficiary there are going to be the Accentures of the world. >> All right. So let's do a quick wrap. I'm going to make a few comments and then have you bring us home, Erik. So we laid out our scenario for the tech spending rebound. We definitely believe last year tracked downward, along with GDP contraction. It was interesting. Gardner doesn't believe, at least factions of Gardner don't believe there's a correlation between GDP and tech spending. But, you know, I personally think there generally is some kind of relatively proportional pattern there. And I think we saw contraction last year. People are concerned about inflation. Of course, that adds some uncertainty. And as well, as you mentioned around the Delta variant. But I feel as though that the boards of directors and CEOs, they've mandated that tech execs have to build out digital platforms for the future. They're data centric. They're highly automated, to your earlier points. They're intelligent with AI infused, and that's going to take investment. I feel like the tech community has said, "Look, we know what to do here. We're dealing with hybrid work. We can't just stop doing what we're doing. Let's move forward." You know, and as you say, we're flying again and so forth. You know, getting hybrid right is a major priority that directly impacts strategies. Technology strategies, particularly around security, cloud, the productivity of remote workers with collaboration. And as we've said many times, we are entering a new era of data that's going to focus on decentralized data, building data products, and Erik let's keep an eye on this observability space. Lot of interest there, and buyers have a number of choices. You know, do they go with a specialist, as we saw recently, we've seen in the past, or did they go with the generalist like Service Now with the acquisition of LightStep? You know, it's going to be interesting. A lot of people are going to get into this space, start bundling into larger platforms. And so as you said, there's probably not enough room for all the players. We're going to see some consolidation there. But anyway, let me give you the final word here. >> Yeah, no, I completely agree with all of it. And I think your earlier points are spot on, that analytics and automation are certainly going to be moving more and more to that left of that chart we had of priorities. I think as we continue that survey heading into 2022, we'll have some fresh data for you again in a few months, that's going to start looking at 2022 priorities and overall spend. And the one other area that I keep hearing about over and over and over again is customer experience. There's a transition from good old CRM to CXM. Right now, everything is digital. It is not going away. So you need an omni-channel support to not only track your customer experience, but improve it. Make sure there's a two way communication. And it's a really interesting space. Salesforce is going to migrate into it. We've got Qualtrics out there. You've got Medallia. You've got FreshWorks, you've got Sprinkler. You got some names out there. And everyone I keep talking to on the IT end user side keeps bringing up customer experience. So let's keep an eye on that as well. >> That's a great point. And again, it brings me back to Service Now. We wrote a piece last week that's sort of, Service Now and Salesforce are on a collision course. We've said that for many, many years. And you've got this platform of platforms. They're just kind of sucking in different functions saying, "Hey, we're friends with everybody." But as you know Erik, software companies, they want to own it all. (both chuckling) All right. Hey Erik, thank you so much. I want to thank you for coming back on. It's always a pleasure to have you on Breaking Analysis. Great to see you. >> Love the partnership. Love the collaboration. Let's go enjoy this summer Friday. >> All right. Let's do. Okay, remember everybody, these episodes, they're all available as podcasts, wherever you listen. All you got to do is search Breaking Analysis Podcast, click subscribe to the series. Check out ETR's website at etr.plus. They've just launched a new website. They've got a whole new pricing model. It's great to see that innovation going on. Now remember we also publish a full report every week on WikiBond.com and SiliconAngle.com. You can always email me, appreciate the back channel comments, the metadata insights. David.Vellante@SiliconAngle.com. DM me on Twitter @DVellante or comment on the LinkedIn posts. This is Dave Vellante for Erik Bradley and theCUBE insights powered by ETR. Have a great week, a good rest of summer, be well. And we'll see you next time. (inspiring music)

(bright upbeat music) >> Hello, and welcome back to the DockerCon 2021 virtual coverage. I'm John Furrie host of theCUBE here in Palo Alto with a remote interview with a great guest Cuban alumni, Jim Walker VP of Product Marketing at Cockroach Labs. Jim, great to see you remotely coming into theCUBE normally we're in person, soon we'll be back in real life. Great to see you. >> Great to see you as well John, I miss you. I miss senior live and in person. So this has got to do, I guess right? >> We we had the first multi-cloud event in New York city. You guys had was I think one of the last events that was going on towards the end of the year before the pandemic hit. So a lot's happened with Cockroach Labs over the past few years, accelerated growth, funding, amazing stuff here at DockerCon containerization of the world, containers everywhere and all places hybrid, pure cloud, edge everywhere. Give us the update what's going on with Cockroach Labs and then we'll get into what's going on at DockerCon. >> Yeah Cockroach