>> Announcer: Live, from San Francisco. It's The Cube, covering Oracle Open World 2016. Brought to you by Oracle. Now, here's your host, John Furrier and Peter Burris. >> Hey, welcome back everyone, we are live here in San Francisco. This is SiliconANGLE Media's The Cube. It's our flagship program, we go out to the events and extract the signal from the noise. I'm John Furrier, the CEO of SiliconANGLE Media, joined by co-host Peter Burris all week. Three days of wall-walk of day three. He's the head of research at SiliconeANGLE Media Inc., as well as the general manager of Wikibon research. Our next guest is Roddy Martin, VP of SC Supply Chain Cloud Product Marketing at Oracle. Welcome to The Cube. >> Thank you very much for the opportunity. I look forward to the discussion. >> Thanks for coming on. Really want to hear your thought leadership around the supply chain transformation, because it might be a little bit bumpy depending upon your perspective. But is a huge opportunity going on in every single theater of where software used to be a point solution. The cloud is now an opportunity for customers to think differently, and is a catalyst for essentially a business model change as well as a fundamental data-driven change. Your thoughts on this? What do you see going on? What are the key inflection points? >> So a very interesting part of my background is I came out of the brewing industry in South Africa. and then I led the supply chain practice at AMR Research, which today is Gartner. And we did a lot of studies on, what are companies doing to lead this transformation? Because it's a transformation of the interim business operating model of a company. This is not stitching data together in the traditional supply chain system sense. So one of the very first foundations that is really fundamental, and Gartner has done a great job of carrying the search forward, is the idea that every company progresses to an interim operating model in five stages of capability, and every one of those builds on the other. So they're either reacting in stage one's problem and never saw the shortage coming and ran out of product. Stage two is I performance improve around projects. Stage three is I drive functional excellence. And stage four I start working as an engine outside an operating model. In other words, I'm driving the business from what's happening in the market and I'm making sure that supply is matching demand. So it's very interesting and it's very important to consider that as the base foundation for this whole discussion. >> So that outside is interesting, we've heard this before, a lot of people are going that way, but there's no shortcuts. Can you talk about, cause you talk about the endpoint is then outside-in. >> Right, when you're operating as a demand-driven interim supply channel operating model, you can't run out of supply, right? So if you saw a change happening in the marketplace but there's nothing to supply, you've really just messed up the business. And so, each of these stages builds on every other stage. So functional excellence is: Am I good at planning? Am I good at product management? Am I good at logistics? Because those are the foundations for operating in the interim business model. This is why the Oracle's blanching in the cloud, in fact all of Oracle's developments in the cloud are so important because you're effectively building a new process oriented operating model that spins the entire business. If I started off with ERP systems and then I put logistics in place and tied it together, there's all sorts of disconnects in the business. When you pick it up in cycle times, you pick it in disconnect sometimes, they don't see changes to the marketplace for weeks. So, this overarching end to end supply chain operating model in the cloud is a fundamental enabler. >> So how do you gauge a customer? First of all, I buy everything that you said, but I want to bring up a point, because it seems to me that the theme of Oracle OpenWorld that traditional applications and I won't say, I'll just say the word Silo just to use it as a point, has been a specific domain specific thing. But to be end to end and be outside-in, which is the end game, you have to know how to talk and integrate with other systems which might have been a problem if you built the most badass end to end system. >> That is a part of the challenge and in fact, a lot of companies that I've worked with over the 15 years I've been researching this, they get stuck for that very reason. In other words, this is a re-engineering of the whole IT infrastructure versus having a thousand consultants come in and tie all my data together over a question of four years and move 15 instances of whatever system you want to one. >> So, if I question on the journey thing, you mentioned thousands of consultants, which customers are now seeing. They want faster mile posts, they want to see faster agility but a lot of the customers actually outline the journey for the customer. So they're saying, here's your journey and they shorten the mile posts for the deliverables. But they're the one getting paid for it so is that the right model, should they be outlining the journey for the customer? >> And they are. It's been very interesting because I was a partner with a major global consulting company for four years and I've been mixing with them here, they suddenly recognizing that this path to the cloud is something they've better get on the bandwagon because they're not going to have a thousand consultants deploying whatever ERP system you talk about as the future of IT. So, what's happening is the business is having much more of a say in this fast deployment, fast time to value, putting these new-- >> So they're driving the journey for parameters? >> They are gearing up for this new journey, the consultants are. >> So, let's get to the fundamentals behind all this and ask a question about it. At the end of the day, digital technologies give customers an option to do their journeys very differently whether in a B2B sense or a consumer sense. And as they use digital technologies, they're also giving data up and so we have now a combination where customers are getting something out of digital, they are demanding it as part of the engagement model. They are giving up data along the way, and the technologies for sensing and doing something with that data in business are now, we're not figuring out how that impacts business design, process design, and offering design. >> So, that's stage 4S, what we talk about is people, process, and technology versus, in the past, when you had stage one, two, and three. People as one set of projects, process as another set of projects, and technology as another set of projects. >> Yeah, I may or may not take some middlings with the model you put out, but it does matter. At the end of the day, what is driving this increasingly is that it used to be that the dominant consideration in, I think, and I'm testing you, the dominant consideration was assets. Where is the physical asset, where are the materials, where is the machine, and we'll focus our returns on this things and then presume that there's a demand for it and now we're getting all this data about demand and that is having an impact on how we talk about arranging the assets. >> That is the inside-out to outside-in. So, let me give you an example without mentioning companies. A major retailer and a major pharmaceutical company. They share pollen data, they share weather data, they mine Facebook to find out what are people saying about allergies, let's say in New England. And the ragweed's busting and they say, do we have the right levels of inventory, and they're moving inventory to make sure that people who aren't on Facebook are saying we can't buy this particular product. They're moving inventory, that's the difference. >> So, they're sharing data amongst themselves. >> Yes, and they're collaborating between retailers. >> Arguably a similar example, and a retailer that's actually not moving inventory but moving pointers and offering new channel options so that someone decides may not, that they know somebody's going to come into the store, the size may not be there but they can still get it to them that day. >> So, it's very interesting, Procter and Gamble, who I did a lot of work with, and this is public domain information, the CEO drove two fundamental transformation messages in the business. And they called it the two moments of truth. He said, we will always have our product when we say we've got a product. So, if we promote a new product, the consumer goes to the shelf, it will be there. Moment of truth number two, we understand why consumers choose and use our products. And you don't fix number two until you fix number one because if I wanted a small tube of toothpaste and I went in and there were only big ones, it's the wrong buying signal. So, what you're seeing is that whole flip to measuring what the market's looking for and shaping their demand and then making sure that the assets and the supply system is geared to deliver. >> Right, I want to ask you a question. First of all, I love that point, I love your point about the data, but here's the question: cause supply chain has been very instrumentation drive, okay, and that certainly is transforming but now you mention Procter and Gamble. We are living in an era where, in the history of business, you can actually now potentially measure everything. So how does that impacting the reconfiguration of the business model? I mean, Procter and Gamble has those moments of truth, every company will have a moment of truth which is, everything is now measurable so, advertising to employee things and everything. >> So let's take the asset story versus the on shelf thing, right, so when I have assets and I'm getting all the data out of my assets, what am I doing with all of that data, right? Because it's not connected to demand. What I got to know is what demand data do I really want to be able to move my assets to the right place. >> Peter: By the way, the shelf is an asset. >> Of course it is, yes. It's a sensing point and it's an asset. They own it, they replenish that shelf. So the point is, data is everywhere and now these, the consulting and the BPM organizations supporting and companies doing their own business process manner, they got to know what data is really important and what data from the outside-in is going to allow me to leverage a new operating model for my business and become digital. >> So, this is really awesome, I was talking with an Oracle executive last night at one of their customer parties and we had a conversation around this data sharing. This is a new, different behavior. This is a theme of the show that no one's really talking about but it's in plain sight which is there is a data sharing aspect of systems and vendors and companies. >> Roddy: That's why the cloud is so important. >> John: This is now impacting everything. >> Everything. >> How do companies go forward and do this? What are you seeing, is there a best practice, is there a starting point? Is there a five step process on that? >> Well, first of all, these transformations are being lead by the C level executive team in a business. This is now longer somebody who decides to buy a new IT system and plug it in to the business. So, the business is saying, how do we change the operating model of the way we work, right? So, and then, what are the capabilities, and this is where that five stage model comes in, what capabilities do we need to look at building over the next three years so that we can operate in this intent way because you can't wake up tomorrow and go from an inside-out asset driven business to an outside-in demand driven business in two weeks. It ain't going to happen. >> So what's the progression? What's the progress bar look like when you have that moment of an epiphany and say, you know, I'm the CEO-- >> What's the earning point of the business? If it's Procter and Gamble, I want X number of one billion dollars brands. If you're a pharmaceutical company, you want to launch brand new drugs and you want to do it at half the price and half the speed that you're used to. It's the business articulating, this is why the leadership teams are so fundamental, articulating what's the burning platform and then translating that back into the capabilities-- >> So you get a reverse engineer. >> Outside-In. >> Outside-In, I love it. >> The way our research says it, and it's very similar but I want to test this because it's, we say start with context. >> Yes. >> What are you going to do with your customer that you have to do better than everybody else? And then identify the community that you're going to do it with and identify the capabilities that are going to delight that community. So it's context, community, and capabilities. >> Now here's the context, further piece to context. If context changes, how quickly do I sense that change and how fast can I respond to that change? Because if I've got all my asset capabilities and my supply capabilities locked into one set of context and that changes and I now have to re-engineer my whole business, I may lose the whole show in the process. I got to see those changes as they are happening, literally in real time. This is where the internet of things, this is where demand shaping, demand sensing, retailers collaborating, supplies connected into supply chain, everybody sharing that information and the fact that not many people, they don't know how to do it. The culture of business is not yet at the points-- >> That's why the measurement thing I brought up, I mean Procter and Gamble, they used to say to their agencies, we know that 50% of our advertising is good, we don't know which half. So now they can measure it all just like in every other aspect so this is where the business model-- >> You also have to be careful about whether or not, again going back to context changes, measurements change, data can blow you away. You have to be very smart about how you do it so a lot of these intelligent things, machine learning, how the models get built, how the insides get delivered, all become very very important. Very quickly, I have two quick questions for you. One is really approximate to the conversation, one less so but the approximate one: IOT. IOT is, has many many applications. Certainly turning analogue data into digital data so you can build models is a crucial piece of it. But it also has another implication in how you enact the output of that model back into the real word. How does supply chain and IOT come together? >> So if you look at the studies that are being done by Oracle and Gartner et cetera on what's important to the supply chain, two things come up. One is visibility and the other is analytics. Right, so there's tons of data available, to your point just now. That data could cause massive noise to the business unless you know what you're looking at. I know companies that will say, 95% visibility of changes on their demand side is good enough but I'm good enough on the supply side to be able to adjust. But you got to know which data to look at. So I'm looking at on shelf. I'm looking at what consumers are choosing and using, I'm looking to see what of my contract manufacturers-- >> Peter: Analyze key constraints. >> Bingo, so it's not about, I think what we're all going to have to learn in the internet of things is we need, again, a cloud based internet of things platform that does the analytics. >> Because we can rewire things faster. >> Exactly, you can adjust the business to new scenarios based on what you're reading from the demand side and what you're reading from the supply side. >> So you're a great foil for my second question. My second question is you look back at the history, or the recent history let's call it, of strategy, very asset based, Porter said pick the industry that has the best returns, pick your position in that industry, then choose your games based on the five factor analysis that you want to play to get to that position. Very asset oriented, we're in control, that's going to dictate how things change. What you just suggested was a very very different way of thinking about strategy. >> Same fundamentals. It's the same fundamentals but it's allowing yourself to adjust those fundamentals based on what's happening in the market place. >> Peter: But you're not going to base it on just the assets. >> No, we're not going to base it on the assets unless you've focused on, like if you're an engineering company and that's all you make is machines, you can't suddenly start producing toothpaste, for example. There are, that's why I say it's a reconfiguration of those same principles but flexible enough to meet demand. >> So how does, how does the world of design and the world of strategy start to come together in C suite? >> Fundamentally, because it's the voice of the customer that starts to count. It's the voice of the customer that dictates the strategy. So if my customers don't want green Guinness for Saint Patrick's Day, don't make any, because it's going to hang around and get thrown away, right? So, the voice of the customer determines what's happening on the demand side and the supply side has to be agile enough to meet that need. >> So, I would suggest keep Guinness the way it is because it's damn good the way it is, so personally I would agree on the Guinness comment. No green Guinness. >> So, what's the South Africa beer? >> Castle Lager. Well, SAB, South African Brewery, has been bought by Anheuser-Busch InBrev, a massive big giant. >> We love beer and if there's any beer sponsors out there, we're happy looking for our Budweiser. We want a, maybe an IPA in there. Roddy, thanks for spending the time, coming in with you, appreciate it. Some thought leadership here on Reconfiguration and looking at some of the nuances that are really going to impact the buyers here on The Cube. Oracle Open will be back with more live coverage from SiliconANGLE's The Cube after this short break.

>> From theCUBE Studios in Palo Alto and Boston, bringing you data-driven insights from theCUBE and ETR. This is Breaking Analysis with Dave Vellante. >> Spark became a top level Apache project in 2014, and then shortly thereafter, burst onto the big data scene. Spark, along with the cloud, transformed and in many ways, disrupted the big data market. Databricks optimized its tech stack for Spark and took advantage of the cloud to really cleverly deliver a managed service that has become a leading AI and data platform among data scientists and data engineers. However, emerging customer data requirements are shifting into a direction that will cause modern data platform players generally and Databricks, specifically, we think, to make some key directional decisions and perhaps even reinvent themselves. Hello and welcome to this week's wikibon theCUBE Insights, powered by ETR. In this Breaking Analysis, we're going to do a deep dive into Databricks. We'll explore its current impressive market momentum. We're going to use some ETR survey data to show that, and then we'll lay out how customer data requirements are changing and what the ideal data platform will look like in the midterm future. We'll then evaluate core elements of the Databricks portfolio against that vision, and then we'll close with some strategic decisions that we think the company faces. And to do so, we welcome in our good friend, George Gilbert, former equities analyst, market analyst, and current Principal at TechAlpha Partners. George, good to see you. Thanks for coming on. >> Good to see you, Dave. >> All right, let me set this up. We're going to start by taking a look at where Databricks sits in the market in terms of how customers perceive the company and what it's momentum looks like. And this chart that we're showing here is data from ETS, the emerging technology survey of private companies. The N is 1,421. What we did is we cut the data on three sectors, analytics, database-data warehouse, and AI/ML. The vertical axis is a measure of customer sentiment, which evaluates an IT decision maker's awareness of the firm and the likelihood of engaging and/or purchase intent. The horizontal axis shows mindshare in the dataset, and we've highlighted Databricks, which has been a consistent high performer in this survey over the last several quarters. And as we, by the way, just as aside as we previously reported, OpenAI, which burst onto the scene this past quarter, leads all names, but Databricks is still prominent. You can see that the ETR shows some open source tools for reference, but as far as firms go, Databricks is very impressively positioned. Now, let's see how they stack up to some mainstream cohorts in the data space, against some bigger companies and sometimes public companies. This chart shows net score on the vertical axis, which is a measure of spending momentum and pervasiveness in the data set is on the horizontal axis. You can see that chart insert in the upper right, that informs how the dots are plotted, and net score against shared N. And that red dotted line at 40% indicates a highly elevated net score, anything above that we think is really, really impressive. And here we're just comparing Databricks with Snowflake, Cloudera, and Oracle. And that squiggly line leading to Databricks shows their path since 2021 by quarter. And you can see it's performing extremely well, maintaining an elevated net score and net range. Now it's comparable in the vertical axis to Snowflake, and it consistently is moving to the right and gaining share. Now, why did we choose to show Cloudera and Oracle? The reason is that Cloudera got the whole big data era started and was disrupted by Spark. And of course the cloud, Spark and Databricks and Oracle in many ways, was the target of early big data players like Cloudera. Take a listen to Cloudera CEO at the time, Mike Olson. This is back in 2010, first year of theCUBE, play the clip. >> Look, back in the day, if you had a data problem, if you needed to run business analytics, you wrote the biggest check you could to Sun Microsystems, and you bought a great big, single box, central server, and any money that was left over, you handed to Oracle for a database licenses and you installed that database on that box, and that was where you went for data. That was your temple of information. >> Okay? So Mike Olson implied that monolithic model was too expensive and inflexible, and Cloudera set out to fix that. But the best laid plans, as they say, George, what do you make of the data that we just shared? >> So where Databricks has really come up out of sort of Cloudera's tailpipe was they took big data processing, made it coherent, made it a managed service so it could run in the cloud. So it relieved customers of the operational burden. Where they're really strong and where their traditional meat and potatoes or bread and butter is the predictive and prescriptive analytics that building and training and serving machine learning models. They've tried to move into traditional business intelligence, the more traditional descriptive and diagnostic analytics, but they're less mature there. So what that means is, the reason you see Databricks and Snowflake kind of side by side is there are many, many accounts that have both Snowflake for business intelligence, Databricks for AI machine learning, where Snowflake, I'm sorry, where Databricks also did really well was in core data engineering, refining the data, the old ETL process, which kind of turned into ELT, where you loaded into the analytic repository in raw form and refine it. And so people have really used both, and each is trying to get into the other. >> Yeah, absolutely. We've reported on this quite a bit. Snowflake, kind of moving into the domain of Databricks and vice versa. And the last bit of ETR evidence that we want to share in terms of the company's momentum comes from ETR's Round Tables. They're run by Erik Bradley, and now former Gartner analyst and George, your colleague back at Gartner, Daren Brabham. And what we're going to show here is some direct quotes of IT pros in those Round Tables. There's a data science head and a CIO as well. Just make a few call outs here, we won't spend too much time on it, but starting at the top, like all of us, we can't talk about Databricks without mentioning Snowflake. Those two get us excited. Second comment zeros in on the flexibility and the robustness of Databricks from a data warehouse perspective. And then the last point is, despite competition from cloud players, Databricks has reinvented itself a couple of times over the year. And George, we're going to lay out today a scenario that perhaps calls for Databricks to do that once again. >> Their big opportunity and their big challenge for every tech company, it's managing a technology transition. The transition that we're talking about is something that's been bubbling up, but it's really epical. First time in 60 years, we're moving from an application-centric view of the world to a data-centric view, because decisions are becoming more important than automating processes. So let me let you sort of develop. >> Yeah, so let's talk about that here. We going to put up some bullets on precisely that point and the changing sort of customer environment. So you got IT stacks are shifting is George just said, from application centric silos to data centric stacks where the priority is shifting from automating processes to automating decision. You know how look at RPA and there's still a lot of automation going on, but from the focus of that application centricity and the data locked into those apps, that's changing. Data has historically been on the outskirts in silos, but organizations, you think of Amazon, think Uber, Airbnb, they're putting data at the core, and logic is increasingly being embedded in the data instead of the reverse. In other words, today, the data's locked inside the app, which is why you need to extract that data is sticking it to a data warehouse. The point, George, is we're putting forth this new vision for how data is going to be used. And you've used this Uber example to underscore the future state. Please explain? >> Okay, so this is hopefully an example everyone can relate to. The idea is first, you're automating things that are happening in the real world and decisions that make those things happen autonomously without humans in the loop all the time. So to use the Uber example on your phone, you call a car, you call a driver. Automatically, the Uber app then looks at what drivers are in the vicinity, what drivers are free, matches one, calculates an ETA to you, calculates a price, calculates an ETA to your destination, and then directs the driver once they're there. The point of this is that that cannot happen in an application-centric world very easily because all these little apps, the drivers, the riders, the routes, the fares, those call on data locked up in many different apps, but they have to sit on a layer that makes it all coherent. >> But George, so if Uber's doing this, doesn't this tech already exist? Isn't there a tech platform that does this already? >> Yes, and the mission of the entire tech industry is to build services that make it possible to compose and operate similar platforms and tools, but with the skills of mainstream developers in mainstream corporations, not the rocket scientists at Uber and Amazon. >> Okay, so we're talking about horizontally scaling across the industry, and actually giving a lot more organizations access to this technology. So by way of review, let's summarize the trend that's going on today in terms of the modern data stack that is propelling the likes of Databricks and Snowflake, which we just showed you in the ETR data and is really is a tailwind form. So the trend is toward this common repository for analytic data, that could be multiple virtual data warehouses inside of Snowflake, but you're in that Snowflake environment or Lakehouses from Databricks or multiple data lakes. And we've talked about what JP Morgan Chase is doing with the data mesh and gluing data lakes together, you've got various public clouds playing in this game, and then the data is annotated to have a common meaning. In other words, there's a semantic layer that enables applications to talk to the data elements and know that they have common and coherent meaning. So George, the good news is this approach is more effective than the legacy monolithic models that Mike Olson was talking about, so what's the problem with this in your view? >> So today's data platforms added immense value 'cause they connected the data that was previously locked up in these monolithic apps or on all these different microservices, and that supported traditional BI and AI/ML use cases. But now if we want to build apps like Uber or Amazon.com, where they've got essentially an autonomously running supply chain and e-commerce app where humans only care and feed it. But the thing is figuring out what to buy, when to buy, where to deploy it, when to ship it. We needed a semantic layer on top of the data. So that, as you were saying, the data that's coming from all those apps, the different apps that's integrated, not just connected, but it means the same. And the issue is whenever you add a new layer to a stack to support new applications, there are implications for the already existing layers, like can they support the new layer and its use cases? So for instance, if you add a semantic layer that embeds app logic with the data rather than vice versa, which we been talking about and that's been the case for 60 years, then the new data layer faces challenges that the way you manage that data, the way you analyze that data, is not supported by today's tools. >> Okay, so actually Alex, bring me up that last slide if you would, I mean, you're basically saying at the bottom here, today's repositories don't really do joins at scale. The future is you're talking about hundreds or thousands or millions of data connections, and today's systems, we're talking about, I don't know, 6, 8, 10 joins and that is the fundamental problem you're saying, is a new data error coming and existing systems won't be able to handle it? >> Yeah, one way of thinking about it is that even though we call them relational databases, when we actually want to do lots of joins or when we want to analyze data from lots of different tables, we created a whole new industry for analytic databases where you sort of mung the data together into fewer tables. So you didn't have to do as many joins because the joins are difficult and slow. And when you're going to arbitrarily join thousands, hundreds of thousands or across millions of elements, you need a new type of database. We have them, they're called graph databases, but to query them, you go back to the prerelational era in terms of their usability. >> Okay, so we're going to come back to that and talk about how you get around that problem. But let's first lay out what the ideal data platform of the future we think looks like. And again, we're going to come back to use this Uber example. In this graphic that George put together, awesome. We got three layers. The application layer is where the data products reside. The example here is drivers, rides, maps, routes, ETA, et cetera. The digital version of what we were talking about in the previous slide, people, places and things. The next layer is the data layer, that breaks down the silos and connects the data elements through semantics and everything is coherent. And then the bottom layers, the legacy operational systems feed that data layer. George, explain what's different here, the graph database element, you talk about the relational query capabilities, and why can't I just throw memory at solving this problem? >> Some of the graph databases do throw memory at the problem and maybe without naming names, some of them live entirely in memory. And what you're dealing with is a prerelational