Labs, this has been a pretty fun ride. I mean, I think about two and a half years now and John it's been phenomenal as the world kind of wakes up to a distributed systems and the containerization of everything. I'm happy we're at DockerCon talking about containerization 'cause I think it has radically changed the way we think about software, but more importantly it's starting to take hold. I think a lot of people would say, oh, it's already taken hold but if you start to think about like just, these kind of modern applications that are depending on data and what does containerization mean for the database? Well, Cockroach has got a pretty good story. I mean, gosh, before Escape I think the last time I talked to you, I was at CoreOS and we were playing the whole Kubernetes game and I remember Alex Povi talking about GIFEE Google infrastructure for everyone or for everyone else I should say. And I think that's what we've seen that kind of happened with the infrastructure layer but I think that last layer of infrastructure is the database. Like I really feel like the database is that dividing line between the business logic and infrastructure. And it's really exciting to see, just massive huge customers come to Cockroach to rethink what the database means in cloud, right? What does the database mean when we moved to distributed systems and that sort of thing, and so, momentum has been building here, we are, upwards of, oh gosh, over 300 paying customers now, thousands of Cockroach customers in the wild out there but we're seeing this huge massive attraction to CockroachCloud which is a great name. Come on, Johnny, you got to say, right? And our database as a service. So getting that out there and seeing the uptake there has just been, it's been phenomenal over the past couple of years. >> Yeah and you've got to love the Cockroach name, love it, survive nuclear war and winter all that good stuff as they say, but really the reality is that it's kind of an interesting play on words because one of the trends that we've been talking about, I mean, you and I've been telling this for years with our CUBE coverage around Amazon Web Services early on was very clear about a decade ago that there wasn't going to be one database to rule the world. They're going to many, many databases. And as you started getting into these cloud native deployments at scale, use your database of choice was the developer ethos just whatever it takes to get the job done. Now you start integrating this in a horizontally scalable way with the cloud, you have now new kinds of scale, cloud scale. And it kind of changed the game on the always on availability question which is how do I get high availability? How do I keep things running? And that is the number one developer challenge whether it's infrastructure as code, whether it's security shifting left, it all comes down to making sure stuff's running at scale and secure. Talk about that. >> Yeah, absolutely and it's interesting it's been, like I said, this journey in this arc towards distributed systems and truly like delivery of what people want in the cloud, it's been a long arc and it's been a long journey and I think we're getting to the point where people, they are starting to kind of bake resilience and scale into their applications and I think that's kind of this modern approach. Look we're taking legacy databases today. There are people are kind of lift and shift, move them into the cloud, try to run them there but they aren't just built for that infrastructure like the there's a fundamentally different approach and infrastructure when it talks, when you talk about cloud it's one of the reasons why John early on your conversations with the AWS Team and what they did, it's like, yeah, how do we give resilient and ubiquitous and always on scalable kind of infrastructure people. Well, that's great for those layers but when you start to get into the software that's running on these things, it isn't lift and shift and it's not even move and improve. You can't like just take a legacy system and change one piece of it to make it kind of take advantage of the scale and the resilience and the ubiquity of the cloud, because there's very very explicit challenges. For us, it's about re-architect and rebuild. Let's tear the database down and let's rethink it and build from the ground up to be cloud native. And I think the technologies that have done that, that have kind of built from scratch, to be cloud native are the ones that are I believe, three years from now that's what we're going to be talking about. I mean, this comes back to again, like the Genesis of what we did is Google Cloud Spanner. Spanner white paper and what Google did, they didn't build, they didn't use an existing database because they needed something for a transactional relational database. They hire a bunch of really incredible engineers, right? And I got like Jeff Dean and Sanjay Ghemawat over there, like designing and doing all these cool things, they build and I think that's what we're seeing and I think that's, to me the exciting part about data in the cloud as we move forward. >> Yeah, and I think the Google cloud infrastructure, everyone I think that's the same mindset for Amazon is that I want all the scale, but I don't want to do it like over 10 years I to do it now, which I love I want to get back to in a second, but I want to ask you specifically this definition of containerization of the database. I've heard that kicked around, love the concept. I kind of understand what it means but I want you to define it for us. What does it mean when someone says containerizing the database? >> Yeah, I mean, simply put the database in container and run it and that's all that I can think that's like, maybe step one I think that's kind of lift and shift. Let's put it in a container and run it somewhere. And that's not that hard to do. I think I could do that. I mean, I haven't coded in a long time but I think I could figure that out. It's when you start to actually have multiple instances of a container, right? And that's where things get really, really tricky. Now we're talking about true distributed systems. We're talking about how do you coordinate data? How do you balance data across multiple instances of a database, right? How do you actually have fail over so that if one node goes down, a bunch of them are still available. How do you guarantee transactional consistency? You can't just have four instances of a database, all with the same information in it John without any sort of coordination, right? Like you hit one node and you hit another one in the same account which transaction wins. And so the concepts in distributed systems around there's this thing called the cap theorem, there's consistency, availability, and partition tolerance and actually understanding how these things work especially for data in distributed systems, to make sure that it's going to be consistent and available and you're going to scale those things are not simple to solve. And again, it comes back to this. I don't think you can do it with legacy database. You kind of have to re-architect and it comes down to where data is stored, it comes down to how it's replicated, it comes down to really ultimately where it's physically located. I think when you deploy a database you think about the logical model, right? You think about tables, and normalization and referential integrity. The physical location is extremely important as we kind of moved to that kind of containerized and distributed systems, especially around data. >> Well, you guys are here at DockerCon 2021 Cockroach Labs good success, love the architectural flexibility that you guys offer. And again, bringing that scale, like you mentioned it's awesome value proposition, especially if people want to just program the infrastructure. What's going on with with DockerCon specifically a lot of talk about developer productivity, a lot of talk about collaboration and trust with containers, big story around security. What's your angle here at DockerCon this year? What's the big reveal? What's the discussion? What's the top conversation? >> Yeah, I mean look at where we are a containerized database and we are an incredibly great choice for developers. For us, it's look at there's certain developer communities that are important on this planet, John, and this is one of them, right? This is I don't know a developer doesn't have that little whale up in their status bar, right? And for us, you know me man, I believe in this tech and I believe that this is something that's driven and greatly simplify our lives over the next two to three to 10 to 15 years. And for us, it's about awareness. And I think once people see Cockroach, they're like oh my God, how did I ever even think differently? And so for us, it's kind of moving in that direction. But ultimately our vision where we want to be, is we want to abstract the database to a SQL API in the cloud. We want to make it so simple that I just have this rest interface, there's end points all over the planet. And as a developer, I never have to worry about scale. I never have to worry about DR right? It's always going to be on. And most importantly, I don't have to worry about low latency access to data no matter where I'm at on the planet, right? I can give every user this kind of sub 50 millisecond access to data or sub 20 millisecond access to data. And that is the true delivery of the cloud, right? Like I think that's what the developer wants out of the cloud. They want to code against a service like, and it's got to be consumption-based and you secure and I don't want to have to pay for stuff I'm not using and that all those things. And so, for us, that's what we're building to, and interacting in this environment is critical for us because I think that's where audiences. >> I want to get your thoughts on you guys do have success with a couple of different personas and developers out there, groups, classic developers, software developers which is this show is that DockerCon full of developers KubeCon a lot of operators cool, and some dads, but mostly cloud native operations. Here's a developer shops. So you guys got to hit the developers which really care about building fast and building the scale and last with security. Architects you had success with, which is the classic, cloud architecture, which now distributed computing, we get that. But the third area I would call the kind of the role that both the architects and the developers had to take on which is being the DevOps person or then becomes the SRE in the group, right? So most startups have the DevOps team developers. They do DevOps natively and within every role. So they're the same people provisioning. But as you get larger and an enterprise, the DevOps role, whether it's in a team or group takes on this SRE site reliability engineer. This is a new dynamic that brings engineering and coding together. It's like not so much an ops person. It's much more of like an engineering developer. Why is that role so important? And we're seeing more of it in dev teams, right? Seeing an SRE person or a DevOps person inside teams, not a department. >> Yeah, look, John, we, yeah, I mean, we employ an army of SREs that manage and maintain our CockroachCloud, which is CockroachDB as a service, right? How do you deliver kind of a world-class experience for somebody to adopt a managed service a database such as