in-memory database system where you navigate between elements, and the issue with that is we've had SQL for 50 years, so we don't have to navigate, we can say what we want without how to get it. That's the core of the problem. >> Okay. So if I may, I just want to drill into this a little bit. So you're talking about the expressiveness of a graph. Alex, if you'd bring that back out, the fourth bullet, expressiveness of a graph database with the relational ease of query. Can you explain what you mean by that? >> Yeah, so graphs are great because when you can describe anything with a graph, that's why they're becoming so popular. Expressive means you can represent anything easily. They're conducive to, you might say, in a world where we now want like the metaverse, like with a 3D world, and I don't mean the Facebook metaverse, I mean like the business metaverse when we want to capture data about everything, but we want it in context, we want to build a set of digital twins that represent everything going on in the world. And Uber is a tiny example of that. Uber built a graph to represent all the drivers and riders and maps and routes. But what you need out of a database isn't just a way to store stuff and update stuff. You need to be able to ask questions of it, you need to be able to query it. And if you go back to prerelational days, you had to know how to find your way to the data. It's sort of like when you give directions to someone and they didn't have a GPS system and a mapping system, you had to give them turn by turn directions. Whereas when you have a GPS and a mapping system, which is like the relational thing, you just say where you want to go, and it spits out the turn by turn directions, which let's say, the car might follow or whoever you're directing would follow. But the point is, it's much easier in a relational database to say, "I just want to get these results. You figure out how to get it." The graph database, they have not taken over the world because in some ways, it's taking a 50 year leap backwards. >> Alright, got it. Okay. Let's take a look at how the current Databricks offerings map to that ideal state that we just laid out. So to do that, we put together this chart that looks at the key elements of the Databricks portfolio, the core capability, the weakness, and the threat that may loom. Start with the Delta Lake, that's the storage layer, which is great for files and tables. It's got true separation of compute and storage, I want you to double click on that George, as independent elements, but it's weaker for the type of low latency ingest that we see coming in the future. And some of the threats highlighted here. AWS could add transactional tables to S3, Iceberg adoption is picking up and could accelerate, that could disrupt Databricks. George, add some color here please? >> Okay, so this is the sort of a classic competitive forces where you want to look at, so what are customers demanding? What's competitive pressure? What are substitutes? Even what your suppliers might be pushing. Here, Delta Lake is at its core, a set of transactional tables that sit on an object store. So think of it in a database system, this is the storage engine. So since S3 has been getting stronger for 15 years, you could see a scenario where they add transactional tables. We have an open source alternative in Iceberg, which Snowflake and others support. But at the same time, Databricks has built an ecosystem out of tools, their own and others, that read and write to Delta tables, that's what makes the Delta Lake and ecosystem. So they have a catalog, the whole machine learning tool chain talks directly to the data here. That was their great advantage because in the past with Snowflake, you had to pull all the data out of the database before the machine learning tools could work with it, that was a major shortcoming. They fixed that. But the point here is that even before we get to the semantic layer, the core foundation is under threat. >> Yep. Got it. Okay. We got a lot of ground to cover. So we're going to take a look at the Spark Execution Engine next. Think of that as the refinery that runs really efficient batch processing. That's kind of what disrupted the DOOp in a large way, but it's not Python friendly and that's an issue because the data science and the data engineering crowd are moving in that direction, and/or they're using DBT. George, we had Tristan Handy on at Supercloud, really interesting discussion that you and I did. Explain why this is an issue for Databricks? >> So once the data lake was in place, what people did was they refined their data batch, and Spark has always had streaming support and it's gotten better. The underlying storage as we've talked about is an issue. But basically they took raw data, then they refined it into tables that were like customers and products and partners. And then they refined that again into what was like gold artifacts, which might be business intelligence metrics or dashboards, which were collections of metrics. But they were running it on the Spark Execution Engine, which it's a Java-based engine or it's running on a Java-based virtual machine, which means all the data scientists and the data engineers who want to work with Python are really working in sort of oil and water. Like if you get an error in Python, you can't tell whether the problems in Python or where it's in Spark. There's just an impedance mismatch between the two. And then at the same time, the whole world is now gravitating towards DBT because it's a very nice and simple way to compose these data processing pipelines, and people are using either SQL in DBT or Python in DBT, and that kind of is a substitute for doing it all in Spark. So it's under threat even before we get to that semantic layer, it so happens that DBT itself is becoming the authoring environment for the semantic layer with business intelligent metrics. But that's again, this is the second element that's under direct substitution and competitive threat. >> Okay, let's now move down to the third element, which is the Photon. Photon is Databricks' BI Lakehouse, which has integration with the Databricks tooling, which is very rich, it's newer. And it's also not well suited for high concurrency and low latency use cases, which we think are going to increasingly become the norm over time. George, the call out threat here is customers want to connect everything to a semantic layer. Explain your thinking here and why this is a potential threat to Databricks? >> Okay, so two issues here. What you were touching on, which is the high concurrency, low latency, when people are running like thousands of dashboards and data is streaming in, that's a problem because SQL data warehouse, the query engine, something like that matures over five to 10 years. It's one of these things, the joke that Andy Jassy makes just in general, he's really talking about Azure, but there's no compression algorithm for experience. The Snowflake guy started more than five years earlier, and for a bunch of reasons, that lead is not something that Databricks can shrink. They'll always be behind. So that's why Snowflake has transactional tables now and we can get into that in another show. But the key point is, so near term, it's struggling to keep up with the use cases that are core to business intelligence, which is highly concurrent, lots of users doing interactive query. But then when you get to a semantic layer, that's when you need to be able to query data that might have thousands or tens of thousands or hundreds of thousands of joins. And that's a SQL query engine, traditional SQL query engine is just not built for that. That's the core problem of traditional relational databases. >> Now this is a quick aside. We always talk about Snowflake and Databricks in sort of the same context. We're not necessarily saying that Snowflake is in a position to tackle all these problems. We'll deal with that separately. So we don't mean to imply that, but we're just sort of laying out some of the things that Snowflake or rather Databricks customers we think, need to be thinking about and having conversations with Databricks about and we hope to have them as well. We'll come back to that in terms of sort of strategic options. But finally, when come back to the table, we have Databricks' AI/ML Tool Chain, which has been an awesome capability for the data science crowd. It's comprehensive, it's a one-stop shop solution, but the kicker here is that it's optimized for supervised model building. And the concern is that foundational models like GPT could cannibalize the current Databricks tooling, but George, can't Databricks, like other software companies, integrate foundation model capabilities into its platform? >> Okay, so the sound bite answer to that is sure, IBM 3270 terminals could call out to a graphical user interface when they're running on the XT terminal, but they're not exactly good citizens in that world. The core issue is Databricks has this wonderful end-to-end tool chain for training, deploying, monitoring, running inference on supervised models. But the paradigm there is the customer builds and trains and deploys each model for each feature or application. In a world of foundation models which are pre-trained and unsupervised, the entire tool chain is different. So it's not like Databricks can junk everything they've done and start over with all their engineers. They have to keep maintaining what they've done in the old world, but they have to build something new that's optimized for the new world. It's a classic technology transition and their mentality appears to be, "Oh, we'll support the new stuff from our old stuff." Which is suboptimal, and as we'll talk about, their biggest patron and the company that put them on the map, Microsoft, really stopped working on their old stuff three years ago so that they could build a new tool chain optimized for this new world. >> Yeah, and so let's sort of close with what we think the options are and decisions that Databricks has for its future architecture. They're smart people. I mean we've had Ali Ghodsi on many times, super impressive. I think they've got to be keenly aware of the limitations, what's going on with foundation models. But at any rate, here in this chart, we lay out sort of three scenarios. One is re-architect the platform by incrementally adopting new technologies. And example might be to layer a graph query engine on top of its stack. They could license key technologies like graph database, they could get aggressive on M&A and buy-in, relational knowledge graphs, semantic technologies, vector database technologies. George, as David Floyer always says, "A lot of ways to skin a cat." We've seen companies like, even think about EMC maintained its relevance through M&A for many, many years. George, give us your thought on each of these strategic options? >> Okay, I find this question the most challenging 'cause remember, I used to be an equity research analyst. I worked for Frank Quattrone, we were one of the top tech shops in the banking industry, although this is 20 years ago. But the M&A team was the top team in the industry and everyone wanted them on their side. And I remember going to meetings with these CEOs, where Frank and the bankers would say, "You want us for your M&A work because we can do better." And they really could do better. But in software, it's not like with EMC in hardware because with hardware, it's easier to connect different boxes. With software, the whole point of a software company is to integrate and architect the components so they fit together and reinforce each other, and that makes M&A harder. You can do it, but it takes a long time to fit the pieces together. Let me give you examples. If they put a graph query engine, let's say something like TinkerPop, on top of, I don't even know if it's possible, but let's say they put it on top of Delta Lake, then you have this graph query engine talking to their storage layer, Delta Lake. But if you want to do analysis, you got to put the data in Photon, which is not really ideal for highly connected data. If you license a graph database, then most of your data is in the Delta Lake and how do you sync it with the graph database? If you do sync it, you've got data in two places, which kind of defeats the purpose of having a unified repository. I find this semantic layer option in number three actually more promising, because that's something that you can layer on top of the storage layer that you have already. You just have to figure out then how to have your query engines talk to that. What I'm trying to highlight is, it's easy as an analyst to say, "You can buy this company or license that technology." But the really hard work is making it all work together and that is where the challenge is. >> Yeah, and well look, I thank you for laying that out. We've seen it, certainly Microsoft and Oracle. I guess you might argue that well, Microsoft had a monopoly in its desktop software and was able to throw off cash for a decade plus while it's stock was going sideways. Oracle had won the database wars and had amazing margins and cash flow to be able to do that. Databricks isn't even gone public yet, but I want to close with some of the players to watch. Alex, if you'd bring that back up, number four here. AWS, we talked about some of their options with S3 and it's not just AWS, it's blob storage, object storage. Microsoft, as you sort of alluded to, was an early go-to market channel for Databricks. We didn't address that really. So maybe in the closing comments we can. Google obviously, Snowflake of course, we're going to dissect their options in future Breaking Analysis. Dbt labs, where do they fit? Bob Muglia's company, Relational.ai, why are these players to watch George, in your opinion? >> So everyone is trying to assemble and integrate the pieces that would make building data applications, data products easy. And the critical part isn't just assembling a bunch of pieces, which is traditionally what AWS did. It's a Unix ethos, which is we give you the tools, you put 'em together, 'cause you then have the maximum choice and maximum power. So what the hyperscalers are doing is they're taking their key value stores, in the case of ASW it's DynamoDB, in the case of Azure it's Cosmos DB, and each are putting a graph query engine on top of those. So they have a unified storage and graph database engine, like all the data would be collected in the key value store. Then you have a graph database, that's how they're going to be presenting a foundation for building these data apps. Dbt labs is putting a semantic layer on top of data lakes and data warehouses and as we'll talk about, I'm sure in the future, that makes it easier to swap out the underlying data platform or swap in new ones for specialized use cases. Snowflake, what they're doing, they're so strong in data management and with their transactional tables, what they're trying to do is take in the operational data that used to be in the province of many state stores like MongoDB and say, "If you manage that data with us, it'll be connected to your analytic data without having to send it through a pipeline." And that's hugely valuable. Relational.ai is the wildcard, 'cause what they're trying to do, it's almost like a holy grail where you're trying to take the expressiveness of connecting all your data in a graph but making it as easy to query as you've always had it in a SQL database or I should say, in a relational database. And if they do that, it's sort of like, it'll be as easy to program these data apps as a spreadsheet was compared to procedural languages, like BASIC or Pascal. That's the implications of Relational.ai. >> Yeah, and again, we talked before, why can't you just throw this all in memory? We're talking in that example of really getting down to differences in how you lay the data out on disk in really, new database architecture, correct? >> Yes. And that's why it's not clear that you could take a data lake or even a Snowflake and why you can't put a relational knowledge graph on those. You could potentially put a graph database, but it'll be compromised because to really do what Relational.ai has done, which is the ease of Relational on top of the power of graph, you actually need to change how you're storing your data on disk or even in memory. So you can't, in other words, it's not like, oh we can add graph support to Snowflake, 'cause if you did that, you'd have to change, or in your data lake, you'd have to change how the data is physically laid out. And then that would break all the tools that talk to that currently. >> What in your estimation, is the timeframe where this becomes critical for a Databricks and potentially Snowflake and others? I mentioned earlier midterm, are we talking three to five years here? Are we talking end of decade? What's your radar say? >> I think something surprising is going on that's going to sort of come up the tailpipe and take everyone by storm. All the hype around business intelligence metrics, which is what we used to put in our dashboards where bookings, billings, revenue, customer, those things, those were the key artifacts that used to live in definitions in your BI tools, and DBT has basically created a standard for defining those so they live in your data pipeline or they're defined in their data pipeline and executed in the data warehouse or data lake in a shared way, so that all tools can use them. This sounds like a digression, it's not. All this stuff about data mesh, data fabric, all that's going on is we need a semantic layer and the business intelligence metrics are defining common semantics for your data. And I think we're going to find by the end of this year, that metrics are how we annotate all our analytic data to start adding common semantics to it. And we're going to find this semantic layer, it's not three to five years off, it's going to be staring us in the face by the end of this year. >> Interesting. And of course SVB today was shut down. We're seeing serious tech headwinds, and oftentimes in these sort of downturns or flat turns, which feels like this could be going on for a while, we emerge with a lot of new players and a lot of new technology. George, we got to leave it there. Thank you to George Gilbert for excellent insights and input for today's episode. I want to thank Alex Myerson who's on production and manages the podcast, of course Ken Schiffman as well. Kristin Martin and Cheryl Knight help get the word out on social media and in our newsletters. And Rob Hof is our EIC over at Siliconangle.com, he does some great editing. Remember all these episodes, they're available as podcasts. Wherever you listen, all you got to do is search Breaking Analysis Podcast, we publish each week on wikibon.com and siliconangle.com, or you can email me at David.Vellante@siliconangle.com, or DM me @DVellante. Comment on our LinkedIn post, and please do check out ETR.ai, great survey data, enterprise tech focus, phenomenal. This is Dave Vellante for theCUBE Insights powered by ETR. Thanks for watching, and we'll see you next time on Breaking Analysis.

(bright upbeat music) >> Hello and welcome to theCUBE's coverage of International Women's Day. I'm your host, John Furrier here in Palo Alto, California Studio and remoting is a great guest CUBE alumni, co-founder, technical co-founder and she's also the VP of Product at Platform9 Systems. It's a company pioneering Kubernetes infrastructure, been doing it for a long, long time. Madhura Maskasky, thanks for coming on theCUBE. Appreciate you. Thanks for coming on. >> Thank you for having me. Always exciting. >> So I always... I love interviewing you for many reasons. One, you're super smart, but also you're a co-founder, a technical co-founder, so entrepreneur, VP of product. It's hard to do startups. (John laughs) Okay, so everyone who started a company knows how hard it is. It really is and the rewarding too when you're successful. So I want to get your thoughts on what's it like being an entrepreneur, women in tech, some things you've done along the way. Let's get started. How did you get into your career in tech and what made you want to start a company? >> Yeah, so , you know, I got into tech long, long before I decided to start a company. And back when I got in tech it was very clear to me as a direction for my career that I'm never going to start a business. I was very explicit about that because my father was an entrepreneur and I'd seen how rough the journey can be. And then my brother was also and is an entrepreneur. And I think with both of them I'd seen the ups and downs and I had decided to myself and shared with my family that I really want a very well-structured sort of job at a large company type of path for my career. I think the tech path, tech was interesting to me, not because I was interested in programming, et cetera at that time, to be honest. When I picked computer science as a major for myself, it was because most of what you would consider, I guess most of the cool students were picking that as a major, let's just say that. And it sounded very interesting and cool. A lot of people were doing it and that was sort of the top, top choice for people and I decided to follow along. But I did discover after I picked computer science as my major, I remember when I started learning C++ the first time when I got exposure to it, it was just like a light bulb clicking in my head. I just absolutely loved the language, the lower level nature, the power of it, and what you can do with it, the algorithms. So I think it ended up being a really good fit for me. >> Yeah, so it clicked for you. You tried it, it was all the cool kids were doing it. I mean, I can relate, I did the same thing. Next big thing is computer science, you got to be in there, got to be smart. And then you get hooked on it. >> Yeah, exactly. >> What was the next level? Did you find any blockers in your way? Obviously male dominated, it must have been a lot of... How many females were in your class? What was the ratio at that time? >> Yeah, so the ratio was was pretty, pretty, I would say bleak when it comes to women to men. I think computer science at that time was still probably better compared to some of the other majors like mechanical engineering where I remember I had one friend, she was the single girl in an entire class of about at least 120, 130 students or so. So ratio was better for us. I think there were maybe 20, 25 girls in our class. It was a large class and maybe the number of men were maybe three X or four X number of women. So relatively better. Yeah. >> How about the job when you got into the structured big company? How did that go? >> Yeah, so, you know, I think that was a pretty smooth path I would say after, you know, you graduated from undergrad to grad school and then when I got into Oracle first and VMware, I think both companies had the ratios were still, you know, pretty off. And I think they still are to a very large extent in this industry, but I think this industry in my experience does a fantastic job of, you know, bringing everybody and kind of embracing them and treating them at the same level. That was definitely my experience. And so that makes it very easy for self-confidence, for setting up a path for yourself to thrive. So that was it. >> Okay, so you got an undergraduate degree, okay, in computer science and a master's from Stanford in databases and distributed systems. >> That's right. >> So two degrees. Was that part of your pathway or you just decided, "I want to go right into school?" Did it go right after each other? How did that work out? >> Yeah, so when I went into school, undergrad there was no special major and I didn't quite know if I liked a particular subject or set of subjects or not. Even through grad school, first year it wasn't clear to me, but I think in second year I did start realizing that in general I was a fan of backend systems. I was never a front-end person. The backend distributed systems really were of interest to me because there's a lot of complex problems to solve, and especially databases and large scale distributed systems design in the context of database systems, you know, really started becoming a topic of interest for me. And I think luckily enough at Stanford there were just fantastic professors like Mendel Rosenblum who offered operating system class there, then started VMware and later on I was able to join the company and I took his class while at school and it was one of the most fantastic classes I've ever taken. So they really had and probably I think still do a fantastic curriculum when it comes to distributor systems. And I think that probably helped stoke that interest. >> How do you talk to the younger girls out there in elementary school and through? What's the advice as they start to get into computer science, which is changing and still evolving? There's backend, there's front-end, there's AI, there's data science, there's no code, low code, there's cloud. What's your advice when they say what's the playbook? >> Yeah, so I think two things I always say, and I share this with anybody who's looking to get into computer science or engineering for that matter, right? I think one is that it's, you know, it's important to not worry about what that end specialization's going to be, whether it's AI or databases or backend or front-end. It does naturally evolve and you lend yourself to a path where you will understand, you know, which systems, which aspect you like better. But it's very critical to start with getting the fundamentals well, right? Meaning all of the key coursework around algorithm, systems design, architecture, networking, operating system. I think it is just so crucial to understand those well, even though at times you make question is this ever going to be relevant and useful to me later on in my career? It really does end up helping in ways beyond, you know, you can describe. It makes you a much better engineer. So I think that is the most important aspect of, you know, I would think any engineering stream, but definitely true for computer science. Because there's also been a trend more recently, I think, which I'm not a big fan of, of sort of limited scoped learning, which is you decide early on that you're going to be, let's say a front-end engineer, which is fine, you know. Understanding that is great, but if you... I don't think is ideal to let that limit the scope of your learning when you are an undergrad phrase or grad school. Because later on it comes back to sort of bite you in terms of you not being able to completely understand how the systems work. >> It's a systems kind of thinking. You got to have that mindset of, especially now with cloud, you got distributed systems paradigm going to the edge. You got 5G, Mobile World Congress recently happened, you got now all kinds of IOT devices out there, IP of devices at the edge. Distributed computing is only getting more distributed. >> That's right. Yeah, that's exactly right. But the other thing is also happens... That happens in computer science is that the abstraction layers keep raising things up and up and up. Where even if you're operating at a language like Java, which you know, during some of my times of programming there was a period when it was popular, it already abstracts you so far away from the underlying system. So it can become very easier if you're doing, you know, Java script or UI programming that you really have no understanding of what's happening behind the scenes. And I think that can be pretty difficult. >> Yeah. It's easy to lean in and rely too heavily on the abstractions. I want to get your thoughts on blockers. In your career, have you had situations where it's like, "Oh, you're a woman, okay seat at the table, sit on the side." Or maybe people misunderstood your role. How did you deal with that? Did you have any of that? >> Yeah. So, you know, I think... So there's something really kind of personal to me, which I like to share a few times, which I think I believe in pretty strongly. And which is for me, sort of my personal growth began at a very early phase because my dad and he passed away in 2012, but throughout the time when I was growing up, I was his special little girl. And every little thing that I did could be a simple test. You know, not very meaningful but the genuine pride and pleasure that he felt out of me getting great scores in those tests sort of et cetera, and that I could see that in him, and then I wanted to please him. And through him, I think I build that confidence in myself that I am good at things and I can do good. And I think that just set the building blocks for me for the rest of my life, right? So, I believe very strongly that, you know, yes, there are occasions of unfair treatment and et cetera, but for the most part, it comes from within. And if you are able to be a confident person who is kind of leveled and understands and believes in your capabilities, then for the most part, the right things happen around you. So, I believe very strongly in that kind of grounding and in finding a source to get that for yourself. And I think that many women suffer from the biggest challenge, which is not having enough self-confidence. And I've even, you know, with everything that I said, I've myself felt that, experienced that a few times. And then there's a methodical way to get around it. There's processes to, you know, explain to yourself that that's actually not true. That's a fake feeling. So, you know, I think that is the most important aspect for women. >> I love that. Get the confidence. Find the source for the confidence. We've also been hearing about curiosity and building, you mentioned engineering earlier, love that term. Engineering something, like building something. Curiosity, engineering, confidence. This brings me to my next question for you. What do you think the key skills and qualities are needed to succeed in a technical role? And how do you develop to maintain those skills over time? >> Yeah, so I think that it is so critical that you love that technology that you are part of. It is just so important. I mean, I remember as an example, at one point with one of my buddies before we started Platform9, one of my buddies, he's also a fantastic computer scientists from VMware and he loves video games. And so he said, "Hey, why don't we try to, you know, hack up a video game and see if we can take it somewhere?" And so, it sounded cool to me. And then so we started doing things, but you know, something I realized very quickly is that I as a person, I absolutely hate video games. I've never liked them. I don't think that's ever going to change. And so I was miserable. You know, I was trying to understand what's going on, how to build these systems, but I was not enjoying it. So, I'm glad that I decided to not pursue that. So it is just so important that you enjoy whatever aspect of technology that you decide to associate yourself with. I think that takes away 80, 90% of the work. And then I think it's important to inculcate a level of discipline that you are not going to get sort of... You're not going to get jaded or, you know, continue with happy path when doing the same things over and over again, but you're not necessarily challenging yourself, or pushing yourself, or putting yourself in uncomfortable situation. I think a combination of those typically I think works pretty well in any technical career. >> That's a great advice there. I think trying things when you're younger, or even just for play to understand whether you abandon that path is just as important as finding a good path because at least you know that skews the value in favor of the choices. Kind of like math probability. So, great call out there. So I have to ask you the next question, which is, how do you keep up to date given all the changes? You're in the middle of a world where you've seen personal change in the past 10 years from OpenStack to now. Remember those days when I first interviewed you at OpenStack, I think it was 2012 or something like that. Maybe 10 years ago. So much changed. How do you keep up with technologies in your field and resources that you rely on for personal development? >> Yeah, so I think when it comes to, you know, the field and what we are doing for example, I think one of the most important aspect and you know I am product manager and this is something I insist that all the other product managers in our team also do, is that you have to spend 50% of your time talking to prospects, customers, leads, and through those conversations they do a huge favor to you in that they make you aware of the other things that they're keeping an eye on as long as you're doing the right job of asking the right questions and not just, you know, listening in. So I think that to me ends up being one of the biggest sources where you get tidbits of information, new things, et cetera, and then you pursue. To me, that has worked to be a very effective source. And then the second is, you know, reading and keeping up with all of the publications. You guys, you know, create a lot of great material, you interview a lot of people, making sure you are watching those for us you know, and see there's a ton of activities, new projects keeps coming along every few months. So keeping up with that, listening to podcasts around those topics, all of that helps. But I think the first one I think goes in a big way in terms of being aware of what matters to your customers. >> Awesome. Let me ask you a question. What's the most rewarding aspect of your job right now? >> So, I think there are many. So I think I love... I've come to realize that I love, you know, the high that you get out of being an entrepreneur independent of, you know, there's... In terms of success and failure, there's always ups and downs as an entrepreneur, right? But there is this... There's something really alluring about being able to, you know, define, you know, path of your products and in a way that can potentially impact, you know, a number of companies that'll consume your products, employees that work with you. So that is, I think to me, always been the most satisfying path, is what kept me going. I think that is probably first and foremost. And then the projects. You know, there's always new exciting things that we are working on. Even just today, there are certain projects we are working on that I'm super excited about. So I think it's those two things. >> So now we didn't get into how you started. You said you didn't want to do a startup and you got the big company. Your dad, your brother were entrepreneurs. How did you get into it? >> Yeah, so, you know, it was kind of surprising to me as well, but I think I reached a point of VMware after spending about eight years or so where I definitely packed hold and I could have pushed myself by switching to a completely different company or a different organization within VMware. And I was trying all of those paths, interviewed at different companies, et cetera, but nothing felt different enough. And then I think I was very, very fortunate in that my co-founders, Sirish Raghuram, Roopak Parikh, you know, Bich, you've met them, they were kind of all at the same journey in their careers independently at the same time. And so we would all eat lunch together at VMware 'cause we were on the same team and then we just started brainstorming on different ideas during lunchtime. And that's kind of how... And we did that almost for a year. So by the time that the year long period went by, at the end it felt like the most logical, natural next step to leave our job and to, you know, to start off something together. But I think I wouldn't have done that had it not been for my co-founders. >> So you had comfort with the team as you knew each other at VMware, but you were kind of a little early, (laughing) you had a vision. It's kind of playing out now. How do you feel right now as the wave is hitting? Distributed computing, microservices, Kubernetes, I mean, stuff you guys did and were doing. I mean, it didn't play out exactly, but directionally you were right on the line there. How do you feel? >> Yeah. You know, I think that's kind of the challenge and the fun part with the startup journey, right? Which is you can never predict how things are going to go. When we kicked off we thought that OpenStack is going to really take over infrastructure management space and things kind of went differently, but things are going that way now with Kubernetes and distributed infrastructure. And so I think it's been interesting and in every path that you take that does end up not being successful teaches you so much more, right? So I think it's been a very interesting journey. >> Yeah, and I think the cloud, certainly AWS hit that growth right at 2013 through '17, kind of sucked all the oxygen out. But now as it reverts back to this abstraction layer essentially makes things look like private clouds, but they're just essentially DevOps. It's cloud operations, kind of the same thing. >> Yeah, absolutely. And then with the edge things are becoming way more distributed where having a single large cloud provider is becoming even less relevant in that space and having kind of the central SaaS based management model, which is what we pioneered, like you said, we were ahead of the game at that time, is becoming sort of the most obvious choice now. >> Now you look back at your role at Stanford, distributed systems, again, they have world class program there, neural networks, you name it. It's really, really awesome. As well as Cal Berkeley, there was in debates with each other, who's better? But that's a separate interview. Now you got the edge, what are some of the distributed computing challenges right now with now the distributed edge coming online, industrial 5G, data? What do you see as some of the key areas to solve from a problem statement standpoint with edge and as cloud goes on-premises to essentially data center at the edge, apps coming over the top AI enabled. What's your take on that? >> Yeah, so I think... And there's different flavors of edge and the one that we focus on is, you know, what we call thick edge, which is you have this problem of managing thousands of as we call it micro data centers, rather than managing maybe few tens or hundreds of large data centers where the problem just completely shifts on its head, right? And I think it is still an unsolved problem today where whether you are a retailer or a telecommunications vendor, et cetera, managing your footprints of tens of thousands of stores as a retailer is solved in a very archaic way today because the tool set, the traditional management tooling that's designed to manage, let's say your data centers is not quite, you know, it gets retrofitted to manage these environments and it's kind of (indistinct), you know, round hole kind of situation. So I think the top most challenges are being able to manage this large footprint of micro data centers in the most effective way, right? Where you have latency solved, you have the issue of a small footprint of resources at thousands of locations, and how do you fit in your containerized or virtualized or other workloads in the most effective way? To have that solved, you know, you need to have the security aspects around these environments. So there's a number of challenges that kind of go hand-in-hand, like what is the most effective storage which, you know, can still be deployed in that compact environment? And then cost becomes a related point. >> Costs are huge 'cause if you move data, you're going to have cost. If you move compute, it's not as much. If you have an operating system concept, is the data and state or stateless? These are huge problems. This is an operating system, don't you think? >> Yeah, yeah, absolutely. It's a distributed operating system where it's multiple layers, you know, of ways of solving that problem just in the context of data like you said having an intermediate caching layer so that you know, you still do just in time processing at those edge locations and then send some data back and that's where you can incorporate some AI or other technologies, et cetera. So, you know, just data itself is a multi-layer problem there. >> Well, it's great to have you on this program. Advice final question for you, for the folks watching technical degrees, most people are finding out in elementary school, in middle school, a lot more robotics programs, a lot more tech exposure, you know, not just in Silicon Valley, but all around, you're starting to see that. What's your advice for young girls and people who are getting either coming into the workforce re-skilled as they get enter, it's easy to enter now as they stay in and how do they stay in? What's your advice? >> Yeah, so, you know, I think it's the same goal. I have two little daughters and it's the same principle I try to follow with them, which is I want to give them as much exposure as possible without me having any predefined ideas about what you know, they should pursue. But it's I think that exposure that you need to find for yourself one way or the other, because you really never know. Like, you know, my husband landed into computer science through a very, very meandering path, and then he discovered later in his career that it's the absolute calling for him. It's something he's very good at, right? But so... You know, it's... You know, the reason why he thinks he didn't pick that path early is because he didn't quite have that exposure. So it's that exposure to various things, even things you think that you may not be interested in is the most important aspect. And then things just naturally lend themselves. >> Find your calling, superpower, strengths. Know what you don't want to do. (John chuckles) >> Yeah, exactly. >> Great advice. Thank you so much for coming on and contributing to our program for International Women's Day. Great to see you in this context. We'll see you on theCUBE. We'll talk more about Platform9 when we go KubeCon or some other time. But thank you for sharing your personal perspective and experiences for our audience. Thank you. >> Fantastic. Thanks for having me, John. Always great. >> This is theCUBE's coverage of International Women's Day, I'm John Furrier. We're talking to the leaders in the industry, from developers to the boardroom and everything in between and getting the stories out there making an impact. Thanks for watching. (bright upbeat music)

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

>> Narrator: TheCUBE's live coverage is made possible by funding from Dell Technologies, creating technologies that drive human progress. (upbeat music intro) (logo background tingles) >> Hi everybody, welcome back to day three of MWC23, my name is Dave Vellante and we're here live at the Theater of Barcelona, Lisa Martin, David Nicholson, John Furrier's in our studio in Palo Alto. Lot of buzz at the show, the Mobile World Daily Today, front page, Netflix chief hits back in fair share row, Greg Peters, the co-CEO of Netflix, talking about how, "Hey, you guys want to tax us, the telcos want to tax us, well, maybe you should help us pay for some of the content. Your margins are higher, you have a monopoly, you know, we're delivering all this value, you're bundling Netflix in, from a lot of ISPs so hold on, you know, pump the brakes on that tax," so that's the big news. Lockheed Martin, FOSS issues, AI guidelines, says, "AI's not going to take over your job anytime soon." Although I would say, your job's going to be AI-powered for the next five years. We're going to talk about data, we've been talking about the disaggregation of the telco stack, part of that stack is a data layer. John Kreisa is here, the CMO of Couchbase, John, you know, we've talked about all week, the disaggregation of the telco stacks, they got, you know, Silicon and operating systems that are, you know, real time OS, highly reliable, you know, compute infrastructure all the way up through a telemetry stack, et cetera. And that's a proprietary block that's really exploding, it's like the big bang, like we saw in the enterprise 20 years ago and we haven't had much discussion about that data layer, sort of that horizontal data layer, that's the market you play in. You know, Couchbase obviously has a lot of telco customers- >> John: That's right. >> We've seen, you know, Snowflake and others launch telco businesses. What are you seeing when you talk to customers at the show? What are they doing with that data layer? >> Yeah, so they're building applications to drive and power unique experiences for their users, but of course, it all starts with where the data is. So they're building mobile applications where they're stretching it out to the edge and you have to move the data to the edge, you have to have that capability to deliver that highly interactive experience to their customers or for their own internal use cases out to that edge, so seeing a lot of that with Couchbase and with our customers in telco. >> So what do the telcos want to do with data? I mean, they've got the telemetry data- >> John: Yeah. >> Now they frequently complain about the over-the-top providers that have used that data, again like Netflix, to identify customer demand for content and they're mopping that up in a big way, you know, certainly Amazon and shopping Google and ads, you know, they're all using that network. But what do the telcos do today and what do they want to do in the future? They're all talking about monetization, how do they monetize that data? >> Yeah, well, by taking that data, there's insight to be had, right? So by usage patterns and what's happening, just as you said, so they can deliver a better experience. It's all about getting that edge, if you will, on their competition and so taking that data, using it in a smart way, gives them that edge to deliver a better service and then grow their business. >> We're seeing a lot of action at the edge and, you know, the edge can be a Home Depot or a Lowe's store, but it also could be the far edge, could be a, you know, an oil drilling, an oil rig, it could be a racetrack, you know, certainly hospitals and certain, you know, situations. So let's think about that edge, where there's maybe not a lot of connectivity, there might be private networks going in, in the future- >> John: That's right. >> Private 5G networks. What's the data flow look like there? Do you guys have any customers doing those types of use cases? >> Yeah, absolutely. >> And what are they doing with the data? >> Yeah, absolutely, we've got customers all across, so telco and transportation, all kinds of service delivery and healthcare, for example, we've got customers who are delivering healthcare out at the edge where they have a remote location, they're able to deliver healthcare, but as you said, there's not always connectivity, so they need to have the applications, need to continue to run and then sync back once they have that connectivity. So it's really having the ability to deliver a service, reliably and then know that that will be synced back to some central server when they have connectivity- >> So the processing might occur where the data- >> Compute at the edge. >> How do you sync back? What is that technology? >> Yeah, so there's, so within, so Couchbase and Couchbase's case, we have an autonomous sync capability that brings it back to the cloud once they get back to whether it's a private network that they want to run over, or if they're doing it over a public, you know, wifi network, once it determines that there's connectivity and, it can be peer-to-peer sync, so different edge apps communicating with each other and then ultimately communicating back to a central server. >> I mean, the other theme here, of course, I call it the software-defined telco, right? But you got to have, you got to run on something, got to have hardware. So you see companies like AWS putting Outposts, out to the edge, Outposts, you know, doesn't really run a lot of database to mind, I mean, it runs RDS, you know, maybe they're going to eventually work with companies like... I mean, you're a partner of AWS- >> John: We are. >> Right? So do you see that kind of cloud infrastructure that's moving to the edge? Do you see that as an opportunity for companies like Couchbase? >> Yeah, we do. We see customers wanting to push more and more of that compute out to the edge and so partnering with AWS gives us that opportunity and we are certified on Outpost and- >> Oh, you are? >> We are, yeah. >> Okay. >> Absolutely. >> When did that, go down? >> That was last year, but probably early last year- >> So I can run Couchbase at the edge, on Outpost? >> Yeah, that's right. >> I mean, you know, Outpost adoption has been slow, we've reported on that, but are you seeing any traction there? Are you seeing any nibbles? >> Starting to see some interest, yeah, absolutely. And again, it has to be for the right use case, but again, for service delivery, things like healthcare and in transportation, you know, they're starting to see where they want to have that compute, be very close to where the actions happen. >> And you can run on, in the data center, right? >> That's right. >> You can run in the cloud, you know, you see HPE with GreenLake, you see Dell with Apex, that's essentially their Outposts. >> Yeah. >> They're saying, "Hey, we're going to take our whole infrastructure and make it as a service." >> Yeah, yeah. >> Right? And so you can participate in those environments- >> We do. >> And then so you've got now, you know, we call it supercloud, you've got the on-prem, you've got the, you can run in the public cloud, you can run at the edge and you want that consistent experience- >> That's right. >> You know, from a data layer- >> That's right. >> So is that really the strategy for a data company is taking or should be taking, that horizontal layer across all those use cases? >> You do need to think holistically about it, because you need to be able to deliver as a, you know, as a provider, wherever the customer wants to be able to consume that application. So you do have to think about any of the public clouds or private networks and all the way to the edge. >> What's different John, about the telco business versus the traditional enterprise? >> Well, I mean, there's scale, I mean, one thing they're dealing with, particularly for end user-facing apps, you're dealing at a very very high scale and the expectation that you're going to deliver a very interactive experience. So I'd say one thing in particular that we are focusing on, is making sure we deliver that highly interactive experience but it's the scale of the number of users and customers that they have, and the expectation that your application's always going to work. >> Speaking of applications, I mean, it seems like that's where the innovation is going to come from. We saw yesterday, GSMA announced, I think eight APIs telco APIs, you know, we were talking on theCUBE, one of the analysts was like, "Eight, that's nothing," you know, "What do these guys know about developers?" But you know, as Daniel Royston said, "Eight's better than zero." >> Right? >> So okay, so we're starting there, but the point being, it's all about the apps, that's where the innovation's going to come from- >> That's right. >> So what are you seeing there, in terms of building on top of the data app? >> Right, well you have to provide, I mean, have to provide the APIs and the access because it is really, the rubber meets the road, with the developers and giving them the ability to create those really rich applications where they want and create the experiences and innovate and change the way that they're giving those experiences. >> Yeah, so what's your relationship with developers at Couchbase? >> John: Yeah. >> I mean, talk about that a little bit- >> Yeah, yeah, so we have a great relationship with developers, something we've been investing more and more in, in terms of things like developer relations teams and community, Couchbase started in open source, continue to be based on open source projects and of course, those are very developer centric. So we provide all the consistent APIs for developers to create those applications, whether it's something on Couchbase Lite, which is our kind of edge-based database, or how they can sync that data back and we actually automate a lot of that syncing which is a very difficult developer task which lends them to one of the developer- >> What I'm trying to figure out is, what's the telco developer look like? Is that a developer that comes from the enterprise and somebody comes from the blockchain world, or AI or, you know, there really doesn't seem to be a lot of developer talk here, but there's a huge opportunity. >> Yeah, yeah. >> And, you know, I feel like, the telcos kind of remind me of, you know, a traditional legacy company trying to get into the developer world, you know, even Oracle, okay, they bought Sun, they got Java, so I guess they have developers, but you know, IBM for years tried with Bluemix, they had to end up buying Red Hat, really, and that gave them the developer community. >> Yep. >> EMC used to have a thing called EMC Code, which was a, you know, good effort, but eh. And then, you know, VMware always trying to do that, but, so as you move up the stack obviously, you have greater developer affinity. Where do you think the telco developer's going to come from? How's that going to evolve? >> Yeah, it's interesting, and I think they're... To kind of get to your first question, I think they're fairly traditional enterprise developers and when we break that down, we look at it in terms of what the developer persona is, are they a front-end developer? Like they're writing that front-end app, they don't care so much about the infrastructure behind or are they a full stack developer and they're really involved in the entire application development lifecycle? Or are they living at the backend and they're really wanting to just focus in on that data layer? So we lend towards all of those different personas and we think about them in terms of the APIs that we create, so that's really what the developers are for telcos is, there's a combination of those front-end and full stack developers and so for them to continue to innovate they need to appeal to those developers and that's technology, like Couchbase, is what helps them do that. >> Yeah and you think about the Apples, you know, the app store model or Apple sort of says, "Okay, here's a developer kit, go create." >> John: Yeah. >> "And then if it's successful, you're going to be successful and we're going to take a vig," okay, good model. >> John: Yeah. >> I think I'm hearing, and maybe I misunderstood this, but I think it was the CEO or chairman of Ericsson on the day one keynotes, was saying, "We are going to monetize the, essentially the telemetry data, you know, through APIs, we're going to charge for that," you know, maybe that's not the best approach, I don't know, I think there's got to be some innovation on top. >> John: Yeah. >> Now maybe some of these greenfield telcos are going to do like, you take like a dish networks, what they're doing, they're really trying to drive development layers. So I think it's like this wild west open, you know, community that's got to be formed and right now it's very unclear to me, do you have any insights there? >> I think it is more, like you said, Wild West, I think there's no emerging standard per se for across those different company types and sort of different pieces of the industry. So consequently, it does need to form some more standards in order to really help it grow and I think you're right, you have to have the right APIs and the right access in order to properly monetize, you have to attract those developers or you're not going to be able to monetize properly. >> Do you think that if, in thinking about your business and you know, you've always sold to telcos, but now it's like there's this transformation going on in telcos, will that become an increasingly larger piece of your business or maybe even a more important piece of your business? Or it's kind of be steady state because it's such a slow moving industry? >> No, it is a big and increasing piece of our business, I think telcos like other enterprises, want to continue to innovate and so they look to, you know, technologies like, Couchbase document database that allows them to have more flexibility and deliver the speed that they need to deliver those kinds of applications. So we see a lot of migration off of traditional legacy infrastructure in order to build that new age interface and new age experience that they want to deliver. >> A lot of buzz in Silicon Valley about open AI and Chat GPT- >> Yeah. >> You know, what's your take on all that? >> Yeah, we're looking at it, I think it's exciting technology, I think there's a lot of applications that are kind of, a little, sort of innovate traditional interfaces, so for example, you can train Chat GPT to create code, sample code for Couchbase, right? You can go and get it to give you that sample app which gets you a headstart or you can actually get it to do a better job of, you know, sorting through your documentation, like Chat GPT can do a better job of helping you get access. So it improves the experience overall for developers, so we're excited about, you know, what the prospect of that is. >> So you're playing around with it, like everybody is- >> Yeah. >> And potentially- >> Looking at use cases- >> Ways tO integrate, yeah. >> Hundred percent. >> So are we. John, thanks for coming on theCUBE. Always great to see you, my friend. >> Great, thanks very much. >> All right, you're welcome. All right, keep it right there, theCUBE will be back live from Barcelona at the theater. SiliconANGLE's continuous coverage of MWC23. Go to siliconangle.com for all the news, theCUBE.net is where all the videos are, keep it right there. (cheerful upbeat music outro)

>> Announcer: theCUBE's live coverage is made possible by funding from Dell Technologies. Creating technologies that drive human progress. (upbeat music) >> Hi everybody. Welcome back to Barcelona. We're here at the Fira Live, theCUBE's ongoing coverage of day two of MWC 23. Back in 2021 was my first Mobile World Congress. And you know what? It was actually quite an experience because there was nobody there. I talked to my friend, who's now my co-host, Chris Lewis about what to expect. He said, Dave, I don't think a lot of people are going to be there, but Danielle Royston is here and she's the CEO of Totoge. And that year when Erickson tapped out of its space she took out 60,000 square feet and built out Cloud City. If it weren't for Cloud City, there would've been no Mobile World Congress in June and July of 2021. DR is back. Great to see you. Thanks for coming on. >> It's great to see you. >> Chris. Awesome to see you. >> Yeah, Chris. Yep. >> Good to be back. Yep. >> You guys remember the narrative back then. There was this lady running around this crazy lady that I met at at Google Cloud next saying >> Yeah. Yeah. >> the cloud's going to take over Telco. And everybody's like, well, this lady's nuts. The cloud's been leaning in, you know? >> Yeah. >> So what do you think, I mean, what's changed since since you first caused all those ripples? >> I mean, I have to say that I think that I caused a lot of change in the industry. I was talking to leaders over at AWS yesterday and they were like, we've never seen someone push like you have and change so much in a short period of time. And Telco moves slow. It's known for that. And they're like, you are pushing buttons and you're getting people to change and thank you and keep going. And so it's been great. It's awesome. >> Yeah. I mean, it was interesting, Chris, we heard on the keynotes we had Microsoft, Satya came in, Thomas Curian came in. There was no AWS. And now I asked CMO of GSMA about that. She goes, hey, we got a great relationship with it, AWS. >> Danielle: Yeah. >> But why do you think they weren't here? >> Well, they, I mean, they are here. >> Mean, not here. Why do you think they weren't profiled? >> They weren't on the keynote stage. >> But, you know, at AWS, a lot of the times they want to be the main thing. They want to be the main part of the show. They don't like sharing the limelight. I think they just didn't want be on the stage with the Google CLoud guys and the these other guys, what they're doing they're building out, they're doing so much stuff. As Danielle said, with Telcos change in the ecosystem which is what's happening with cloud. Cloud's making the Telcos think about what the next move is, how they fit in with the way other people do business. Right? So Telcos never used to have to listen to anybody. They only listened to themselves and they dictated the way things were done. They're very successful and made a lot of money but they're now having to open up they're having to leverage the cloud they're having to leverage the services that (indistinct words) and people out provide and they're changing the way they work. >> So, okay in 2021, we talked a lot about the cloud as a potential disruptor, and your whole premise was, look you got to lean into the cloud, or you're screwed. >> Danielle: Yeah. >> But the flip side of that is, if they lean into the cloud too much, they might be screwed. >> Danielle: Yeah. >> So what's that equilibrium? Have they been able to find it? Are you working with just the disruptors or how's that? >> No I think they're finding it right. So my talk at MWC 21 was all about the cloud is a double-edged sword, right? There's two sides to it, and you definitely need to proceed through it with caution, but also I don't know that you have a choice, right? I mean, the multicloud, you know is there another industry that spends more on CapEx than Telco? >> No. >> Right. The hyperscalers are doing it right. They spend, you know, easily approaching over a $100 billion in CapEx that rivals this industry. And so when you have a player like that an industry driving, you know and investing so much Telco, you're always complaining how everyone's riding your coattails. This is the opportunity to write someone else's coattails. So jump on, right? I think you don't have a choice especially if other Telco competitors are using hyperscalers and you don't, they're going to be left behind. >> So you advise these companies all the time, but >> I mean, the issue is they're all they're all using all the hyperscalers, right? So they're the multi, the multiple relationships. And as Danielle said, the multi-layer of relationship they're using the hyperscalers to change their own internal operational environments to become more IT-centric to move to that software centric Telco. And they're also then with the hyperscalers going to market in different ways sometimes with them, sometimes competing with them. What what it means from an analyst point of view is you're suddenly changing the dynamic of a market where we used to have nicely well defined markets previously. Now they're, everyone's in it together, you know, it's great. And, and it's making people change the way they think about services. What I, what I really hope it changes more than anything else is the way the customers at the end of the, at the end of the supply, the value chain think this is what we can get hold of this stuff. Now we can go into the network through the cloud and we can get those APIs. We can draw on the mechanisms we need to to run our personal lives, to run our business lives. And frankly, society as a whole. It's really exciting. >> Then your premise is basically you were saying they should ride on the top over the top of the cloud vendor. >> Yeah. Right? >> No. Okay. But don't they lose the, all the data if they do that? >> I don't know. I mean, I think the hyperscalers are not going to take their data, right? I mean, that