ours, right? And so for us, yeah I mean, SREs are extremely important. So we have personal kind of an opinion on this but more importantly, I think, look at if you look at Cockroach and the architecture of what we built, I think Kelsey Hightower at one point said, I am going to probably mess this up but there was a tweet that he wrote. It's something like, CockroachDB is the Spanner as Kubernetes is the board. And if you think about that, I mean that's exactly what this is and we built a database that was actually amenable to the SRE, right? This is exactly what they want. They want it to scale up and down. They want it to just survive things. They want to be able to script this thing and basically script the world. They want to actually, that's how they want to manage and maintain. And so for us, I think our initial audience was definitely architects and operators and it's theCUBE con crowd and they're like, wow, this is cool. This is architected just like Kubernetes. In fact, like at etcd, which is a key piece of Kubernetes but we contribute back up to NCD our raft implementation. So there's a lot of the same tech here. What we've realized though John, with database is interesting. The architect is choosing a database sometimes but more often than not, a developer is choosing that database. And it's like they go out, they find a database, they just start building and that's what happens. So, for us, we made a very critical decision early on, this database is wire compatible with Postgres and it speaks to SQL syntax which if you look at some of the other solutions that are trying to do these things, those things are really difficult to do at the end. So like a critical decision to make sure that it's amenable so that now we can build the ORMs and all the tools that people would use and expect that of Postgres from a developer point of view, but let's simplify and automate and give the right kind of like the platform that the SREs need as well. And so for us the last year and a half is really about how do we actually build the right tooling for the developer crowd too. And we've really pushed really far in that world as well. >> Talk about the aspect of the scale of like, say startup for instance, 'cause you made this a great example borg to Kubernetes 'cause borg was Google's internal Kubernetes, like thing. So you guys have Spanner which everyone knows is a great product at Google had. You guys with almost the commercial version of that for the world. Is there, I mean, some people will say and I'll just want to challenge you on this and we'll get your thoughts. I'm not Google, I'll never be Google, I don't need that scale. Or so how do you address that point because some people say, well this might dismiss the notion of using it. How do you respond to that? >> Yeah, John, we get this all the time. Like, I'm not global. My application's not global. I don't need this. I don't need a tank, right? I just need, like, I just need to walk down the road. You know what I mean? And so, the funny thing is, even if you're in a single region and you're building a simple application, does it need to be always on does it need to be available. Can it survive the failure of a server or a rack or an AZ it doesn't have to survive the failure of a region but I tell you what, if you're successful, you're going to want to start actually deploying this thing across multiple regions. So you can survive a backhoe hit in a cable and the entire east coast going out, right? Like, and so with Cockroach, it's real easy to do that. So it's four little SQL commands and I have a database that's going to span all those regions, right? And I think that's important but more importantly, think about scale, when a developer wants to scale, typically it's like, okay, I'm going to spin up Postgres and I'm going to keep increasing my instance size. So I'm going to scale vertically until I run out of room. And then I'm going to have to start sharding this database. And when you start doing that, it adds this kind of application complexity that nobody really wants to deal with. And so forget it, just let the database deal with all that. So we find this thing extremely useful for the single developer in a very small application but the beauty thing is, if you want to go global, great just keep that in notes. Like when that application does take off and it's the next breakthrough thing, this database going to grow with you. So it's good enough to kind of start small but it's the scale fast, it'll go global if you want to, you have that option, I guess, right? >> I mean, why wouldn't you want optionality on this at all? So clearly a good point. Let me ask you a question, take me through a use case where with Cockroach, some scenario develops nicely, you can point to the visibility of the use case for the developer and then kind of how it played out and then compare that and contrast that to a scenario that doesn't go well, like where where we're at plays out well, for an example, and then if they didn't deploy it they got hung up and went sideways. >> Yeah like Cockroach was built for transactional workloads. That that's what we are like, we are optimized for the speed of light and consistent transactions. That's what we do, and we do it very well. At least I think so, right. But I think, like my favorite customer of all of ours is DoorDash and about a year ago DoorDash came to us and said, look at we have a transactional database that can't handle the right volume that we're getting and falls over. And they they'd significant challenges and if you think about DoorDash and DoorDash is business they're looking at an IPO in the summer and going through these, you can't have any issues. So like