would be a really really bad business move if Google Cloud and Azure and and AWS start to take over that, that data. >> But they can't take it. >> They can't. >> From regulate, from sovereignty and regulation. >> They can't because of regulation, but also just like business, right? If they started taking their data and like no enterprises would use them. So I think, I think the data is safe. I think you, obviously every country is different. You got to understand the different rules and regulations for data privacy and, and how you keep it. But I think as we look at the long term, right and we always talk about 10 and 20 years there's going to be a hyperscaler region in every country right? And there will be a way for every Telco to use it. I think their data will be safe. And I think it just, you're going to be able to stand on on the shoulders of someone else for once and use the building blocks of software that these guys provide to make better experiences for subscribers. >> You guys got to explain this to me because when I say data I'm not talking about, you know, personal information. I'm talking about all the telemetry, you know, all the all the, you know the plumbing. >> Danielle: Yeah. >> Data, which is- >> It will increasingly be shared because you need to share it in order to deliver the services in the streamline efficient way that needs to be deliver. >> Did I hear the CEO of Ericsson Wright where basically he said, we're going to charge developers for access to that data through APIs. >> What the Ericsson have done, obviously with the Vage acquisition is they want to get into APIs. So the idea is you're exposing features, quality policy on demand type features for example, or even pulling we still use that a lot of SMS, right? So pulling those out using those APIs. So it will be charged in some way. Whether- >> Man: Like Twitter's charging me for APIs, now I API calls, you >> Know what it is? I think it's Twilio. >> Man: Oh, okay. >> Right. >> Man: No, no, that's sure. >> There's no reason why telcos couldn't provide a Twilio like service itself. >> It's a horizontal play though right? >> Danielle: Correct because developers need to be charged by the API. >> But doesn't there need to be an industry standard to do that as- >> Well. I think that's what they just announced. >> Industry standard. >> Danielle: I think they just announced that. Yeah. Right now I haven't looked at that API set, right? >> There's like eight of them. >> There's eight of them. Twilio has, it's a start you got to start somewhere Dave. (crosstalk) >> And there's all, the TM forum is all the other standard >> Right? Eight is better than zero- >> Right? >> Haven't got plenty. >> I mean for an industry that didn't really understand APIs as a feature, as a product as a service, right? For Mats Granryd, the deputy general of GSMA to stand on the keynote stage and say we partnered and we're unveiling, right. Pay by the use APIs. I was for it. I was like, that is insane. >> I liked his keynote actually, because I thought he was going to talk about how many attendees and how much economic benefiting >> Danielle: We're super diverse. >> He said, I would usually talk about that and you know greening in the network by what you did talk about a little bit. But, but that's, that surprised me. >> Yeah. >> But I've seen in the enterprise this is not my space as, you know, you guys don't live this but I've seen Oracle try to get developers. IBM had to pay $35 billion trying to get for Red Hat to get developers, right? EMC used to have a thing called EMC code, failed. >> I mean they got to do something, right? So 4G they didn't really make the business case the ROI on the investment in the network. Here we are with 5G, same discussion is having where's the use case? How are we going to monetize and make the ROI on this massive investment? And now they're starting to talk about 6G. Same fricking problem is going to happen again. And so I think they need to start experimenting with new ideas. I don't know if it's going to work. I don't know if this new a API network gateway theme that Mats talked about yesterday will work. But they need to start unbundling that unlimited plan. They need to start charging people who are using the network more, more money. Those who are using it less, less. They need to figure this out. This is a crisis for them. >> Yeah our own CEO, I mean she basically said, Hey, I'm for net neutrality, but I want to be able to charge the people that are using it more and more >> To make a return on, on a capital. >> I mean it costs billions of dollars to build these networks, right? And they're valuable. We use them and we talked about this in Cloud City 21, right? The ability to start building better metaverses. And I know that's a buzzword and everyone hates it, but it's true. Like we're working from home. We need- there's got to be a better experience in Zoom in 2D, right? And you need a great network for that metaverse to be awesome. >> You do. But Danielle, you don't need cellular for doing that, do you? So the fixed network is as important. >> Sure. >> And we're at mobile worlds. But actually what we beginning to hear and Crystal Bren did say this exactly, it's about the comp the access is sort of irrelevant. Fixed is better because it's more the cost the return on investment is better from fiber. Mobile we're going to change every so many years because we're a new generation. But we need to get the mechanism in place to deliver that. I actually don't agree that we should everyone should pay differently for what they use. It's a universal service. We need it as individuals. We need to make it sustainable for every user. Let's just not go for the biggest user. It's not, it's not the way to build it. It won't work if you do that you'll crash the system if you do that. And, and the other thing which I disagree on it's not about standing on the shoulders and benefiting from what- It's about cooperating across all levels. The hyperscalers want to work with the telcos as much as the telcos want to work with the hyperscalers. There's a lot of synergy there. There's a lot of ways they can work together. It's not one or the other. >> But I think you're saying let the cloud guys do the heavy lifting and I'm - >> Yeah. >> Not at all. >> And so you don't think so because I feel like the telcos are really good at pipes. They've always been good at pipes. They're engineers. >> Danielle: Yeah. >> Are they hanging on to the to the connectivity or should they let that go and well and go toward the developer. >> I mean AWS had two announcements on the 21st a week before MWC. And one was that telco network builder. This is literally being able to deploy a network capability at AWS with keystrokes. >> As a managed service. >> Danielle: Correct. >> Yeah. >> And so I don't know how the telco world I felt the shock waves, right? I was like, whoa, that seems really big. Because they're taking something that previously was like bread and butter. This is what differentiates each telco and now they've standardized it and made it super easy so anyone can do it. Now do I think the five nines of super crazy hardcore network criteria will be built on AWS this way? Probably not, but no >> It's not, it's not end twin. So you can't, no. >> Right. But private networks could be built with this pretty easily, right? And so telcos that don't have as much funding, right. Smaller, more experiments. I think it's going to change the way we think about building networks in telcos >> And those smaller telcos I think are going to be more developer friendly. >> Danielle: Yeah. >> They're going to have business models that invite those developers in. And that's, it's the disruption's going to come from the ISVs and the workloads that are on top of that. >> Well certainly what Dish is trying to do, right? Dish is trying to build a- they launched it reinvent a developer experience. >> Dave: Yeah. >> Right. Built around their network and you know, again I don't know, they were not part of this group that designed these eight APIs but I'm sure they're looking with great intent on what does this mean for them. They'll probably adopt them because they want people to consume the network as APIs. That's their whole thing that Mark Roanne is trying to do. >> Okay, and then they're doing open ran. But is it- they're not really cons- They're not as concerned as Rakuten with the reliability and is that the right play? >> In this discussion? Open RAN is not an issue. It really is irrelevant. It's relevant for the longer term future of the industry by dis aggregating and being able to share, especially ran sharing, for example, in the short term in rural environments. But we'll see some of that happening and it will change, but it will also influence the way the other, the existing ran providers build their services and offer their value. Look you got to remember in the relationship between the equipment providers and the telcos are very dramatically. Whether it's Ericson, NOKIA, Samsung, Huawei, whoever. So those relations really, and the managed services element to that depends on what skills people have in-house within the telco and what service they're trying to deliver. So there's never one size fits all in this industry. >> You're very balanced in your analysis and I appreciate that. >> I try to be. >> But I am not. (chuckles) >> So when Dr went off, this is my question. When Dr went off a couple years ago on the cloud's going to take over the world, you were skeptical. You gave a approach. Have you? >> I still am. >> Have you moderated your thoughts on that or- >> I believe the telecom industry is is a very strong industry. It's my industry of course I love it. But the relationship it is developing much different relationships with the ecosystem players around it. You mentioned developers, you mentioned the cloud players the equipment guys are changing there's so many moving parts to build the telco of the future that every country needs a very strong telco environment to be able to support the site as a whole. People individuals so- >> Well I think two years ago we were talking about should they or shouldn't they, and now it's an inevitability. >> I don't think we were Danielle. >> All using the hyperscalers. >> We were always going to need to transform the telcos from the conservative environments in which they developed. And they've had control of everything in order to reduce if they get no extra revenue at all, reducing the cost they've got to go on a cloud migration path to do that. >> Amenable. >> Has it been harder than you thought? >> It's been easier than I thought. >> You think it's gone faster than >> It's gone way faster than I thought. I mean pushing on this flywheel I thought for sure it would take five to 10 years it is moving. I mean the maths comp thing the AWS announcements last week they're putting in hyperscalers in Saudi Arabia which is probably one of the most sort of data private places in the world. It's happening really fast. >> What Azure's doing? >> I feel like I can't even go to sleep. Because I got to keep up with it. It's crazy. >> Guys. >> This is awesome. >> So awesome having you back on. >> Yeah. >> Chris, thanks for co-hosting. Appreciate you stay here. >> Yep. >> Danielle, amazing. We'll see you. >> See you soon. >> A lot of action here. We're going to come out >> Great. >> Check out your venue. >> Yeah the Togi buses that are outside. >> The big buses. You got a great setup there. We're going to see you on Wednesday. Thanks again. >> Awesome. Thanks. >> All right. Keep it right there. We'll be back to wrap up day two from MWC 23 on theCUBE. (upbeat music)

>> theCUBE's live coverage is made possible by funding from Dell Technologies. Creating technologies that drive human progress. (ambient music) >> Lisa: Hey everyone, welcome back to Barcelona, Spain. It's theCUBE Live at MWC 23. Lisa Martin with Dave Vellante. This is day two of four days of cube coverage but you know that, because you've already been watching yesterday and today. We're going to have a great conversation next with EnterpriseWeb and Red Hat. We've had great conversations the last day and a half about the Telco industry, the challenges, the opportunities. We're going to unpack that from this lens. Please welcome Dave Duggal, founder and CEO of EnterpriseWeb and Azhar Sayeed is here, Senior Director Solution Architecture at Red Hat. >> Guys, it's great to have you on the program. >> Yes. >> Thank you Lisa, >> Great being here with you. >> Dave let's go ahead and start with you. Give the audience an overview of EnterpriseWeb. What kind of business is it? What's the business model? What do you guys do? >> Okay so, EnterpriseWeb is reinventing middleware, right? So the historic middleware was to build vertically integrated stacks, right? And those stacks are now such becoming the rate limiters for interoperability for so the end-to-end solutions that everybody's looking for, right? Red Hat's talking about the unified platform. You guys are talking about Supercloud, EnterpriseWeb addresses that we've built middleware based on serverless architecture, so lightweight, low latency, high performance middleware. And we're working with the world's biggest, we sell through channels and we work through partners like Red Hat Intel, Fortnet, Keysight, Tech Mahindra. So working with some of the biggest players that have recognized the value of our innovation, to deliver transformation to the Telecom industry. >> So what are you guys doing together? Is this, is this an OpenShift play? >> Is it? >> Yeah. >> Yeah, so we've got two projects right her on the floor at MWC throughout the various partners, where EnterpriseWeb is actually providing an application layer, sorry application middleware over Red Hat's, OpenShift and we're essentially generating operators so Red Hat operators, so that all our vendors, and, sorry vendors that we onboard into our catalog can be deployed easily through the OpenShift platform. And we allow those, those vendors to be flexibly composed into network services. So the real challenge for operators historically is that they, they have challenges onboarding the vendors. It takes a long time. Each one of them is a snowflake. They, you know, even though there's standards they don't all observe or follow the same standards. So we make it easier using models, right? For, in a model driven process to on boards or streamline that onboarding process, compose functions into services deploy those services seamlessly through Red Hat's OpenShift, and then manage the, the lifecycle, like the quality of service and the SLAs for those services. >> So Red Hat obviously has pretty prominent Telco business has for a while. Red Hat OpenStack actually is is pretty popular within the Telco business. People thought, "Oh, OpenStack, that's dead." Actually, no, it's actually doing quite well. We see it all over the place where for whatever reason people want to build their own cloud. And, and so, so what's happening in the industry because you have the traditional Telcos we heard in the keynotes that kind of typical narrative about, you know, we can't let the over the top vendors do this again. We're, we're going to be Apifi everything, we're going to monetize this time around, not just with connectivity but the, but the fact is they really don't have a developer community. >> Yes. >> Yet anyway. >> Then you have these disruptors over here that are saying "Yeah, we're going to enable ISVs." How do you see it? What's the landscape look like? Help us understand, you know, what the horses on the track are doing. >> Sure. I think what has happened, Dave, is that the conversation has moved a little bit from where they were just looking at IS infrastructure service with virtual machines and OpenStack, as you mentioned, to how do we move up the value chain and look at different applications. And therein comes the rub, right? You have applications with different requirements, IT network that have various different requirements that are there. So as you start to build those cloud platform, as you start to modernize those set of applications, you then start to look at microservices and how you build them. You need the ability to orchestrate them. So some of those problem statements have moved from not just refactoring those applications, but actually now to how do you reliably deploy, manage in a multicloud multi cluster way. So this conversation around Supercloud or this conversation around multicloud is very >> You could say Supercloud. That's okay >> (Dave Duggal and Azhar laughs) >> It's absolutely very real though. The reason why it's very real is, if you look at transformations around Telco, there are two things that are happening. One, Telco IT, they're looking at partnerships with hybrid cloud, I mean with public cloud players to build a hybrid environment. They're also building their own Telco Cloud environment for their network functions. Now, in both of those spaces, they end up operating two to three different environments themselves. Now how do you create a level of abstraction across those? How do you manage that particular infrastructure? And then how do you orchestrate all of those different workloads? Those are the type of problems that they're actually beginning to solve. So they've moved on from really just putting that virtualizing their application, putting it on OpenStack to now really seriously looking at "How do I build a service?" "How do I leverage the catalog that's available both in my private and public and build an overall service process?" >> And by the way what you just described as hybrid cloud and multicloud is, you know Supercloud is what multicloud should have been. And what, what it originally became is "I run on this cloud and I run on this cloud" and "I run on this cloud and I have a hybrid." And, and Supercloud is meant to create a common experience across those clouds. >> Dave Duggal: Right? >> Thanks to, you know, Supercloud middleware. >> Yeah. >> Right? And, and so that's what you guys do. >> Yeah, exactly. Exactly. Dave, I mean, even the name EnterpriseWeb, you know we started from looking from the application layer down. If you look at it, the last 10 years we've looked from the infrastructure up, right? And now everybody's looking northbound saying "You know what, actually, if I look from the infrastructure up the only thing I'll ever build is silos, right?" And those silos get in the way of the interoperability and the agility the businesses want. So we take the perspective as high level abstractions, common tools, so that if I'm a CXO, I can look down on my environments, right? When I'm really not, I honestly, if I'm an, if I'm a CEO I don't really care or CXO, I don't really care so much about my infrastructure to be honest. I care about my applications and their behavior. I care about my SLAs and my quality of service, right? Those are the things I care about. So I really want an EnterpriseWeb, right? Something that helps me connect all my distributed applications all across all of the environments. So I can have one place a consistency layer that speaks a common language. We know that there's a lot of heterogeneity down all those layers and a lot of complexity down those layers. But the business doesn't care. They don't want to care, right? They want to actually take their applications deploy them where they're the most performant where they're getting the best cost, right? The lowest and maybe sustainability concerns, all those. They want to address those problems, meet their SLAs meet their quality service. And you know what, if it's running on Amazon, great. If it's running on Google Cloud platform, great. If it, you know, we're doing one project right here that we're demonstrating here is with with Amazon Tech Mahindra and OpenShift, where we took a disaggregated 5G core, right? So this is like sort of latest telecom, you know net networking software, right? We're deploying pulling elements of that network across core, across Amazon EKS, OpenShift on Red Hat ROSA, as well as just OpenShift for cloud. And we, through a single pane of deployment and management, we deployed the elements of the 5G core across them and then connected them in an end-to-end process. That's Telco Supercloud. >> Dave Vellante: So that's an O-RAN deployment. >> Yeah that's >> So, the big advantage of that, pardon me, Dave but the big advantage of that is the customer really doesn't care where the components are being served from for them. It's a 5G capability. It happens to sit in different locations. And that's, it's, it's about how do you abstract and how do you manage all those different workloads in a cohesive way? And that's exactly what EnterpriseWeb is bringing to the table. And what we do is we abstract the underlying infrastructure which is the cloud layer. So if, because AWS operating environment is different then private cloud operating environment then Azure environment, you have the networking is set up is different in each one of them. If there is a way you can abstract all of that and present it in a common operating model it becomes a lot easier than for anybody to be able to consume. >> And what a lot of customers tell me is the way they deal with multicloud complexity is they go with mono cloud, right? And so they'll lose out on some of the best services >> Absolutely >> If best of, so that's not >> that's not ideal, but at the end of the day, agree, developers don't want to muck with all the plumbing >> Dave Duggal: Yep. >> They want to write code. >> Azhar: Correct. >> So like I come back to are the traditional Telcos leaning in on a way that they're going to enable ISVs and developers to write on top of those platforms? Or are there sort of new entrance and disruptors? And I know, I know the answer is both >> Dave Duggal: Yep. >> but I feel as though the Telcos still haven't, traditional Telcos haven't tuned in to that developer affinity, but you guys sell to them. >> What, what are you seeing? >> Yeah, so >> What we have seen is there are Telcos fall into several categories there. If you look at the most mature ones, you know they are very eager to move up the value chain. There are some smaller very nimble ones that have actually doing, they're actually doing something really interesting. For example, they've provided sandbox environments to developers to say "Go develop your applications to the sandbox environment." We'll use that to build an net service with you. I can give you some interesting examples across the globe that, where that is happening, right? In AsiaPac, particularly in Australia, ANZ region. There are a couple of providers who have who have done this, but in, in, in a very interesting way. But the challenges to them, why it's not completely open or public yet is primarily because they haven't figured out how to exactly monetize that. And, and that's the reason why. So in the absence of that, what will happen is they they have to rely on the ISV ecosystem to be able to build those capabilities which they can then bring it on as part of the catalog. But in Latin America, I was talking to one of the providers and they said, "Well look we have a public cloud, we have our own public cloud, right?" What we want do is use that to offer localized services not just bring everything in from the top >> But, but we heard from Ericson's CEO they're basically going to monetize it by what I call "gouge", the developers >> (Azhar laughs) >> access to the network telemetry as opposed to saying, "Hey, here's an open platform development on top of it and it will maybe create something like an app store and we'll take a piece of the action." >> So ours, >> to be is a better model. >> Yeah. So that's perfect. Our second project that we're showing here is with Intel, right? So Intel came to us cause they are a reputation for doing advanced automation solutions. They gave us carte blanche in their labs. So this is Intel Network Builders they said pick your partners. And we went with the Red Hat, Fort Net, Keysite this company KX doing AIML. But to address your DevX, here's Intel explicitly wants to get closer to the developers by exposing their APIs, open APIs over their infrastructure. Just like Red Hat has APIs, right? And so they can expose them northbound to developers so developers can leverage and tune their applications, right? But the challenge there is what Intel is doing at the low level network infrastructure, right? Is fundamentally complex, right? What you want is an abstraction layer where develop and this gets to, to your point Dave where you just said like "The developers just want to get their job done." or really they want to focus on the business logic and accelerate that service delivery, right? So the idea here is an EnterpriseWeb they can literally declaratively compose their services, express their intent. "I want this to run optimized for low latency. I want this to run optimized for energy consumption." Right? And that's all they say, right? That's a very high level statement. And then the run time translates it between all the elements that are participating in that service to realize the developer's intent, right? No hands, right? Zero touch, right? So that's now a movement in telecom. So you're right, it's taking a while because these are pretty fundamental shifts, right? But it's intent based networking, right? So it's almost two parts, right? One is you have to have the open APIs, right? So that the infrastructure has to expose its capabilities. Then you need abstractions over the top that make it simple for developers to take, you know, make use of them. >> See, one of the demonstrations we are doing is around AIOps. And I've had literally here on this floor, two conversations around what I call as network as a platform. Although it sounds like a cliche term, that's exactly what Dave was describing in terms of exposing APIs from the infrastructure and utilizing them. So once you get that data, then now you can do analytics and do machine learning to be able to build models and figure out how you can orchestrate better how you can monetize better, how can how you can utilize better, right? So all of those things become important. It's just not about internal optimization but it's also about how do you expose it to third party ecosystem to translate that into better delivery mechanisms or IOT capability and so on. >> But if they're going to charge me for every API call in the network I'm going to go broke (team laughs) >> And I'm going to get really pissed. I mean, I feel like, I'm just running down, Oracle. IBM tried it. Oracle, okay, they got Java, but they don't they don't have developer jobs. VMware, okay? They got Aria. EMC used to have a thing called code. IBM had to buy Red Hat to get to the developer community. (Lisa laughs) >> So I feel like the telcos don't today have those developer shops. So, so they have to partner. [Azhar] Yes. >> With guys like you and then be more open and and let a zillion flowers bloom or else they're going to get disrupted in a big way and they're going to it's going to be a repeat of the over, over the top in, in in a different model that I can't predict. >> Yeah. >> Absolutely true. I mean, look, they cannot be in the connectivity business. Telcos cannot be just in the connectivity business. It's, I think so, you know, >> Dave Vellante: You had a fry a frozen hand (Dave Daggul laughs) >> off that, you know. >> Well, you know, think about they almost have to go become over the top on themselves, right? That's what the cloud guys are doing, right? >> Yeah. >> They're riding over their backbone that by taking a creating a high level abstraction, they in turn abstract away the infrastructure underneath them, right? And that's really the end game >> Right? >> Dave Vellante: Yeah. >> Is because now, >> they're over the top it's their network, it's their infrastructure, right? They don't want to become bid pipes. >> Yep. >> Now you, they can take OpenShift, run that in any cloud. >> Yep. >> Right? >> You can run that in hybrid cloud, enterprise web can do the application layer configuration and management. And together we're running, you know, OSI layers one through seven, east to west, north to south. We're running across the the RAN, the core and the transport. And that is telco super cloud, my friend. >> Yeah. Well, >> (Dave Duggal laughs) >> I'm dominating the conversation cause I love talking super cloud. >> I knew you would. >> So speaking of super superpowers, when you're in customer or prospective customer conversations with providers and they've got, obviously they're they're in this transformative state right now. How, what do you describe as the superpower between Red Hat and EnterpriseWeb in terms of really helping these Telcos transforms. But at the end of the day, the connectivity's there the end user gets what they want, which is I want this to work wherever I am. >> Yeah, yeah. That's a great question, Lisa. So I think the way you could look at it is most software has, has been evolved to be specialized, right? So in Telcos' no different, right? We have this in the enterprise, right? All these specialized stacks, all these components that they wire together in the, in you think of Telco as a sort of a super set of enterprise problems, right? They have all those problems like magnified manyfold, right? And so you have specialized, let's say orchestrators and other tools for every Telco domain for every Telco layer. Now you have a zoo of orchestrators, right? None of them were designed to work together, right? They all speak a specific language, let's say quote unquote for doing a specific purpose. But everything that's interesting in the 21st century is across layers and across domains, right? If a siloed static application, those are dead, right? Nobody's doing those anymore. Even developers don't do those developers are doing composition today. They're not doing, nobody wants to hear about a 6 million lines of code, right? They want to hear, "How did you take these five things and bring 'em together for productive use?" >> Lisa: Right. How did you deliver faster for my enterprise? How did you save me money? How did you create business value? And that's what we're doing together. >> I mean, just to add on to Dave, I was talking to one of the providers, they have more than 30,000 nodes in their infrastructure. When I say no to your servers running, you know, Kubernetes,running open stack, running different components. If try managing that in one single entity, if you will. Not possible. You got to fragment, you got to segment in some way. Now the question is, if you are not exposing that particular infrastructure and the appropriate KPIs and appropriate things, you will not be able to efficiently utilize that across the board. So you need almost a construct that creates like a manager of managers, a hierarchical structure, which would allow you to be more intelligent in terms of how you place those, how you manage that. And so when you ask the question about what's the secret sauce between the two, well this is exactly where EnterpriseWeb brings in that capability to analyze information, be more intelligent about it. And what we do is provide an abstraction of the cloud layer so that they can, you know, then do the right job in terms of making sure that it's appropriate and it's consistent. >> Consistency is key. Guys, thank you so much. It's been a pleasure really digging through EnterpriseWeb. >> Thank you. >> What you're doing >> with Red Hat. How you're helping the organization transform and Supercloud, we can't forget Supercloud. (Dave Vellante laughs) >> Fight Supercloud. Guys, thank you so much for your time. >> Thank you so much Lisa. >> Thank you. >> Thank you guys. >> Very nice. >> Lisa: We really appreciate it. >> For our guests and for Dave Vellante, I'm Lisa Martin. You're watching theCUBE, the leader in live tech coverage coming to you live from MWC 23. We'll be back after a short break.

>> From theCUBE Studios in Palo Alto in Boston, bringing you data-driven insights from theCUBE and ETR, this is Breaking Analysis with Dave Vellante. >> While never really meant to be a consumer tech event, the rapid ascendancy of smartphones sucked much of the air out of Mobile World Congress over the years, now MWC. And while the device manufacturers continue to have a major presence at the show, the maturity of intelligent devices, longer life cycles, and the disaggregation of the network stack, have put enterprise technologies front and center in the telco business. Semiconductor manufacturers, network equipment players, infrastructure companies, cloud vendors, software providers, and a spate of startups are eyeing the trillion dollar plus communications industry as one of the next big things to watch this decade. Hello, and welcome to this week's Wikibon CUBE Insights, powered by ETR. In this Breaking Analysis, we bring you part two of our ongoing coverage of MWC '23, with some new data on enterprise players specifically in large telco environments, a brief glimpse at some of the pre-announcement news and corresponding themes ahead of MWC, and some of the key announcement areas we'll be watching at the show on theCUBE. Now, last week we shared some ETR data that showed how traditional enterprise tech players were performing, specifically within the telecoms vertical. Here's a new look at that data from ETR, which isolates the same companies, but cuts the data for what ETR calls large telco. The N in this cut is 196, down from 288 last week when we included all company sizes in the dataset. Now remember the two dimensions here, on the y-axis is net score, or spending momentum, and on the x-axis is pervasiveness in the data set. The table insert in the upper left informs how the dots and companies are plotted, and that red dotted line, the horizontal line at 40%, that indicates a highly elevated net score. Now while the data are not dramatically different in terms of relative positioning, there are a couple of changes at the margin. So just going down the list and focusing on net score. Azure is comparable, but slightly lower in this sector in the large telco than it was overall. Google Cloud comes in at number two, and basically swapped places with AWS, which drops slightly in the large telco relative to overall telco. Snowflake is also slightly down by one percentage point, but maintains its position. Remember Snowflake, overall, its net score is much, much higher when measuring across all verticals. Snowflake comes down in telco, and relative to overall, a little bit down in large telco, but it's making some moves to attack this market that we'll talk about in a moment. Next are Red Hat OpenStack and Databricks. About the same in large tech telco as they were an overall telco. Then there's Dell next that has a big presence at MWC and is getting serious about driving 16G adoption, and new servers, and edge servers, and other partnerships. Cisco and Red Hat OpenShift basically swapped spots when moving from all telco to large telco, as Cisco drops and Red Hat bumps up a bit. And VMware dropped about four percentage points in large telco. Accenture moved up dramatically, about nine percentage points in big telco, large telco relative to all telco. HPE dropped a couple of percentage points. Oracle stayed about the same. And IBM surprisingly dropped by about five points. So look, I understand not a ton of change in terms of spending momentum in the large sector versus telco overall, but some deltas. The bottom line for enterprise players is one, they're just getting started in this new disruption journey that they're on as the stack disaggregates. Two, all these players have experience in delivering horizontal solutions, but now working with partners and identifying big problems to be solved, and three, many of these companies are generally not the fastest moving firms relative to smaller disruptive disruptors. Now, cloud has been an exception in fairness. But the good news for the legacy infrastructure and IT companies is that the telco transformation and the 5G buildout is going to take years. So it's moving at a pace that is very favorable to many of these companies. Okay, so looking at just some of the pre-announcement highlights that have hit the wire this week, I want to give you a glimpse of the diversity of innovation that is occurring in the telecommunication space. You got semiconductor manufacturers, device makers, network equipment players, carriers, cloud vendors, enterprise tech companies, software companies, startups. Now we've included, you'll see in this list, we've included OpeRAN, that logo, because there's so much buzz around the topic and we're going to come back to that. But suffice it to say, there's no way we can cover all the announcements from the 2000 plus exhibitors at the show. So we're going to cherry pick here and make a few call outs. Hewlett Packard Enterprise announced an acquisition of an Italian private cellular network company called AthoNet. Zeus Kerravala wrote about it on SiliconANGLE if you want more details. Now interestingly, HPE has a partnership with Solana, which also does private 5G. But according to Zeus, Solona is more of an out-of-the-box solution, whereas AthoNet is designed for the core and requires more integration. And as you'll see in a moment, there's going to be a lot of talk at the show about private network. There's going to be a lot of news there from other competitors, and we're going to be watching that closely. And while many are concerned about the P5G, private 5G, encroaching on wifi, Kerravala doesn't see it that way. Rather, he feels that these private networks are really designed for more industrial, and you know mission critical environments, like factories, and warehouses that are run by robots, et cetera. 'Cause these can justify the increased expense of private networks. Whereas wifi remains a very low cost and flexible option for, you know, whatever offices and homes. Now, over to Dell. Dell announced its intent to go hard after opening up the telco network with the announcement that in the second half of this year it's going to begin shipping its infrastructure blocks for Red Hat. Remember it's like kind of the converged infrastructure for telco with a more open ecosystem and sort of more flexible, you know, more mature engineered system. Dell has also announced a range of PowerEdge servers for a variety of use cases. A big wide line bringing forth its 16G portfolio and aiming squarely at the telco space. Dell also announced, here we go, a private wireless offering with airspan, and Expedo, and a solution with AthoNet, the company HPE announced it was purchasing. So I guess Dell and HPE are now partnering up in the private wireless space, and yes, hell is freezing over folks. We'll see where that relationship goes in the mid- to long-term. Dell also announced new lab and certification capabilities, which we said last week was going to be critical for the further adoption of open ecosystem technology. So props to Dell for, you know, putting real emphasis and investment in that. AWS also made a number of announcements in this space including private wireless solutions and associated managed services. AWS named Deutsche Telekom, Orange, T-Mobile, Telefonica, and some others as partners. And AWS announced the stepped up partnership, specifically with T-Mobile, to bring AWS services to T-Mobile's network portfolio. Snowflake, back to Snowflake, announced its telecom data cloud. Remember we showed the data earlier, it's Snowflake not as strong in the telco sector, but they're continuing to move toward this go-to market alignment within key industries, realigning their go-to market by vertical. It also announced that AT&T, and a number of other partners, are collaborating to break down data silos specifically in telco. Look, essentially, this is Snowflake taking its core value prop to the telco vertical and forming key partnerships that resonate in the space. So think simplification, breaking down silos, data sharing, eventually data monetization. Samsung previewed its future capability to allow smartphones to access satellite services, something Apple has previously done. AMD, Intel, Marvell, Qualcomm, are all in the act, all the semiconductor players. Qualcomm for example, announced along with Telefonica, and Erickson, a 5G millimeter network that will be showcased in Spain at the event this coming week using Qualcomm Snapdragon chipset platform, based on none other than Arm technology. Of course, Arm we said is going to dominate the edge, and is is clearly doing so. It's got the volume advantage over, you know, traditional Intel, you know, X86 architectures. And it's no surprise that Microsoft is touting its open AI relationship. You're going to hear a lot of AI talk at this conference as is AI is now, you know, is the now topic. All right, we could go on and on and on. There's just so much going on at Mobile World Congress or MWC, that we just wanted to give you a glimpse of some of the highlights that we've been watching. Which brings us to the key topics and issues that we'll be exploring at MWC next week. We touched on some of this last week. A big topic of conversation will of course be, you know, 5G. Is it ever going to become real? Is it, is anybody ever going to make money at 5G? There's so much excitement around and anticipation around 5G. It has not lived up to the hype, but that's because the rollout, as we've previous reported, is going to take years. And part of that rollout is going to rely on the disaggregation of the hardened telco stack, as we reported last week and in previous Breaking Analysis episodes. OpenRAN is a big component of that evolution. You know, as our RAN intelligent controllers, RICs, which essentially the brain of OpenRAN, if you will. Now as we build out 5G networks at massive scale and accommodate unprecedented volumes of data and apply compute-hungry AI to all this data, the issue of energy efficiency is going to be front and center. It has to be. Not only is it a, you know, hot political issue, the reality is that improving power efficiency is compulsory or the whole vision of telco's future is going to come crashing down. So chip manufacturers, equipment makers, cloud providers, everybody is going to be doubling down and clicking on this topic. Let's talk about AI. AI as we said, it is the hot topic right now, but it is happening not only in consumer, with things like ChatGPT. And think about the theme of this Breaking Analysis in the enterprise, AI in the enterprise cannot be ChatGPT. It cannot be error prone the way ChatGPT is. It has to be clean, reliable, governed, accurate. It's got to be ethical. It's got to be trusted. Okay, we're going to have Zeus Kerravala on the show next week and definitely want to get his take on private networks and how they're going to impact wifi. You know, will private networks cannibalize wifi? If not, why not? He wrote about this again on SiliconANGLE if you want more details, and we're going to unpack that on theCUBE this week. And finally, as always we'll be following the data flows to understand where and how telcos, cloud players, startups, software companies, disruptors, legacy companies, end customers, how are they going to make money from new data opportunities? 'Cause we often say in theCUBE, don't ever bet against data. All right, that's a wrap for today. Remember theCUBE is going to be on location at MWC 2023 next week. We got a great set. We're in the walkway in between halls four and five, right in Congress Square, stand CS-60. Look for us, we got a full schedule. If you got a great story or you have news, stop by. We're going to try to get you on the program. I'll be there with Lisa Martin, co-hosting, David Nicholson as well, and the entire CUBE crew, so don't forget to come by and see us. I want to thank Alex Myerson, who's on production and manages the podcast, and Ken Schiffman, as well, in our Boston studio. Kristen Martin and Cheryl Knight help get the word out on social media and in our newsletters. And Rob Hof is our editor-in-chief over at SiliconANGLE.com. He does some great editing. Thank you. All right, remember all these episodes they are available as podcasts wherever you listen. All you got to do is search Breaking Analysis podcasts. I publish each week on Wikibon.com and SiliconANGLE.com. All the video content is available on demand at theCUBE.net, or you can email me directly if you want to get in touch David.Vellante@SiliconANGLE.com or DM me @DVellante, or comment on our LinkedIn posts. And please do check out ETR.ai for the best survey data in the enterprise tech business. This is Dave Vellante for theCUBE Insights, powered by ETR. Thanks for watching. We'll see you next week at Mobile World Congress '23, MWC '23, or next time on Breaking Analysis. (bright music)

>> From the Cube Studios in Palo Alto in Boston, bringing you data-driven insights from The Cube and ETR. This is "Breaking Analysis" with Dave Vellante. >> The world's leading telcos are trying to shed the stigma of being monopolies lacking innovation. Telcos have been great at operational efficiency and connectivity and living off of transmission, and the costs and expenses or revenue associated with that transmission. But in a world beyond telephone poles and basic wireless and mobile services, how will telcos modernize and become more agile and monetize new opportunities brought about by 5G and private wireless and a spate of new innovations and infrastructure, cloud data and apps? Hello, and welcome to this week's Wikibon CUBE Insights powered by ETR. In this breaking analysis and ahead of Mobile World Congress or now, MWC23, we explore the evolution of the telco business and how the industry is in many ways, mimicking transformations that took place decades ago in enterprise IT. We'll model some of the traditional enterprise vendors using ETR data and investigate how they're faring in the telecommunications sector, and we'll pose some of the key issues facing the industry this decade. First, let's take a look at what the GSMA has in store for MWC23. GSMA is the host of what used to be called Mobile World Congress. They've set the theme for this year's event as "Velocity" and they've rebranded MWC to reflect the fact that mobile technology is only one part of the story. MWC has become one of the world's premier events highlighting innovations not only in Telco, mobile and 5G, but the collision between cloud, infrastructure, apps, private networks, smart industries, machine intelligence, and AI, and more. MWC comprises an enormous ecosystem of service providers, technology companies, and firms from virtually every industry including sports and entertainment. And as well, GSMA, along with its venue partner at the Fira Barcelona, have placed a major emphasis on sustainability and public and private partnerships. Virtually every industry will be represented at the event because every industry is impacted by the trends and opportunities in this space. GSMA has said it expects 80,000 attendees at MWC this year, not quite back to 2019 levels, but trending in that direction. Of course, attendance from Chinese participants has historically been very high at the show, and obviously the continued travel issues from that region are affecting the overall attendance, but still very strong. And despite these concerns, Huawei, the giant Chinese technology company. has the largest physical presence of any exhibitor at the show. And finally, GSMA estimates that more than $300 million in economic benefit will result from the event which takes place at the end of February and early March. And The Cube will be back at MWC this year with a major presence thanks to our anchor sponsor, Dell Technologies and other supporters of our content program, including Enterprise Web, ArcaOS, VMware, Snowflake, Cisco, AWS, and others. And one of the areas we're interested in exploring is the evolution of the telco stack. It's a topic that's often talked about and one that we've observed taking place in the 1990s when the vertically integrated IBM mainframe monopoly gave way to a disintegrated and horizontal industry structure. And in many ways, the same thing is happening today in telecommunications, which is shown on the left-hand side of this diagram. Historically, telcos have relied on a hardened, integrated, and incredibly reliable, and secure set of hardware and software services that have been fully vetted and tested, and certified, and relied upon for decades. And at the top of that stack on the left are the crown jewels of the telco stack, the operational support systems and the business support systems. For the OSS, we're talking about things like network management, network operations, service delivery, quality of service, fulfillment assurance, and things like that. For the BSS systems, these refer to customer-facing elements of the stack, like revenue, order management, what products they sell, billing, and customer service. And what we're seeing is telcos have been really good at operational efficiency and making money off of transport and connectivity, but they've lacked the innovation in services and applications. They own the pipes and that works well, but others, be the over-the-top content companies, or private network providers and increasingly, cloud providers have been able to bypass the telcos, reach around them, if you will, and drive innovation. And so, the right-most diagram speaks to the need to disaggregate pieces of the stack. And while the similarities to the 1990s in enterprise IT are greater than the differences, there are things that are different. For example, the granularity of hardware infrastructure will not likely be as high where competition occurred back in the 90s at every layer of the value chain with very little infrastructure integration. That of course changed in the 2010s with converged infrastructure and hyper-converged and also software defined. So, that's one difference. And the advent of cloud, containers, microservices, and AI, none of that was really a major factor in the disintegration of legacy IT. And that probably means that disruptors can move even faster than did the likes of Intel and Microsoft, Oracle, Cisco, and the Seagates of the 1990s. As well, while many of the products and services will come from traditional enterprise IT names like Dell, HPE, Cisco, Red Hat, VMware, AWS, Microsoft, Google, et cetera, many of the names are going to be different and come from traditional network equipment providers. These are names like Ericsson and Huawei, and Nokia, and other names, like Wind River, and Rakuten, and Dish Networks. And there are enormous opportunities in data to help telecom companies and their competitors go beyond telemetry data into more advanced analytics and data monetization. There's also going to be an entirely new set of apps based on the workloads and use cases ranging from hospitals, sports arenas, race tracks, shipping ports, you name it. Virtually every vertical will participate in this transformation as the industry evolves its focus toward innovation, agility, and open ecosystems. Now remember, this is not a binary state. There are going to be greenfield companies disrupting the apple cart, but the incumbent telcos are going to have to continue to ensure newer systems work with their legacy infrastructure, in their OSS and BSS existing systems. And as we know, this is not going to be an overnight task. Integration is a difficult thing, transformations, migrations. So that's what makes this all so interesting because others can come in with Greenfield and potentially disrupt. There'll be interesting partnerships and ecosystems will form and coalitions will also form. Now, we mentioned that several traditional enterprise companies are or will be playing in this space. Now, ETR doesn't have a ton of data on specific telecom equipment and software providers, but it does have some interesting data that we cut for this breaking analysis. What we're showing here in this graphic is some of the names that we've followed over the years and how they're faring. Specifically, we did the cut within the telco sector. So the Y-axis here shows net score or spending velocity. And the horizontal axis, that shows the presence or pervasiveness in the data set. And that table insert in the upper left, that informs as to how the dots are plotted. You know, the two columns there, net score and the ends. And that red-dotted line, that horizontal line at 40%, that is an indicator of a highly elevated level. Anything above that, we consider quite outstanding. And what we'll do now is we'll comment on some of the cohorts and share with you how they're doing in telecommunications, and that sector, that vertical relative to their position overall in the data set. Let's start with the public cloud players. They're prominent in every industry. Telcos, telecommunications is no exception and it's quite an interesting cohort here. On the one hand, they can help telecommunication firms modernize and become more agile by eliminating the heavy lifting and you know, all the cloud, you know, value prop, data center costs, and the cloud benefits. At the same time, public cloud players are bringing their services to the edge, building out their own global networks and are a disruptive force to traditional telcos. All right, let's talk about Azure first. Their net score is basically identical to telco relative to its overall average. AWS's net score is higher in telco by just a few percentage points. Google Cloud platform is eight percentage points higher in telco with a 53% net score. So all three hyperscalers have an equal or stronger presence in telco than their average overall. Okay, let's look at the traditional enterprise hardware and software infrastructure cohort. Dell, Cisco, HPE, Red Hat, VMware, and Oracle. We've highlighted in this chart just as sort of indicators or proxies. Dell's net score's 10 percentage points higher in telco than its overall average. Interesting. Cisco's is a bit higher. HPE's is actually lower by about nine percentage points in the ETR survey, and VMware's is lower by about four percentage points. Now, Red Hat is really interesting. OpenStack, as we've previously reported is popular with telcos who want to build out their own private cloud. And the data shows that Red Hat OpenStack's net score is 15 percentage points higher in the telco sector than its overall average. OpenShift, on the other hand, has a net score that's four percentage points lower in telco than its overall average. So this to us talks to the pace of adoption of microservices and containers. You know, it's going to happen, but it's going to happen more slowly. Finally, Oracle's spending momentum is somewhat lower in the sector than its average, despite the firm having a decent telco business. IBM and Accenture, heavy services companies are both lower in this sector than their average. And real quickly, snowflake's net score is much lower by about 12 percentage points relative to its very high average net score of 62%. But we look for them to be a player in this space as telcos need to modernize their analytics stack and share data in a governed manner. Databricks' net score is also much lower than its average by about 13 points. And same, I would expect them to be a player as open architectures and cloud gains steam in telco. All right, let's close out now on what we're going to be talking about at MWC23 and some of the key issues that we'll be unpacking. We've talked about stack disaggregation in this breaking analysis, but the key here will be the pace at which it will reach the operational efficiency and reliability of closed stacks. Telcos, you know, in a large part, they're engineering heavy firms and much of their work takes place, kind of in the basement, in the dark. It's not really a big public hype machine, and they tend to move slowly and cautiously. While they understand the importance of agility, they're going to be careful because, you know, it's in their DNA. And so at the same time, if they don't move fast enough, they're going to get hurt and disrupted by competitors. So that's going to be a topic of conversation, and we'll be looking for proof points. And the other comment I'll make is around integration. Telcos because of their conservatism will benefit from better testing and those firms that can innovate on the testing front and have labs and certifications and innovate at that level, with an ecosystem are going to be in a better position. Because open sometimes means wild west. So the more players like Dell, HPE, Cisco, Red Hat, et cetera, that do that and align with their ecosystems and provide those resources, the faster adoption is going to go. So we'll be looking for, you know, who's actually doing that, Open RAN or Radio Access Networks. That fits in this discussion because O-RAN is an emerging network architecture. It essentially enables the use of open technologies from an ecosystem and over time, look at O-RAN is going to be open, but the questions, you know, a lot of questions remain as to when it will be able to deliver the operational efficiency of traditional RAN. Got some interesting dynamics going on. Rakuten is a company that's working hard on this problem, really focusing on operational efficiency. Then you got Dish Networks. They're also embracing O-RAN. They're coming at it more from service innovation. So that's something that we'll be monitoring and unpacking. We're going to look at cloud as a disruptor. On the one hand, cloud can help drive agility, as we said earlier and optionality, and innovation for incumbent telcos. But the flip side is going to also do the same for startups trying to disrupt and cloud attracts startups. While some of the telcos are actually embracing the cloud, many are being cautious. So that's going to be an interesting topic of discussion. And there's private wireless networks and 5G, and hyperlocal private networks, they're being deployed, you know, at the edge. This idea of open edge is also a really hot topic and this trend is going to accelerate. You know, the importance here is that the use cases are going to be widely varied. The needs of a hospital are going to be different than those of a sports venue are different from a remote drilling location, and energy or a concert venue. Things like real-time AI inference and data flows are going to bring new services and monetization opportunities. And many firms are going to be bypassing traditional telecommunications networks to build these out. Satellites as well, we're going to see, you know, in this decade, you're going to have, you're going to look down at Google Earth and you're going to see real-time. You know, today you see snapshots and so, lots of innovations going in that space. So how is this going to disrupt industries and traditional industry structures? Now, as always, we'll be looking at data angles, right? 'Cause it's in The Cube's DNA to follow the data and what opportunities and risks data brings. The Cube is going to be on location at MWC23 at the end of the month. We got a great set. We're in the walkway between halls four and five, right in Congress Square, it's booths CS60. So we'll have a full, they're called Stan CS60. We have a full schedule. I'm going to be there with Lisa Martin, Dave Nicholson and the entire Cube crew, so don't forget to stop by. All right, that's a wrap. I want to thank Alex Myerson, who's on production and manages the podcast, Ken Schiffman as well. Kristin Martin and Cheryl Knight help get the word out on social media and in our newsletters. And Rob Hof is our editor-in-chief over at Silicon Angle, does some great stuff for us. Thank you all. Remember, all these episodes are available as podcasts. Wherever you listen, just search "Breaking Analysis" podcasts I publish each week on wikibon.com and silicon angle.com. And all the video content is available on demand at thecube.net. You can email me directly at david.vellante@silicon angle.com. You can DM me at dvellante or comment on my LinkedIn post. Please do check out etr.ai for the best survey data in the enterprise tech business. This is Dave Vellante for The Cube Insights powered by ETR. Thanks for watching and we'll see you at Mobile World Congress, and/or at next time on "Breaking Analysis." (bright music) (bright music fades)