system's got to be up and running, right? And so for them, it was like we need something that's reliable. We need something that's not going to come down. We need something that's going to scale and handle burst and these sort of things and their business is big, their businesses not just let me deliver food all the time. It's deliver anything, like be that intermediary between a good and somebody's front door. That's what DoorDash wants to be. And for us, yeah, their transactions and that backend transactional system is built on Cockroach. And that's one year ago, they needed to get experienced. And once they did, they started to see that this was like very, very valuable and lots of different workloads they had. So anywhere there's any sort of transactional workload be it metadata, be it any sort of like inventory, or transaction stuff that we see in companies, that's where people are coming to us. And it's these traditional relational workloads that have been wrapped up in these transactional relational databases what built for the cloud. So I think what you're seeing is that's the other shoe to drop. We've seen this happen, you're watching Databricks, you're watching Snowflake kind of do this whole data cloud and then the analytical side John that's been around for a long time and there's that move to the cloud. That same thing that happened for OLAP, is got to happen for OLTP. Where we don't do well is when somebody thinks that we're an analytic database. That's not what we're built for, right? We're optimized for transactions and I think you're going to continue to see these two sides of the world, especially in cloud especially because I think that the way that our global systems are going to work you don't want to do analytics across multiple regions, it doesn't make sense, right? And so that's why you're going to see this, the continued kind of two markets OLAP and OLTP going on and we're just, we're squaring that OLTP side of the world. >> Yeah talking about the transaction processing side of it when you start to change a distributed architecture that goes from core edge, core on premises to edge. Edge being intelligent edge, industrial edge, whatever you're going to have more action happening. And you're seeing, Kubernetes already kind of talking about this and with the containers you got, so you've got kind of two dynamics. How does that change the nature of, and the level of volume of transactions? >> Well, it's interesting, John. I mean, if you look at something like Kubernetes it's still really difficult to do multi-region or multicloud Kubernetes, right? This is one of those things that like you start to move Kubernetes to the edge, you're still kind of managing all these different things. And I think it's not the volumes, it's the operational nightmare of that. For us, that's federate at the data layer. Like I could deploy Cockroach across multiple Kubernetes clusters today and you're going to have one single logical database running across those. In fact you can deploy Cockroach today on top of three public cloud providers, I can have nodes in AWS, I could have nodes in GCP, I could have nodes running on VMs in my data center. Any one of those nodes can service requests and it's going to look like a single logical database. Now that to me, when we talked about multicloud a year and a half ago or whatever that was John, that's an actual multicloud application and delivering data so that you don't have to actually deal with that in your application layer, right? You can do that down in the guts of the database itself. And so I think it's going to be interesting the way that these things gets consumed and the way that we think about where data lives and where our compute lives. I think that's part of what you're thinking about too. >> Yeah, so let me, well, I got you here. One of the things on my mind I think people want to maybe get clarification on is real quick while you're here. Take a minute to explain that you're seeing a CockroachDB and CockroachCloud. There are different products, you mentioned you've brought them both up. What's the difference for the developers watching? What's the difference of the two and when do I need to know the difference between the two? >> So to me, they're really one because CockroachCloud is CockroachDB as a service. It's our offering that makes it a world-class easy to consume experience of working with CockroachDB, where we take on all the hardware we take on the SRE role, we make sure it's up and running, right? You're getting connection, stringing your code against it. And I think, that's side of our world is really all about this kind of highly evolved database and delivering that as a service and you can actually use it's CockroachDB. I think it was just gets really interesting John is the next generation of what we're building. This serverless version of our database, where this is just an API in the cloud. We're going to have one instance of Cockroach with multi-tenant database in there and any developer can actually spin up on that. And to me, that gets to be a really interesting world when the world turns serverless, and we have, we're running our compute in Lambda and we're doing all these great things, right? Or we're using cloud run and Google, right? But what's the corresponding database to actually deal with that? And that to me is a fundamentally different database 'cause what is scale in the serverless world? It's autonomous, right? What scale in the current, like Cockroach world but you kind of keep adding nodes to it, you manage, you deal with that, right? What does resilience mean in a serverless world? It's just, yeah, its there all the time. What's important is latency when you get