(bright music) >> Hi, everybody, this is Dave Vellante, welcome back to Supercloud 2. Last August, at the first Supercloud event, we invited the broader community to help further define Supercloud, we assessed its viability, and identified the critical elements and deployment models of the concept. The objectives here at Supercloud too are, first of all, to continue to tighten and test the concept, the second is, we want to get real world input from practitioners on the problems that they're facing and the viability of Supercloud in terms of applying it to their business. So on the program, we got companies like Walmart, Sachs, Western Union, Ionis Pharmaceuticals, NASDAQ, and others. And the third thing that we want to do is we want to drill into the intersection of cloud and data to project what the future looks like in the context of Supercloud. So in this segment, we want to explore the concept of data architectures and what's going to be required for Supercloud. And I'm pleased to welcome one of our Supercloud sponsors, ChaosSearch, Ed Walsh is the CEO of the company, with Thomas Hazel, who's the Founder, CTO, and Chief Scientist. Guys, good to see you again, thanks for coming into our Marlborough studio. >> Always great. >> Great to be here. >> Okay, so there's a little debate, I'm going to put you right in the spot. (Ed chuckling) A little debate going on in the community started by Bob Muglia, a former CEO of Snowflake, and he was at Microsoft for a long time, and he looked at the Supercloud definition, said, "I think you need to tighten it up a little bit." So, here's what he came up with. He said, "A Supercloud is a platform that provides a programmatically consistent set of services hosted on heterogeneous cloud providers." So he's calling it a platform, not an architecture, which was kind of interesting. And so presumably the platform owner is going to be responsible for the architecture, but Dr. Nelu Mihai, who's a computer scientist behind the Cloud of Clouds Project, he chimed in and responded with the following. He said, "Cloud is a programming paradigm supporting the entire lifecycle of applications with data and logic natively distributed. Supercloud is an open architecture that integrates heterogeneous clouds in an agnostic manner." So, Ed, words matter. Is this an architecture or is it a platform? >> Put us on the spot. So, I'm sure you have concepts, I would say it's an architectural or design principle. Listen, I look at Supercloud as a mega trend, just like cloud, just like data analytics. And some companies are using the principle, design principles, to literally get dramatically ahead of everyone else. I mean, things you couldn't possibly do if you didn't use cloud principles, right? So I think it's a Supercloud effect, you're able to do things you're not able to. So I think it's more a design principle, but if you do it right, you get dramatic effect as far as customer value. >> So the conversation that we were having with Muglia, and Tristan Handy of dbt Labs, was, I'll set it up as the following, and, Thomas, would love to get your thoughts, if you have a CRM, think about applications today, it's all about forms and codifying business processes, you type a bunch of stuff into Salesforce, and all the salespeople do it, and this machine generates a forecast. What if you have this new type of data app that pulls data from the transaction system, the e-commerce, the supply chain, the partner ecosystem, et cetera, and then, without humans, actually comes up with a plan. That's their vision. And Muglia was saying, in order to do that, you need to rethink data architectures and database architectures specifically, you need to get down to the level of how the data is stored on the disc. What are your thoughts on that? Well, first of all, I'm going to cop out, I think it's actually both. I do think it's a design principle, I think it's not open technology, but open APIs, open access, and you can build a platform on that design principle architecture. Now, I'm a database person, I love solving the database problems. >> I'm waited for you to launch into this. >> Yeah, so I mean, you know, Snowflake is a database, right? It's a distributed database. And we wanted to crack those codes, because, multi-region, multi-cloud, customers wanted access to their data, and their data is in a variety of forms, all these services that you're talked about. And so what I saw as a core principle was cloud object storage, everyone streams their data to cloud object storage. From there we said, well, how about we rethink database architecture, rethink file format, so that we can take each one of these services and bring them together, whether distributively or centrally, such that customers can access and get answers, whether it's operational data, whether it's business data, AKA search, or SQL, complex distributed joins. But we had to rethink the architecture. I like to say we're not a first generation, or a second, we're a third generation distributed database on pure, pure cloud storage, no caching, no SSDs. Why? Because all that availability, the cost of time, is a struggle, and cloud object storage, we think, is the answer. >> So when you're saying no caching, so when I think about how companies are solving some, you know, pretty hairy problems, take MySQL Heatwave, everybody thought Oracle was going to just forget about MySQL, well, they come out with Heatwave. And the way they solve problems, and you see their benchmarks against Amazon, "Oh, we crush everybody," is they put it all in memory. So you said no caching? You're not getting performance through caching? How is that true, and how are you getting performance? >> Well, so five, six years ago, right? When you realize that cloud object storage is going to be everywhere, and it's going to be a core foundational, if you will, fabric, what would you do? Well, a lot of times the second generation say, "We'll take it out of cloud storage, put in SSDs or something, and put into cache." And that adds a lot of time, adds a lot of costs. But I said, what if, what if we could actually make the first read hot, the first read distributed joins and searching? And so what we went out to do was said, we can't cache, because that's adds time, that adds cost. We have to make cloud object storage high performance, like it feels like a caching SSD. That's where our patents are, that's where our technology is, and we've spent many years working towards this. So, to me, if you can crack that code, a lot of these issues we're talking about, multi-region, multicloud, different services, everybody wants to send their data to the data lake, but then they move it out, we said, "Keep it right there." >> You nailed it, the data gravity. So, Bob's right, the data's coming in, and you need to get the data from everywhere, but you need an environment that you can deal with all that different schema, all the different type of technology, but also at scale. Bob's right, you cannot use memory or SSDs to cache that, that doesn't scale, it doesn't scale cost effectively. But if you could, and what you did, is you made object storage, S3 first, but object storage, the only persistence by doing that. And then we get performance, we should talk about it, it's literally, you know, hundreds of terabytes of queries, and it's done in seconds, it's done without memory caching. We have concepts of caching, but the only caching, the only persistence, is actually when we're doing caching, we're just keeping another side-eye track of things on the S3 itself. So we're using, actually, the object storage to be a database, which is kind of where Bob was saying, we agree, but that's what you started at, people thought you were crazy. >> And maybe make it live. Don't think of it as archival or temporary space, make it live, real time streaming, operational data. What we do is make it smart, we see the data coming in, we uniquely index it such that you can get your use cases, that are search, observability, security, or backend operational. But we don't have to have this, I dunno, static, fixed, siloed type of architecture technologies that were traditionally built prior to Supercloud thinking. >> And you don't have to move everything, essentially, you can do it wherever the data lands, whatever cloud across the globe, you're able to bring it together, you get the cost effectiveness, because the only persistence is the cheapest storage persistent layer you can buy. But the key thing is you cracked the code. >> We had to crack the code, right? That was the key thing. >> That's where the plans are. >> And then once you do that, then everything else gets easier to scale, your architecture, across regions, across cloud. >> Now, it's a general purpose database, as Bob was saying, but we use that database to solve a particular issue, which is around operational data, right? So, we agree with Bob's. >> Interesting. So this brings me to this concept of data, Jimata Gan is one of our speakers, you know, we talk about data fabric, which is a NetApp, originally NetApp concept, Gartner's kind of co-opted it. But so, the basic concept is, data lives everywhere, whether it's an S3 bucket, or a SQL database, or a data lake, it's just a node on the data mesh. So in your view, how does this fit in with Supercloud? Ed, you've said that you've built, essentially, an enabler for that, for the data mesh, I think you're an enabler for the Supercloud-like principles. This is a big, chewy opportunity, and it requires, you know, a team approach. There's got to be an ecosystem, there's not going to be one Supercloud to rule them all, so where does the ecosystem fit into the discussion, and where do you fit into the ecosystem? >> Right, so we agree completely, there's not one Supercloud in effect, but we use Supercloud principles to build our platform, and then, you know, the ecosystem's going to be built on leveraging what everyone else's secret powers are, right? So our power, our superpower, based upon what we built is, we deal with, if you're having any scale, or cost effective scale issues, with data, machine generated data, like business observability or security data, we are your force multiplier, we will take that in singularly, just let it, simply put it in your object storage wherever it sits, and we give you uniformity access to that using OpenAPI access, SQL, or you know, Elasticsearch API. So, that's what we do, that's our superpower. So I'll play it into data mesh, that's a perfect, we are a node on a data mesh, but I'll play it in the soup about how, the ecosystem, we see it kind of playing, and we talked about it in just in the last couple days, how we see this kind of possibly. Short term, our superpowers, we deal with this data that's coming at these environments, people, customers, building out observability or security environments, or vendors that are selling their own Supercloud, I do observability, the Datadogs of the world, dot dot dot, the Splunks of the world, dot dot dot, and security. So what we do is we fit in naturally. What we do is a cost effective scale, just land it anywhere in the world, we deal with ingest, and it's a cost effective, an order of magnitude, or two or three order magnitudes more cost effective. Allows them, their customers are asking them to do the impossible, "Give me fast monitoring alerting. I want it snappy, but I want it to keep two years of data, (laughs) and I want it cost effective." It doesn't work. They're good at the fast monitoring alerting, we're good at the long-term retention. And yet there's some gray area between those two, but one to one is actually cheaper, so we would partner. So the first ecosystem plays, who wants to have the ability to, really, all the data's in those same environments, the security observability players, they can literally, just through API, drag our data into their point to grab. We can make it seamless for customers. Right now, we make it helpful to customers. Your Datadog, we make a button, easy go from Datadog to us for logs, save you money. Same thing with Grafana. But you can also look at ecosystem, those same vendors, it used to be a year ago it was, you know, its all about how can you grow, like it's growth at all costs, now it's about cogs. So literally we can go an environment, you supply what your customer wants, but we can help with cogs. And one-on one in a partnership is better than you trying to build on your own. >> Thomas, you were saying you make the first read fast, so you think about Snowflake. Everybody wants to talk about Snowflake and Databricks. So, Snowflake, great, but you got to get the data in there. All right, so that's, can you help with that problem? >> I mean we want simple in, right? And if you have to have structure in, you're not simple. So the idea that you have a simple in, data lake, schema read type philosophy, but schema right type performance. And so what I wanted to do, what we have done, is have that simple lake, and stream that data real time, and those access points of Search or SQL, to go after whatever business case you need, security observability, warehouse integration. But the key thing is, how do I make that click, click, click answer, and do it quickly? And so what we want to do is, that first read has to be fast. Why? 'Cause then you're going to do all this siloing, layers, complexity. If your first read's not fast, you're at a disadvantage, particularly in cost. And nobody says I want less data, but everyone has to, whether they say we're going to shorten the window, we're going to use AI to choose, but in a security moment, when you don't have that answer, you're in trouble. And that's why we are this service, this Supercloud service, if you will, providing access, well-known search, well-known SQL type access, that if you just have one access point, you're at a disadvantage. >> We actually talked about Snowflake and BigQuery, and a different platform, Data Bricks. That's kind of where we see the phase two of ecosystem. One is easy, the low-hanging fruit is observability and security firms. But the next one is, what we do, our super power is dealing with this messy data that schema is changing like night and day. Pipelines are tough, and it's changing all the time, but you want these things fast, and it's big data around the world. That's the next point, just use us alongside, or inside, one of their platforms, and now we get the best of both worlds. Our superpower is keeping this messy data as a streaming, okay, not a batch thing, allow you to do that. So, that's the second one. And then to be honest, the third one, which plays you to Supercloud, it also plays perfectly in the data mesh, is if you really go to the ultimate thing, what we have done is made object storage, S3, GCS, and blob storage, we made it a database. Put, get, complex query with big joins. You know, so back to your original thing, and Muglia teed it up perfectly, we've done that. Now imagine if that's an ecosystem, who would want that? If it's, again, it's uniform available across all the regions, across all the clouds, and it's right next to where you are building a service, or a client's trying, that's where the ecosystem, I think people are going to use Superclouds for their superpowers. We're really good at this, allows that short term. I think the Snowflakes and the Data Bricks are the medium term, you know? And then I think eventually gets to, hey, listen if you can make object storage fast, you can just go after it with simple SQL queries, or elastic. Who would want that? I think that's where people are going to leverage it. It's not going to be one Supercloud, and we leverage the super clouds. >> Our viewpoint is smart object storage can be programmable, and so we agree with Bob, but we're not saying do it here, do it here. This core, fundamental layer across regions, across clouds, that everyone has? Simple in. Right now, it's hard to get data in for access for analysis. So we said, simply, we'll automate the entire process, give you API access across regions, across clouds. And again, how do you do a distributed join that's fast? How do you do a distributed join that doesn't cost you an arm or a leg? And how do you do it at scale? And that's where we've been focused. >> So prior, the cloud object store was a niche. >> Yeah. >> S3 obviously changed that. How standard is, essentially, object store across the different cloud platforms? Is that a problem for you? Is that an easy thing to solve? >> Well, let's talk about it. I mean we've fundamentally, yeah we've extracted it, but fundamentally, cloud object storage, put, get, and list. That's why it's so scalable, 'cause it doesn't have all these other components. That complexity is where we have moved up, and provide direct analytical API access. So because of its simplicity, and costs, and security, and reliability, it can scale naturally. I mean, really, distributed object storage is easy, it's put-get anywhere, now what we've done is we put a layer of intelligence, you know, call it smart object storage, where access is simple. So whether it's multi-region, do a query across, or multicloud, do a query across, or hunting, searching. >> We've had clients doing Amazon and Google, we have some Azure, but we see Amazon and Google more, and it's a consistent service across all of them. Just literally put your data in the bucket of choice, or folder of choice, click a couple buttons, literally click that to say "that's hot," and after that, it's hot, you can see it. But we're not moving data, the data gravity issue, that's the other. That it's already natively flowing to these pools of object storage across different regions and clouds. We don't move it, we index it right there, we're spinning up stateless compute, back to the Supercloud concept. But now that allows us to do all these other things, right? >> And it's no longer just cheap and deep object storage. Right? >> Yeah, we make it the same, like you have an analytic platform regardless of where you're at, you don't have to worry about that. Yeah, we deal with that, we deal with a stateless compute coming up -- >> And make it programmable. Be able to say, "I want this bucket to provide these answers." Right, that's really the hope, the vision. And the complexity to build the entire stack, and then connect them together, we said, the fabric is cloud storage, we just provide the intelligence on top. >> Let's bring it back to the customers, and one of the things we're exploring in Supercloud too is, you know, is Supercloud a solution looking for a problem? Is a multicloud really a problem? I mean, you hear, you know, a lot of the vendor marketing says, "Oh, it's a disaster, because it's all different across the clouds." And I talked to a lot of customers even as part of Supercloud too, they're like, "Well, I solved that problem by just going mono cloud." Well, but then you're not able to take advantage of a lot of the capabilities and the primitives that, you know, like Google's data, or you like Microsoft's simplicity, their RPA, whatever it is. So what are customers telling you, what are their near term problems that they're trying to solve today, and how are they thinking about the future? >> Listen, it's a real problem. I think it started, I think this is a a mega trend, just like cloud. Just, cloud data, and I always add, analytics, are the mega trends. If you're looking at those, if you're not considering using the Supercloud principles, in other words, leveraging what I have, abstracting it out, and getting the most out of that, and then build value on top, I think you're not going to be able to keep up, In fact, no way you're going to keep up with this data volume. It's a geometric challenge, and you're trying to do linear things. So clients aren't necessarily asking, hey, for Supercloud, but they're really saying, I need to have a better mechanism to simplify this and get value across it, and how do you abstract that out to do that? And that's where they're obviously, our conversations are more amazed what we're able to do, and what they're able to do with our platform, because if you think of what we've done, the S3, or GCS, or object storage, is they can't imagine the ingest, they can't imagine how easy, time to glass, one minute, no matter where it lands in the world, querying this in seconds for hundreds of terabytes squared. People are amazed, but that's kind of, so they're not asking for that, but they are amazed. And then when you start talking on it, if you're an enterprise person, you're building a big cloud data platform, or doing data or analytics, if you're not trying to leverage the public clouds, and somehow leverage all of them, and then build on top, then I think you're missing it. So they might not be asking for it, but they're doing it. >> And they're looking for a lens, you mentioned all these different services, how do I bring those together quickly? You know, our viewpoint, our service, is I have all these streams of data, create a lens where they want to go after it via search, go after via SQL, bring them together instantly, no e-tailing out, no define this table, put into this database. We said, let's have a service that creates a lens across all these streams, and then make those connections. I want to take my CRM with my Google AdWords, and maybe my Salesforce, how do I do analysis? Maybe I want to hunt first, maybe I want to join, maybe I want to add another stream to it. And so our viewpoint is, it's so natural to get into these lake platforms and then provide lenses to get that access. >> And they don't want it separate, they don't want something different here, and different there. They want it basically -- >> So this is our industry, right? If something new comes out, remember virtualization came out, "Oh my God, this is so great, it's going to solve all these problems." And all of a sudden it just got to be this big, more complex thing. Same thing with cloud, you know? It started out with S3, and then EC2, and now hundreds and hundreds of different services. So, it's a complex matter for a lot of people, and this creates problems for customers, especially when you got divisions that are using different clouds, and you're saying that the solution, or a solution for the part of the problem, is to really allow the data to stay in place on S3, use that standard, super simple, but then give it what, Ed, you've called superpower a couple of times, to make it fast, make it inexpensive, and allow you to do that across clouds. >> Yeah, yeah. >> I'll give you guys the last word on that. >> No, listen, I think, we think Supercloud allows you to do a lot more. And for us, data, everyone says more data, more problems, more budget issue, everyone knows more data is better, and we show you how to do it cost effectively at scale. And we couldn't have done it without the design principles of we're leveraging the Supercloud to get capabilities, and because we use super, just the object storage, we're able to get these capabilities of ingest, scale, cost effectiveness, and then we built on top of this. In the end, a database is a data platform that allows you to go after everything distributed, and to get one platform for analytics, no matter where it lands, that's where we think the Supercloud concepts are perfect, that's where our clients are seeing it, and we're kind of excited about it. >> Yeah a third generation database, Supercloud database, however we want to phrase it, and make it simple, but provide the value, and make it instant. >> Guys, thanks so much for coming into the studio today, I really thank you for your support of theCUBE, and theCUBE community, it allows us to provide events like this and free content. I really appreciate it. >> Oh, thank you. >> Thank you. >> All right, this is Dave Vellante for John Furrier in theCUBE community, thanks for being with us today. You're watching Supercloud 2, keep it right there for more thought provoking discussions around the future of cloud and data. (bright music)

(gentle synth music) (music ends) >> Welcome back to Supercloud 2, an open industry collaboration between technologists, consultants, analysts, and of course practitioners to help shape the future of cloud. At this event, one of the key areas we're exploring is the intersection of cloud and data. And how building value on top of hyperscale clouds and across clouds is evolving, a concept of course we call "Supercloud". And we're pleased to welcome our friends from Enterprise Technology research, Erik Bradley and Darren Brabham. Guys, thanks for joining us, great to see you. we love to bring the data into these conversations. >> Thank you for having us, Dave, I appreciate it. >> Yeah, thanks. >> You bet. And so, let me do the setup on what is Supercloud. It's a concept that we've floated, Before re:Invent 2021, based on the idea that cloud infrastructure is becoming ubiquitous, incredibly powerful, but there's a lack of standards across the big three clouds. That creates friction. So we defined over the period of time, you know, better part of a year, a set of essential elements, deployment models for so-called supercloud, which create this common experience for specific cloud services that, of course, again, span multiple clouds and even on-premise data. So Erik, with that as background, I wonder if you could add your general thoughts on the term supercloud, maybe play proxy for the CIO community, 'cause you do these round tables, you talk to these guys all the time, you gather a lot of amazing information from senior IT DMs that compliment your survey. So what are your thoughts on the term and the concept? >> Yeah, sure. I'll even go back to last year when you and I did our predictions panel, right? And we threw it out there. And to your point, you know, there's some haters. Anytime you throw out a new term, "Is it marketing buzz? Is it worth it? Why are you even doing it?" But you know, from my own perspective, and then also speaking to the IT DMs that we interview on a regular basis, this is just a natural evolution. It's something that's inevitable in enterprise tech, right? The internet was not built for what it has become. It was never intended to be the underlying infrastructure of our daily lives and work. The cloud also was not built to be what it's become. But where we're at now is, we have to figure out what the cloud is and what it needs to be to be scalable, resilient, secure, and have the governance wrapped around it. And to me that's what supercloud is. It's a way to define operantly, what the next generation, the continued iteration and evolution of the cloud and what its needs to be. And that's what the supercloud means to me. And what depends, if you want to call it metacloud, supercloud, it doesn't matter. The point is that we're trying to define the next layer, the next future of work, which is inevitable in enterprise tech. Now, from the IT DM perspective, I have two interesting call outs. One is from basically a senior developer IT architecture and DevSecOps who says he uses the term all the time. And the reason he uses the term, is that because multi-cloud has a stigma attached to it, when he is talking to his business executives. (David chuckles) the stigma is because it's complex and it's expensive. So he switched to supercloud to better explain to his business executives and his CFO and his CIO what he's trying to do. And we can get into more later about what it means to him. But the inverse of that, of course, is a good CSO friend of mine for a very large enterprise says the concern with Supercloud is the reduction of complexity. And I'll explain, he believes anything that takes the requirement of specific expertise out of the equation, even a little bit, as a CSO worries him. So as you said, David, always two sides to the coin, but I do believe supercloud is a relevant term, and it is necessary because the cloud is continuing to be defined. >> You know, that's really interesting too, 'cause you know, Darren, we use Snowflake a lot as an example, sort of early supercloud, and you think from a security standpoint, we've always pushed Amazon and, "Are you ever going to kind of abstract the complexity away from all these primitives?" and their position has always been, "Look, if we produce these primitives, and offer these primitives, we we can move as the market moves. When you abstract, then it becomes harder to peel the layers." But Darren, from a data standpoint, like I say, we use Snowflake a lot. I think of like Tim Burners-Lee when Web 2.0 came out, he said, "Well this is what the internet was always supposed to be." So in a way, you know, supercloud is maybe what multi-cloud was supposed to be. But I mean, you think about data sharing, Darren, across clouds, it's always been a challenge. Snowflake always, you know, obviously trying to solve that problem, as are others. But what are your thoughts on the concept? >> Yeah, I think the concept fits, right? It is reflective of, it's a paradigm shift, right? Things, as a pendulum have swung back and forth between needing to piece together a bunch of different tools that have specific unique use cases and they're best in breed in what they do. And then focusing on the duct tape that holds 'em all together and all the engineering complexity and skill, it shifted from that end of the pendulum all the way back to, "Let's streamline this, let's simplify it. Maybe we have budget crunches and we need to consolidate tools or eliminate tools." And so then you kind of see this back and forth over time. And with data and analytics for instance, a lot of organizations were trying to bring the data closer to the business. That's where we saw self-service analytics coming in. And tools like Snowflake, what they did was they helped point to different databases, they helped unify data, and organize it in a single place that was, you know, in a sense neutral, away from a single cloud vendor or a single database, and allowed the business to kind of be more flexible in how it brought stuff together and provided it out to the business units. So Snowflake was an example of one of those times where we pulled back from the granular, multiple points of the spear, back to a simple way to do things. And I think Snowflake has continued to kind of keep that mantle to a degree, and we see other tools trying to do that, but that's all it is. It's a paradigm shift back to this kind of meta abstraction layer that kind of simplifies what is the reality, that you need a complex multi-use case, multi-region way of doing business. And it sort of reflects the reality of that. >> And you know, to me it's a spectrum. As part of Supercloud 2, we're talking to a number of of practitioners, Ionis Pharmaceuticals, US West, we got Walmart. And it's a spectrum, right? In some cases the practitioner's saying, "You know, the way I solve multi-cloud complexity is mono-cloud, I just do one cloud." (laughs) Others like Walmart are saying, "Hey, you know, we actually are building an abstraction layer ourselves, take advantage of it." So my general question to both of you is, is this a concept, is the lack of standards across clouds, you know, really a problem, you know, or is supercloud a solution looking for a problem? Or do you hear from practitioners that "No, this is really an issue, we have to bring together a set of standards to sort of unify our cloud estates." >> Allow me to answer that at a higher level, and then we're going to hand it over to Dr. Brabham because he is a little bit more detailed on the realtime streaming analytics use cases, which I think is where we're going to get to. But to answer that question, it really depends on the size and the complexity of your business. At the very large enterprise, Dave, Yes, a hundred percent. This needs to happen. There is complexity, there is not only complexity in the compute and actually deploying the applications, but the governance and the security around them. But for lower end or, you know, business use cases, and for smaller businesses, it's a little less necessary. You certainly don't need to have all of these. Some of the things that come into mind from the interviews that Darren and I have done are, you know, financial services, if you're doing real-time trading, anything that has real-time data metrics involved in your transactions, is going to be necessary. And another use case that we hear about is in online travel agencies. So I think it is very relevant, the complexity does need to be solved, and I'll allow Darren to explain a little bit more about how that's used from an analytics perspective. >> Yeah, go for it. >> Yeah, exactly. I mean, I think any modern, you know, multinational company that's going to have a footprint in the US and Europe, in China, or works in different areas like manufacturing, where you're probably going to have on-prem instances that will stay on-prem forever, for various performance reasons. You have these complicated governance and security and regulatory issues. So inherently, I think, large multinational companies and or companies that are in certain areas like finance or in, you know, online e-commerce, or things that need real-time data, they inherently are going to have a very complex environment that's going to need to be managed in some kind of cleaner way. You know, they're looking for one door to open, one pane of glass to look at, one thing to do to manage these multi points. And, streaming's a good example of that. I mean, not every organization has a real-time streaming use case, and may not ever, but a lot of organizations do, a lot of industries do. And so there's this need to use, you know, they want to use open-source tools, they want to use Apache Kafka for instance. They want to use different megacloud vendors offerings, like Google Pub/Sub or you know, Amazon Kinesis Firehose. They have all these different pieces they want to use for different use cases at different stages of maturity or proof of concept, you name it. They're going to have to have this complexity. And I think that's why we're seeing this need, to have sort of this supercloud concept, to juggle all this, to wrangle all of it. 'Cause the reality is, it's complex and you have to simplify it somehow. >> Great, thanks you guys. All right, let's bring up the graphic, and take a look. Anybody who follows the breaking analysis, which is co-branded with ETR Cube Insights powered by ETR, knows we like to bring data to the table. ETR does amazing survey work every quarter, 1200 plus 1500 practitioners that that answer a number of questions. The vertical axis here is net score, which is ETR's proprietary methodology, which is a measure of spending momentum, spending velocity. And the horizontal axis here is overlap, but it's the presence pervasiveness, and the dataset, the ends, that table insert on the bottom right shows you how the dots are plotted, the net score and then the ends in the survey. And what we've done is we've plotted a bunch of the so-called supercloud suspects, let's start in the upper right, the cloud platforms. Without these hyperscale clouds, you can't have a supercloud. And as always, Azure and AWS, up and to the right, it's amazing we're talking about, you know, 80 plus billion dollar company in AWS. Azure's business is, if you just look at the IaaS is in the 50 billion range, I mean it's just amazing to me the net scores here. Anything above 40% we consider highly elevated. And you got Azure and you got Snowflake, Databricks, HashiCorp, we'll get to them. And you got AWS, you know, right up there at that size, it's quite amazing. With really big ends as well, you know, 700 plus ends in the survey. So, you know, kind of half the survey actually has these platforms. So my question to you guys is, what are you seeing in terms of cloud adoption within the big three cloud players? I wonder if you could could comment, maybe Erik, you could start. >> Yeah, sure. Now we're talking data, now I'm happy. So yeah, we'll get into some of it. Right now, the January, 2023 TSIS is approaching 1500 survey respondents. One caveat, it's not closed yet, it will close on Friday, but with an end that big we are over statistically significant. We also recently did a cloud survey, and there's a couple of key points on that I want to get into before we get into individual vendors. What we're seeing here, is that annual spend on cloud infrastructure is expected to grow at almost a 70% CAGR over the next three years. The percentage of those workloads for cloud infrastructure are expected to grow over 70% as three years as well. And as you mentioned, Azure and AWS are still dominant. However, we're seeing some share shift spreading around a little bit. Now to get into the individual vendors you mentioned about, yes, Azure is still number one, AWS is number two. What we're seeing, which is incredibly interesting, CloudFlare is number three. It's actually beating GCP. That's the first time we've seen it. What I do want to state, is this is on net score only, which is our measure of spending intentions. When you talk about actual pervasion in the enterprise, it's not even close. But from a spending velocity intention point of view, CloudFlare is now number three above GCP, and even Salesforce is creeping up to be at GCPs level. So what we're seeing here, is a continued domination by Azure and AWS, but some of these other players that maybe might fit into your moniker. And I definitely want to talk about CloudFlare more in a bit, but I'm going to stop there. But what we're seeing is some of these other players that fit into your Supercloud moniker, are starting to creep up, Dave. >> Yeah, I just want to clarify. So as you also know, we track IaaS and PaaS revenue and we try to extract, so AWS reports in its quarterly earnings, you know, they're just IaaS and PaaS, they don't have a SaaS play, a little bit maybe, whereas Microsoft and Google include their applications and so we extract those out and if you do that, AWS is bigger, but in the surveys, you know, customers, they see cloud, SaaS to them as cloud. So that's one of the reasons why you see, you know, Microsoft as larger in pervasion. If you bring up that survey again, Alex, the survey results, you see them further to the right and they have higher spending momentum, which is consistent with what you see in the earnings calls. Now, interesting about CloudFlare because the CEO of CloudFlare actually, and CloudFlare itself uses the term supercloud basically saying, "Hey, we're building a new type of internet." So what are your thoughts? Do you have additional information on CloudFlare, Erik that you want to share? I mean, you've seen them pop up. I mean this is a really interesting company that is pretty forward thinking and vocal about how it's disrupting the industry. >> Sure, we've been tracking 'em for a long time, and even from the disruption of just a traditional CDN where they took down Akamai and what they're doing. But for me, the definition of a true supercloud provider can't just be one instance. You have to have multiple. So it's not just the cloud, it's networking aspect on top of it, it's also security. And to me, CloudFlare is the only one that has all of it. That they actually have the ability to offer all of those things. Whereas you look at some of the other names, they're still piggybacking on the infrastructure or platform as a service of the hyperscalers. CloudFlare does not need to, they actually have the cloud, the networking, and the security all themselves. So to me that lends credibility to their own internal usage of that moniker Supercloud. And also, again, just what we're seeing right here that their net score is now creeping above AGCP really does state it. And then just one real last thing, one of the other things we do in our surveys is we track adoption and replacement reasoning. And when you look at Cloudflare's adoption rate, which is extremely high, it's based on technical capabilities, the breadth of their feature set, it's also based on what we call the ability to avoid stack alignment. So those are again, really supporting reasons that makes CloudFlare a top candidate for your moniker of supercloud. >> And they've also announced an object store (chuckles) and a database. So, you know, that's going to be, it takes a while as you well know, to get database adoption going, but you know, they're ambitious and going for it. All right, let's bring the chart back up, and I want to focus Darren in on the ecosystem now, and really, we've identified Snowflake and Databricks, it's always fun to talk about those guys, and there are a number of other, you know, data platforms out there, but we use those too as really proxies for leaders. We got a bunch of the backup guys, the data protection folks, Rubric, Cohesity, and Veeam. They're sort of in a cluster, although Rubric, you know, ahead of those guys in terms of spending momentum. And then VMware, Tanzu and Red Hat as sort of the cross cloud platform. But I want to focus, Darren, on the data piece of it. We're seeing a lot of activity around data sharing, governed data sharing. Databricks is using Delta Sharing as their sort of place, Snowflakes is sort of this walled garden like the app store. What are your thoughts on, you know, in the context of Supercloud, cross cloud capabilities for the data platforms? >> Yeah, good question. You know, I think Databricks is an interesting player because they sort of have made some interesting moves, with their Data Lakehouse technology. So they're trying to kind of complicate, or not complicate, they're trying to take away the complications of, you know, the downsides of data warehousing and data lakes, and trying to find that middle ground, where you have the benefits of a managed, governed, you know, data warehouse environment, but you have sort of the lower cost, you know, capability of a data lake. And so, you know, Databricks has become really attractive, especially by data scientists, right? We've been tracking them in the AI machine learning sector for quite some time here at ETR, attractive for a data scientist because it looks and acts like a lake, but can have some managed capabilities like a warehouse. So it's kind of the best of both worlds. So in some ways I think you've seen sort of a data science driver for the adoption of Databricks that has now become a little bit more mainstream across the business. Snowflake, maybe the other direction, you know, it's a cloud data warehouse that you know, is starting to expand its capabilities and add on new things like Streamlit is a good example in the analytics space, with apps. So you see these tools starting to branch and creep out a bit, but they offer that sort of neutrality, right? We heard one IT decision maker we recently interviewed that referred to Snowflake and Databricks as the quote unquote Switzerland of what they do. And so there's this desirability from an organization to find these tools that can solve the complex multi-headed use-case of data and analytics, which every business unit needs in different ways. And figure out a way to do that, an elegant way that's governed and centrally managed, that federated kind of best of both worlds that you get by bringing the data close to the business while having a central governed instance. So these tools are incredibly powerful and I think there's only going to be room for growth, for those two especially. I think they're going to expand and do different things and maybe, you know, join forces with others and a lot of the power of what they do well is trying to define these connections and find these partnerships with other vendors, and try to be seen as the nice add-on to your existing environment that plays nicely with everyone. So I think that's where those two tools are going, but they certainly fit this sort of label of, you know, trying to be that supercloud neutral, you know, layer that unites everything. >> Yeah, and if you bring the graphic back up, please, there's obviously big data plays in each of the cloud platforms, you know, Microsoft, big database player, AWS is, you know, 11, 12, 15, data stores. And of course, you know, BigQuery and other, you know, data platforms within Google. But you know, I'm not sure the big cloud guys are going to go hard after so-called supercloud, cross-cloud services. Although, we see Oracle getting in bed with Microsoft and Azure, with a database service that is cross-cloud, certainly Google with Anthos and you know, you never say never with with AWS. I guess what I would say guys, and I'll I'll leave you with this is that, you know, just like all players today are cloud players, I feel like anybody in the business or most companies are going to be so-called supercloud players. In other words, they're going to have a cross-cloud strategy, they're going to try to build connections if they're coming from on-prem like a Dell or an HPE, you know, or Pure or you know, many of these other companies, Cohesity is another one. They're going to try to connect to their on-premise states, of course, and create a consistent experience. It's natural that they're going to have sort of some consistency across clouds. You know, the big question is, what's that spectrum look like? I think on the one hand you're going to have some, you know, maybe some rudimentary, you know, instances of supercloud or maybe they just run on the individual clouds versus where Snowflake and others and even beyond that are trying to go with a single global instance, basically building out what I would think of as their own cloud, and importantly their own ecosystem. I'll give you guys the last thought. Maybe you could each give us, you know, closing thoughts. Maybe Darren, you could start and Erik, you could bring us home on just this entire topic, the future of cloud and data. >> Yeah, I mean I think, you know, two points to make on that is, this question of these, I guess what we'll call legacy on-prem players. These, mega vendors that have been around a long time, have big on-prem footprints and a lot of people have them for that reason. I think it's foolish to assume that a company, especially a large, mature, multinational company that's been around a long time, it's foolish to think that they can just uproot and leave on-premises entirely full scale. There will almost always be an on-prem footprint from any company that was not, you know, natively born in the cloud after 2010, right? I just don't think that's reasonable anytime soon. I think there's some industries that need on-prem, things like, you know, industrial manufacturing and so on. So I don't think on-prem is going away, and I think vendors that are going to, you know, go very cloud forward, very big on the cloud, if they neglect having at least decent connectors to on-prem legacy vendors, they're going to miss out. So I think that's something that these players need to keep in mind is that they continue to reach back to some of these players that have big footprints on-prem, and make sure that those integrations are seamless and work well, or else their customers will always have a multi-cloud or hybrid experience. And then I think a second point here about the future is, you know, we talk about the three big, you know, cloud providers, the Google, Microsoft, AWS as sort of the opposite of, or different from this new supercloud paradigm that's emerging. But I want to kind of point out that, they will always try to make a play to become that and I think, you know, we'll certainly see someone like Microsoft trying to expand their licensing and expand how they play in order to become that super cloud provider for folks. So also don't want to downplay them. I think you're going to see those three big players continue to move, and take over what players like CloudFlare are doing and try to, you know, cut them off before they get too big. So, keep an eye on them as well. >> Great points, I mean, I think you're right, the first point, if you're Dell, HPE, Cisco, IBM, your strategy should be to make your on-premise state as cloud-like as possible and you know, make those differences as minimal as possible. And you know, if you're a customer, then the business case is going to be low for you to move off of that. And I think you're right. I think the cloud guys, if this is a real problem, the cloud guys are going to play in there, and they're going to make some money at it. Erik, bring us home please. >> Yeah, I'm going to revert back to our data and this on the macro side. So to kind of support this concept of a supercloud right now, you know Dave, you and I know, we check overall spending and what we're seeing right now is total year spent is expected to only be 4.6%. We ended 2022 at 5% even though it began at almost eight and a half. So this is clearly declining and in that environment, we're seeing the top two strategies to reduce spend are actually vendor consolidation with 36% of our respondents saying they're actively seeking a way to reduce their number of vendors, and consolidate into one. That's obviously supporting a supercloud type of play. Number two is reducing excess cloud resources. So when I look at both of those combined, with a drop in the overall spending reduction, I think you're on the right thread here, Dave. You know, the overall macro view that we're seeing in the data supports this happening. And if I can real quick, couple of names we did not touch on that I do think deserve to be in this conversation, one is HashiCorp. HashiCorp is the number one player in our infrastructure sector, with a 56% net score. It does multiple things within infrastructure and it is completely agnostic to your environment. And if we're also speaking about something that's just a singular feature, we would look at Rubric for data, backup, storage, recovery. They're not going to offer you your full cloud or your networking of course, but if you are looking for your backup, recovery, and storage Rubric, also number one in that sector with a 53% net score. Two other names that deserve to be in this conversation as we watch it move and evolve. >> Great, thank you for bringing that up. Yeah, we had both of those guys in the chart and I failed to focus in on HashiCorp. And clearly a Supercloud enabler. All right guys, we got to go. Thank you so much for joining us, appreciate it. Let's keep this conversation going. >> Always enjoy talking to you Dave, thanks. >> Yeah, thanks for having us. >> All right, keep it right there for more content from Supercloud 2. This is Dave Valente for John Ferg and the entire Cube team. We'll be right back. (gentle synth music) (music fades)

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

(gentle bright music) >> Okay, welcome back to our "Supercloud 2" event live coverage here at stage performance in Palo Alto syndicating around the world. I'm John Furrier with Dave Vellante. We've got exclusive news and a scoop here for SiliconANGLE and theCUBE. Zhamak Dehghani, creator of data mesh has formed a new company called NextData.com NextData, she's a cube alumni and contributor to our Supercloud initiative, as well as our coverage and breaking analysis with Dave Vellante on data, the killer app for Supercloud. Zhamak, great to see you. Thank you for coming into the studio and congratulations on your newly formed venture and continued success on the data mesh. >> Thank you so much. It's great to be here. Great to see you in person. >> Dave: Yeah, finally. >> John: Wonderful. Your contributions to the data conversation has been well-documented certainly by us and others in the industry. Data mesh taking the world by storm. Some people are debating it, throwing, you know, cold water on it. Some are, I think, it's the next big thing. Tell us about the data mesh super data apps that are emerging out of cloud. >> I mean, data mesh, as you said, it's, you know, the pain point that it surfaced were universal. Everybody said, "Oh, why didn't I think of that?" You know, it was just an obvious next step and people are approaching it, implementing it. I guess the last few years, I've been involved in many of those implementations, and I guess Supercloud is somewhat a prerequisite for it because it's data mesh and building applications using data mesh is about sharing data responsibly across boundaries. And those boundaries include boundaries, organizational boundaries cloud technology boundaries and trust boundaries. >> I want to bring that up because your venture, NextData which is new, just formed. Tell us about that. What wave is that riding? What specifically are you targeting? What's the pain point? >> Zhamak: Absolutely, yes. So next data is the result of, I suppose, the pains that I suffered from implementing a database for many of the organizations. Basically, a lot of organizations that I've worked with, they want decentralized data. So they really embrace this idea of decentralized ownership of the data, but yet they want interconnectivity through standard APIs, yet they want discoverability and governance. So they want to have policies implemented, they want to govern that data, they want to be able to discover that data and yet they want to decentralize it. And we do that with a developer experience that is easy and native to a generalist developer. So we try to find, I guess, the common denominator that solves those problems and enables that developer experience for data sharing. >> John: Since you just announced the news, what's been the reaction? >> Zhamak: I just announced the news right now, so what's the reaction? >> John: But people in the industry that know you, you did a lot of work in the area. What have been some of the feedback on the new venture in terms of the approach, the customers, problem? >> Yeah, so we've been in stealth modes, so we haven't publicly talked about it, but folks that have been close to us in fact have reached out. We already have implementations of our pilot platform with early customers, which is super exciting. And we're going to have multiple of those. Of course, we're a tiny, tiny company. We can have many of those where we are going to have multiple pilots, implementations of our platform in real world. We're real global large scale organizations that have real world problems. So we're not going to build our platform in vacuum. And that's what's happening right now. >> Zhamak: When I think about your role at ThoughtWorks, you had a very wide observation space with a number of clients helping them implement data mesh and other things as well prior to your data mesh initiative. But when I look at data mesh, at least the ones that I've seen, they're very narrow. I think of JPMC, I think of HelloFresh. They're generally obviously not surprising. They don't include the big vision of inclusivity across clouds across different data stores. But it seems like people are having to go through some gymnastics to get to, you know, the organizational reality of decentralizing data, and at least pushing data ownership to the line of business. How are you approaching or are you approaching, solving that problem? Are you taking a narrow slice? What can you tell us about Next Data? >> Zhamak: Sure, yeah, absolutely. Gymnastics, the cute word to describe what the organizations have to go through. And one of those problems is that, you know, the data, as you know, resides on different platforms. It's owned by different people, it's processed by pipelines that who owns them. So there's this very disparate and disconnected set of technologies that were very useful for when we thought about data and processing as a centralized problem. But when you think about data as a decentralized problem, the cost of integration of these technologies in a cohesive developer experience is what's missing. And we want to focus on that cohesive end-to-end developer experience to share data responsibly in this autonomous units, we call them data products, I guess in data mesh, right? That constitutes computation, that governs that data policies, discoverability. So I guess, I heard this expression in the last talks that you can have your cake and eat it too. So we want people have their cakes, which is, you know, data in different places, decentralization and eat it too, which is interconnected access to it. So we start with standardizing and codifying this idea of a data product container that encapsulates data computation, APIs to get to it in a technology agnostic way, in an open way. And then, sit on top and use existing existing tech, you know, Snowflake, Databricks, whatever exists, you know, the millions of dollars of investments that companies have made, sit on top of those but create this cohesive, integrated experience where data product is a first class primitive. And that's really key here, that the language, and the modeling that we use is really native to data mesh is that I will make a data product, I'm sharing a data product, and that encapsulates on providing metadata about this. I'm providing computation that's constantly changing the data. I'm providing the API for that. So we're trying to kind of codify and create a new developer experience based on that. And developer, both from provider side and user side connected to peer-to-peer data sharing with data product as a primitive first class concept. >> Okay, so the idea would be developers would build applications leveraging those data products which are discoverable and governed. Now, today you see some companies, you know, take a snowflake for example. >> Zhamak: Yeah. >> Attempting to do that within their own little walled garden. They even, at one point, used the term, "Mesh." I dunno if they pull back on that. And then they sort of became aware of some of your work. But a lot of the things that they're doing within their little insulated environment, you know, support that, that, you know, governance, they're building out an ecosystem. What's different in your vision? >> Exactly. So we realize that, you know, and this is a reality, like you go to organizations, they have a snowflake and half of the organization happily operates on Snowflake. And on the other half, oh, we are on, you know, bare infrastructure on AWS, or we are on Databricks. This is the realities, you know, this Supercloud that's written up here. It's about working across boundaries of technology. So we try to embrace that. And even for our own technology with the way we're building it, we say, "Okay, nobody's going to use next data mesh operating system. People will have different platforms." So you have to build with openness in mind, and in case of Snowflake, I think, you know, they have I'm sure very happy customers as long as customers can be on Snowflake. But once you cross that boundary of platforms then that becomes a problem. And we try to keep that in mind in our solution. >> So, it's worth reviewing that basically, the concept of data mesh is that, whether you're a data lake or a data warehouse, an S3 bucket, an Oracle database as well, they should be inclusive inside of the data. >> We did a session with AWS on the startup showcase, data as code. And remember, I wrote a blog post in 2007 called, "Data's the new developer kit." Back then, they used to call 'em developer kits, if you remember. And that we said at that time, whoever can code data >> Zhamak: Yes. >> Will have a competitive advantage. >> Aren't there machines going to be doing that? Didn't we just hear that? >> Well we have, and you know, Hey Siri, hey Cube. Find me that best video for data mesh. There it is. I mean, this is the point, like what's happening is that, now, data has to be addressable >> Zhamak: Yes. >> For machines and for coding. >> Zhamak: Yes. >> Because as you need to call the data. So the question is, how do you manage the complexity of big things as promiscuous as possible, making it available as well as then governing it because it's a trade off. The more you make open >> Zhamak: Definitely. >> The better the machine learning. >> Zhamak: Yes. >> But yet, the governance issue, so this is the, you need an OS to handle this maybe. >> Yes, well, we call our mental model for our platform is an OS operating system. Operating systems, you know, have shown us how you can kind of abstract what's complex and take care of, you know, a lot of complexities, but yet provide an open and, you know, dynamic enough interface. So we think about it that way. We try to solve the problem of policies live with the data. An enforcement of the policies happens at the most granular level which is, in this concept, the data product. And that would happen whether you read, write, or access a data product. But we can never imagine what are these policies could be. So our thinking is, okay, we should have a open policy framework that can allow organizations write their own policy drivers, and policy definitions, and encode it and encapsulated in this data product container. But I'm not going to fool myself to say that, you know, that's going to solve the problem that you just described. I think we are in this, I don't know, if I look into my crystal ball, what I think might happen is that right now, the primitives that we work with to train machine-learning model are still bits and bites in data. They're fields, rows, columns, right? And that creates quite a large surface area, an attack area for, you know, for privacy of the data. So perhaps, one of the trends that we might see is this evolution of data APIs to become more and more computational aware to bring the compute to the data to reduce that surface area so you can really leave the control of the data to the sovereign owners of that data, right? So that data product. So I think the evolution of our data APIs perhaps will become more and more computational. So you describe what you want, and the data owner decides, you know, how to manage the- >> John: That's interesting, Dave, 'cause it's almost like we just talked about ChatGPT in the last segment with you, who's a machine learning, could really been around the industry. It's almost as if you're starting to see reason come into the data, reasoning. It's like you starting to see not just metadata, using the data to reason so that you don't have to expose the raw data. It's almost like a, I won't say curation layer, but an intelligence layer. >> Zhamak: Exactly. >> Can you share your vision on that 'cause that seems to be where the dots are connecting. >> Zhamak: Yes, this is perhaps further into the future because just from where we stand, we have to create still that bridge of familiarity between that future and present. So we are still in that bridge-making mode, however, by just the basic notion of saying, "I'm going to put an API in front of my data, and that API today might be as primitive as a level of indirection as in you tell me what you want, tell me who you are, let me go process that, all the policies and lineage, and insert all of this intelligence that need to happen. And then I will, today, I will still give you a file. But by just defining that API and standardizing it, now we have this amazing extension point that we can say, "Well, the next revision of this API, you not just tell me who you are, but you actually tell me what intelligence you're after. What's a logic that I need to go and now compute on your API?" And you can kind of evolve that, right? Now you have a point