to kind of serverless like where are these things deployed? And I think to me, the interesting part of like the two sides of our world is what we're doing with serverless and kind of this and how we actually expose the core value of CockroachDB in that way. >> Yeah and I think that's one of the things that is the Nirvana or the holy grail of infrastructure as code is making it, I won't say irrelevant, but invisible if you're really dealing with a database thing, hey I'm just scaling and coding and the database stuff is just working with compute, just whatever, how that's serverless and you mentioned Lambda that's the action because you don't want the file name and deciding what the database is just having it happen is more productivity for the developers that kind of circles back to the whole productivity message for the developers. So I totally get that I think that's a great vision. The question I have for you Jim, is the big story here is developer simplicity. How you guys making it easier to just deploy. >> John is just an extension of the last part of the conversation. I don't want to developer to ever have to worry about a database. That's what Spencer and Peter and Ben have in their vision. It's how do I make the database so simple? It's simple, it's a SQL API in the cloud. Like it's a rest interface, I code against it, I run queries against it, I never have to worry about scaling the thing. I never have to worry about creating active, passive, and primary and secondary. All these like the DevOps side of it, all this operation stuff, it's just kind of done in the background dude. And if we can build it, and it's actually there now where we have it in beta, what's the role of the cost-based optimizer in this new world that we've had in databases? How are you actually ensuring data is located close to users and we're automating that so that, when John's in Australia doing a show, his data is going to follow him there. So he has fast access to that, right? And that's the kind of stuff that, we're talking about the next generation of infrastructure John, not like we're not building for today. Like, look at Cockroach Labs is not building for like 2021. Sure, do we have something that's great. We're building something that's 22 and 23 and 24, right? Like what do we need to be as a extremely productive set of engineers? And that's what we think about all day. How do we make data easy for the developer? >> Well, Jim, great to have you on VP of Product Marketing at Cockroach Labs, we've known each other for a long time. I got to ask you while I had got you here final question is, you and I have chatted about the many waves of in open source and in the computer industry, what's your take on where we are now. And I see you're looking at it from the Cockroach Labs perspective which is large scale distributed computing kind of you're on the new side of history, the right side of history, cloud native. Where are we right now? Compare and contrast for the folks watching who we're trying to understand the importance of where we are in the industry, where are we in and what's your take? >> Yeah John I feel fortunate to be in a company such as this one and the past couple that I've like been around and I feel like we are in the middle of a transformation. And it's just like the early days of this next generation. And I think we're seeing it in a lot of ways in infrastructure, for sure but we're starting to see it creep up into the application layer. And for me, it is so incredibly exciting to see the cloud was, remember when cloud was like this thing that people were like, oh boy maybe I'll do it. Now it's like, it's anything net new is going to be on cloud, right? Like we don't even think twice about it and the coming nature of cloud native and actually these technologies that are coming are going to be really interesting. I think the other piece that's really interesting John is the changing role of open source in this whole game, because I think of open source as code consumption and community, right? I think about those and then there's license of course, I think people were always there. A lot of people wrapped around the licensing. Consumption has changed, John. Back when we were talking to Dupe, consumption was like, oh, it's free, I get this thing I could just download it use it. Well consumption over the past three years, everybody wants everything as a service. And so we're ready to pay. For us, how do we bring free back to the service? And that's what we're doing. That's what I find like I am so incredibly excited to go through this kind of bringing back free beer to open source. I think that's going to be great 'cause if I can give you a database free up to five gig or 10 gig, man and it's available all over the planet has fully featured, that's coming, that's bringing our community and our code which is all open source and this consumption model back. And I'm super excited about that. >> Yeah, free beer who doesn't like free beer of course, developers love free beer and a great t-shirt too that's soft. Make sure you get that, get the soft >> You just don't want free puppy, you know what I mean? It was just like, yeah, that sounds painful. >> Well Jim, great to see you remotely. Can't wait to see you in person at the next event. And we've got the fall window coming up. We'll see some events. I think KubeCon in LA is going to be in-person re-invent a data breast for sure we'll be in person. I know that for a fact we'll be there. So we'll see you in person and congratulations on the work at Cockroach Labs. >> Thanks, John, great to see you again. All right, this keep coverage of DockerCon 2021. I'm John Furrie your host of theCUBE. Thanks for watching.