of evolution to this very futuristic, I guess, future where you just describe the question that you're asking from the chat. >> Well, this is the Supercloud, Dave. >> I have a question from a fan, I got to get it in. It's George Gilbert. And so, his question is, you're blowing away the way we synchronize data from operational systems to the data stack to applications. So the concern that he has, and he wants your feedback on this, "Is the data product app devs get exposed to more complexity with respect to moving data between data products or maybe it's attributes between data products, how do you respond to that? How do you see, is that a problem or is that something that is overstated, or do you have an answer for that?" >> Zhamak: Absolutely. So I think there's a sweet spot in getting data developers, data product developers closer to the app, but yet not burdening them with the complexity of the application and application logic, and yet reducing their cognitive load by localizing what they need to know about which is that domain where they're operating within. Because what's happening right now? what's happening right now is that data engineers, a ton of empathy for them for their high threshold of pain that they can, you know, deal with, they have been centralized, they've put into the data team, and they have been given this unbelievable task of make meaning out of data, put semantic over it, curates it, cleans it, and so on. So what we are saying is that get those folks embedded into the domain closer to the application developers, these are still separately moving units. Your app and your data products are independent but yet tightly closed with each other, tightly coupled with each other based on the context of the domain, so reduce cognitive load by localizing what they need to know about to the domain, get them closer to the application but yet have them them separate from app because app provides a very different service. Transactional data for my e-commerce transaction, data product provides a very different service, longitudinal data for the, you know, variety of this intelligent analysis that I can do on the data. But yet, it's all within the domain of e-commerce or sales or whatnot. >> So a lot of decoupling and coupling create that cohesiveness. >> Zhamak: Absolutely. >> Architecture. So I have to ask you, this is an interesting question 'cause it came up on theCUBE all last year. Back on the old server, data center days and cloud, SRE, Google coined the term, "Site Reliability Engineer" for someone to look over the hundreds of thousands of servers. We asked a question to data engineering community who have been suffering, by the way, agree. Is there an SRE-like role for data? Because in a way, data engineering, that platform engineer, they are like the SRE for data. In other words, managing the large scale to enable automation and cell service. What's your thoughts and reaction to that? >> Zhamak: Yes, exactly. So, maybe we go through that history of how SRE came to be. So we had the first DevOps movement which was, remove the wall between dev and ops and bring them together. So you have one cross-functional units of the organization that's responsible for, you build it you run it, right? So then there is no, I'm going to just shoot my application over the wall for somebody else to manage it. So we did that, and then we said, "Okay, as we decentralized and had this many microservices running around, we had to create a layer that abstracted a lot of the complexity around running now a lot or monitoring, observing and running a lot while giving autonomy to this cross-functional team." And that's where the SRE, a new generation of engineers came to exist. So I think if I just look- >> Hence Borg, hence Kubernetes. >> Hence, hence, exactly. Hence chaos engineering, hence embracing the complexity and messiness, right? And putting engineering discipline to embrace that and yet give a cohesive and high integrity experience of those systems. So I think, if we look at that evolution, perhaps something like that is happening by bringing data and apps closer and make them these domain-oriented data product teams or domain oriented cross-functional teams, full stop, and still have a very advanced maybe at the platform infrastructure level kind of operational team that they're not busy doing two jobs which is taking care of domains and the infrastructure, but they're building infrastructure that is embracing that complexity, interconnectivity of this data process. >> John: So you see similarities. >> Absolutely, but I feel like we're probably in a more early days of that movement. >> So it's a data DevOps kind of thing happening where scales happening. It's good things are happening yet. Eh, a little bit fast and loose with some complexities to clean up. >> Yes, yes. This is a different restructure. As you said we, you know, the job of this industry as a whole on architects is decompose, recompose, decompose, recomposing a new way, and now we're like decomposing centralized team, recomposing them as domains and- >> John: So is data mesh the killer app for Supercloud? >> You had to do this for me. >> Dave: Sorry, I couldn't- (John and Dave laughing) >> Zhamak: What do you want me to say, Dave? >> John: Yes. >> Zhamak: Yes of course. >> I mean Supercloud, I think it's, really the terminology's Supercloud, Opencloud. But I think, in spirits of it, this embracing of diversity and giving autonomy for people to make decisions for what's right for them and not yet lock them in. I think just embracing that is baked into how data mesh assume the world would work. >> John: Well thank you so much for coming on Supercloud too, really appreciate it. Data has driven this conversation. Your success of data mesh has really opened up the conversation and exposed the slow moving data industry. >> Dave: Been a great catalyst. (John laughs) >> John: That's now going well. We can move faster, so thanks for coming on. >> Thank you for hosting me. It was wonderful. >> Okay, Supercloud 2 live here in Palo Alto. Our stage performance, I'm John Furrier with Dave Vellante. We're back with more after this short break, Stay with us all day for Supercloud 2. (gentle bright music)

(intro music plays) >> Okay, welcome back to Supercloud 2. I'm John Furrier with my co-host, Dave Vellante, here in our Palo Alto Studio, with a live performance all day unpacking the wave of Supercloud. This is our second edition. Back for keynote review here is Vittorio Viarengo, talking about the hype and the reality of the Supercloud momentum. Vittorio, great to see you. You got a presentation. Looking forward to hearing the update. >> It's always great to be here on this stage with you guys. >> John Furrier: (chuckles) So the business imperative for cloud right now is clear and the Supercloud wave points to the builders and they want to break through. VMware, you guys have a lot of builders in the ecosystem. Where do you guys see multicloud today? What's going on? >> So, what we see is, when we talk with our customers is that customers are in a state of cloud chaos. Raghu Raghuram, our CEO, introduced this term at our user conference and it really resonated with our customers. And the chaos comes from the fact that most enterprises have applications spread across private cloud, multiple hyperscalers, and the edge increasingly. And so with that, every hyperscaler brings their own vertical integrated stack of infrastructure development, platform security, and so on and so forth. And so our customers are left with a ballooning cost because they have to train their employees across multiple stacks. And the costs are only going up. >> John Furrier: Have you talked about the Supercloud with your customers? What are they looking for when they look at the business value of Cross-Cloud Services? Why are they digging into it? What are some of the reasons? >> First of all, let's put this in perspective. 90, 87% of customers use two or more cloud including the private cloud. And 55%, get this, 55% use three or more clouds, right? And so, when you talk to these customers they're all asking for two things. One, they find that managing the multicloud is more difficult than the private cloud. And that goes without saying because it's new, they don't have the skills, and they have many of these. And pretty much everybody, 87% of them, are seeing their cost getting out of control. And so they need a new approach. We believe that the industry needs a new approach to solving the multicloud problem, which you guys have introduced and you call it the Supercloud. We call it Cross-Cloud Services. But the idea is that- and the parallel goes back to the private cloud. In the private cloud, if you remember the old days, before we called it the private cloud, we would install SAP. And the CIO would go, "Oh, I hear SAP works great on HP hardware. Oh, let's buy the HP stack", right? (hosts laugh) And then you go, "Oh, oh, Oracle databases. They run phenomenally on Sun Stack." That's another stack. And it wasn't sustainable, right? And so, VMware came in with virtualization and made everything look the same. And we unleashed a tremendous era of growth and speed and cost saving for our customers. So we believe, and I think the industry also believes, if you look at the success of Supercloud, first instance and today, that we need to create a new level of abstraction in the cloud. And this abstraction needs to be at a higher level. It needs to be built around the lingua franca of the cloud, which is Kubernetes, APIs, open source stacks. And by doing so, we're going to allow our customers to have a more unified way of building, managing, running, connecting, and securing applications across cloud. >> So where should that standardization occur? 'Cause we're going to hear from some customers today. When I ask them about cloud chaos, they're like, "Well, the way we deal with cloud chaos is MonoCloud". They sort of put on the blinders, right? But of course, they may be risking not being able to take advantage of best-of-breed. So where should that standardization layer occur across clouds? >> [Vittorio Viarengo] Well, I also hear that from some customers. "Oh, we are one cloud". They are in denial. There's no question about it. In fact, when I met at our user conference with a number of CIOs, and I went around the room and I asked them, I saw the entire spectrum. (laughs) The person is in denial. "Oh, we're using AWS." I said, "Great." "And the private cloud, so we're all set." "Okay, thank you. Next." "Oh, the business units are using AWS." "Ah, okay. So you have three." "Oh, and we just bought a company that is using Google back in Europe." So, okay, so you got four right there. So that person in denial. Then, you have the second category of customers that are seeing the problem, they're ahead of the pack, and they're building their solution. We're going to hear from Walmart later today. >> Dave Vellante: Yeah. >> So they're building their own. Not everybody has the skills and the scale of Walmart to build their own. >> Dave Vellante: Right. >> So, eventually, then you get to the third category of customers. They're actually buying solutions from one of the many ISVs that you are going to talk with today. You know, whether it is Azure Corp or Snowflake or all this. I will argue, any new company, any new ISV, is by definition a multicloud service company, right? And so these people... Or they're buying our Cross-Cloud Services to solve this problem. So that's the spectrum of customers out there. >> What's the stack you're focusing on specifically? What is VMware? Because virtualization is not going away. You're seeing a lot more in the cloud with networking, for example, this abstraction layer. What specifically are you guys focusing on? >> [Vittorio Viarengo] So, I like to talk about this beyond what VMware does, just 'cause I think this is an industry movement. A market is forming around multicloud services. And so it's an approach that pretty much a whole industry is taking of building this abstraction layer. In our approach, it is to bring these services together to simplify things even further. So, initially, we were the first to see multicloud happening. You know, Raghu and Sanjay, back in what, like 2016, 17, saw this coming and our first foray in multicloud was to take this sphere and our hypervisor and port it natively on all the hyperscaling, which is a phenomenal solution to get your enterprise application in the cloud and modernize them. But then we realized that customers were already in the cloud natively. And so we had to have (all chuckle) a religion discussion internally and drop that hypervisor religion and say, "Hey, we need to go and help our customers where they are, in a native cloud". And that's where we brought back Pivotal. We built tons around it. We shifted. And then Aria. And so basically, our evolution was to go from, you know, our hypervisor to cloud native. And then eventually we ended up at what we believe is the most comprehensive multicloud services solution that covers Application Development with Tanzu, Management with Aria, and then you have NSX for security and user computing for connectivity. And so we believe that we have the most comprehensive set of integrated services to solve the challenges of multicloud, bringing excess simplicity into the picture. >> John Furrier: As some would say, multicloud and multi environment, when you get to the distributed computing with the edge, you're going to need that capability. And you guys have been very successful with private cloud. But to be devil's advocate, you guys have been great with private cloud, but some are saying like, you guys don't get public cloud yet. How do you answer that? Because there's a lot of work that you guys have done in public cloud and it seems like private cloud successes are moving up into public cloud. Like networking. You're seeing a lot of that being configured in. So the enterprise-grade solutions are moving into the cloud. So what would you say to the skeptics out there that say, "Oh, I think you got private cloud nailed down, but you don't really have public cloud." (chuckles) >> [Vittorio Viarengo] First of all, we love skeptics. Our engineering team love skeptics and love to prove them wrong. (John laughs) And I would never ever bet against our engineering team. So I believe that VMware has been so successful in building a private cloud and the technology that actually became the foundation for the public cloud. But that is always hard, to be known in a new environment, right? There's always that period where you have to prove yourself. But what I love about VMware is that VMware has what I believe, what I like to call "enterprise pragmatism". The private cloud is not going away. So we're going to help our customers there, and then, as they move to the cloud, we are going to give them an option to adopt the cloud at their own pace, with VMware cloud, to allow them to move to the cloud and be able to rely on the enterprise-class capabilities we built on-prem in the cloud. But then with Tanzu and Aria and the rest of the Cross-Cloud Service portfolio, being able to meet them where they are. If they're already in the cloud, have them have a single place to build application, a single place to manage application, and so on and so forth. >> John Furrier: You know, Dave, we were talking in the opening. Vittorio, I want to get your reaction to this because we were saying in the opening that the market's obviously pushing this next gen. You see ChatGPT and the success of these new apps that are coming out. The business models are demanding kind of a digital transformation. The tech, the builders, are out there, and you guys have a interesting view because your customer base is almost the canary in the coal mine because this is an Operations challenge as well as just enabling the cloud native. So, I want to get your thoughts on, you know, your customer base, VMware customers. They've been in IT Ops for generations. And now, as that crowd moves and sees this Supercloud environment, it's IT again, but it's everywhere. It's not just IT in a data center. It's on-premises, it's cloud, it's edge. So, almost, your customer base is like a canary in the coal mine for this movement of how do you operationalize multiple environments? Which includes clouds, which includes apps. I mean, this is the core question. >> [Vittorio Viarengo] Yeah. And I want to make this an industry conversation. Forget about VMware for a second. We believe that there are like four or five major pillars that you need to implement to create this level of abstraction. It starts from observability. If you don't know- You need to know where your apps are, where your data is, how the the applications are performing, what is the security posture, what is their performance? So then, you can do something about it. We call that the observability part of this, creating this abstraction. The second one is security. So you need to be- Sorry. Infrastructure. An infrastructure. Creating an abstraction layer for infrastructure means to be able to give the applications, and the developer who builds application, the right infrastructure for the application at the right time. Whether it is a VM, whether it's a Kubernetes cluster, or whether it's microservices, and so on and so forth. And so, that allows our developers to think about infrastructure just as code. If it is available, whatever application needs, whatever the cost makes sense for my application, right? The third part of security, and I can give you a very, very simple example. Say that I was talking to a CIO of a major insurance company in Europe and he is saying to me, "The developers went wild, built all these great front office applications. Now the business is coming to me and says, 'What is my compliance report?'" And the guy is saying, "Say that I want to implement the policy that says, 'I want to encrypt all my data no matter where it resides.' How does it do it? It needs to have somebody logging in into Amazon and configure it, then go to Google, configure it, go to the private cloud." That's time and cost, right? >> Yeah. >> So, you need to have a way to enforce security policy from the infrastructure to the app to the firewall in one place and distribute it across. And finally, the developer experience, right? Developers, developers, developers. (all laugh) We're always trying to keep up with... >> Host: You can dance if you want to do... >> [Vittorio Viarengo] Yeah, let's not make a fool of ourselves. More than usual. Developers are the kings and queens of the hill. They are. Why? Because they build the application. They're making us money and saving us money. And so we need- And right now, they have to go into these different stacks. So, you need to give developers two things. One, a common development experience across this different Kubernetes distribution. And two, a way for the operators. To your point. The operators have fallen behind the developers. And they cannot go to the developer there and tell them, "This is how you're going to do things." They have to see how they're doing things and figure out how to bring the gallery underneath so that developers can be developers, but the operators can lay down the tracks and the infrastructure there is secure and compliant. >> Dave Vellante: So two big inferences from that. One is self-serve infrastructure. You got- In a decentralized cloud, a Supercloud world, you got to have self-serve infrastructure, you got to be simple. And the second is governance. You mentioned security, but it's also governance. You know, data sovereignty as we talked about. So the question I have, Vittorio, is where does the customer start? >> [Vittorio Viarengo] So I, it always depends on the business need, but to me, the foundational layer is observability. If you don't know where your staff is, you cannot manage, you cannot secure it, you cannot manage its cost, right? So I think observability is the bar to entry. And then it depends on the business needs, right? So, we go back to the CIO that I talked to. He is clearly struggling with compliance and security. >> Hosts: Mm hmm. >> And so, like many customers. And so, that's maybe where they start. There are other customers that are a little behind the head of the pack in terms of building applications, right? And so they're looking at these, you know, innovative companies that have the developers that get the cloud and build all these application. They are leader in the industry. They're saying, "How do I get some of that?" Well, the way you get some of that is by adopting modern application development and platform operational capabilities. So, that's maybe, that's where they should start. And so on and so forth. It really depends on the business. To me, observability is the foundational part of this. >> John Furrier: Vittorio, we've been on this conversation with you for over a year and a half now with Supercloud. You've been a leader in seeing the wave, you and Raghu and the team at VMware, among other industry leaders. This is our second event. If you're- In the minute and a half that we have left, when you get asked, "what is this Supercloud multicloud Cross-Cloud thing? What's it mean?" I mean, I mentioned earlier, the market, the business models are changing, tech's changing, society needs more economic value out of the cloud. Builders are out there. If someone says, "Hey, Vittorio, what's the bottom line? What's really going on? Why should I pay attention to this wave? What's going on?" How would you describe the relevance of Supercloud? >> I think that this industry is full of smart vendors and smart customers. And if we are smart about it, we look at the history of IT and the history of IT repeats itself over and over again. You follow the- He said, "Follow the money." I say, "Follow the developers." That's how I made my career. I follow great developers. I look at, you know, Kit Colbert. I say, "Okay. I'm going to get behind that guy wherever he is going." And I try to add value to that person. I look at Raghu and all the great engineers that I was blessed to work with. And so the engineers go and explore new territories and then the rest of the stacks moves around. The developers have gone multicloud. And just like in any iteration of IT, at some point, the way you get the right scales at the right cost is with abstractions. And you can see it everywhere from, you know, bits and bytes, integration, to SOA, to APIs and microservices. You can see it now from best-of-breed hyperscaler across multiple clouds to creating an abstraction layer, a Supercloud, that creates a unified way of building, managing, running, securing, and accessing applications. So if you're a customer- (laughs) A minute and a half. (hosts chuckle) If you are customers that are out there and feeling the pain, you got to adopt this. If you are customers that is behind and saying, "Maybe you're in denial" look at the customers that are solving the problems today, and we're going to have some today. See what they're doing and learn from them so you don't make the same mistakes and you can get there ahead of it. >> Dave Vellante: Gracely's Law, John. Brian Gracely. That history repeats itself and- >> John Furrier: And I think one of these, "follow the developers" is interesting. And the other big wave, I want to get your comment real quick, is that developers aren't just application developers. They're network developers. The stack has completely been software-enabled so that you have software-defined networking, you have all kinds of software at all aspects of observability, infrastructure, security. The developers are everywhere. It's not just software. Software is everywhere. >> [Vittorio Viarengo] Yeah. Developers, developers, developers. The other thing that we can tell, I can tell, and we know, because we live in Silicon Valley. We worship developers but if you are out there in manufacturing, healthcare... If you have developers that understand this stuff, pamper them, keep them happy. (hosts laugh) If you don't have them, figure out where they hang out and go recruit them because developers indeed make the IT world go round. >> John Furrier: Vittorio, thank you for coming on with that opening keynote here for Supercloud 2. We're going to unpack what Supercloud is all about in our second edition of our live performance here in Palo Alto. Virtual event. We're going to talk to customers, experts, leaders, investors, everyone who's looking at the future, what's being enabled by this new big wave coming on called Supercloud. I'm John Furrier with Dave Vellante. We'll be right back after this short break. (ambient theme music plays)

(upbeat music) >> Welcome back everyone to Supercloud 2, live here in Palo Alto, our studio, where we're doing a live stage performance and virtually syndicating out around the world. I'm John Furrier with Dave Vellante, my co-host with the The Cube here. We've got Kit Colbert, the CTO of VM. We're doing a keynote on Cloud Chaos, the evolution of SuperCloud Architecture Kit. Great to see you, thanks for coming on. >> Yeah, thanks for having me back. It's great to be here for Supercloud 2. >> And so we're going to dig into it. We're going to do a Q&A. We're going to let you present. You got some slides. I really want to get this out there, it's really compelling story. Do the presentation and then we'll come back and discuss. Take it away. >> Yeah, well thank you. So, we had a great time at the original Supercloud event, since then, been talking to a lot of customers, and started to better formulate some of the thinking that we talked about last time So, let's jump into it. Just a few quick slides to sort of set the tone here. So, if we go to the the next slide, what that shows is the journey that we see customers on today, going from what we call Cloud First into this phase that many customers are stuck in, called Cloud Chaos, and where they want to get to, and this is the term customers actually use, we didn't make this up, we heard it from customers. This notion of Cloud Smart, right? How do they use cloud more effectively, more intelligently? Now, if you walk through this journey, customers start with Cloud First. They usually select a single cloud that they're going to standardize on, and when they do that, they have to build out a whole bunch of functionality around that cloud. Things you can see there on the screen, disaster recovery, security, how do they monitor it or govern it? Like, these are things that are non-negotiable, you've got to figure it out, and typically what they do is, they leverage solutions that are specific for that cloud, and that's fine when you have just one cloud. But if we build out here, what we see is that most customers are using more than just one, they're actually using multiple, not necessarily 10 or however many on the screen, but this is just as an example. And so what happens is, they have to essentially duplicate or replicate that stack they've built for each different cloud, and they do so in a kind of a siloed manner. This results in the Cloud Chaos term that that we talked about before. And this is where most businesses out there are, they're using two, maybe three public clouds. They've got some stuff on-prem and they've also got some stuff out at the edge. This is apps, data, et cetera. So, this is the situation, this is sort of that Cloud Chaos. So, the question is, how do we move from this phase to Cloud Smart? And this is where the architecture comes in. This is why architecture, I think, is so important. It's really about moving away from these single cloud services that just solve a problem for one cloud, to something we call a Cross-Cloud service. Something that can support a set of functionality across all clouds, and that means not just public clouds, but also private clouds, edge, et cetera, and when you evolve that across the board, what you get is this sort of Supercloud. This notion that we're talking about here, where you combine these cross-cloud services in many different categories. You can see some examples there on the screen. This is not meant to be a complete set of things, but just examples of what can be done. So, this is sort of the transition and transformation that we're talking about here, and I think the architecture piece comes in both for the individual cloud services as well as that Supercloud concept of how all those services come together. >> Great presentation., thanks for sharing. If you could pop back to that slide, on the Cloud Chaos one. I just want to get your thoughts on something there. This is like the layout of the stack. So, this slide here that I'm showing on the screen, that you presented, okay, take us through that complexity. This is the one where I wanted though, that looks like a spaghetti code mix. >> Yes. >> So, do you turn this into a Supercloud stack, right? Is that? >> well, I think it's, it's an evolving state that like, let's take one of these examples, like security. So, instead of implementing security individually in different ways, using different technologies, different tooling for each cloud, what you would do is say, "Hey, I want a single security solution that works across all clouds", right? A concrete example of this would be secure software supply chain. This is probably one of the top ones that I hear when I talk to customers. How do I know that the software I'm building is truly what I expect it to be, and not something that some hacker has gotten into, and polluted with malicious code? And what they do is that, typically today, their teams have gone off and created individual secure software supply chain solutions for each cloud. So, now they could say, "Hey, I can take a single implementation and just have different endpoints." It could go to Google, or AWS, or on-prem, or wherever have you, right? So, that's the sort of architectural evolution that we're talking about. >> You know, one of the things we hear, Dave, you've been on theCUBE all the time, and we, when we talk privately with customers who are asking us like, what's, what's going on? They have the same complaint, "I don't want to build a team, a dev team, for that stack." So, if you go back to that slide again, you'll see that, that illustrates the tech stack for the clouds and the clouds at the bottom. So, the number one complaint we hear, and I want to get your reaction to that, "I don't want to have a team to have to work on that. So, I'm going to pick one and then have a hedge secondary one, as a backup." Here, that's one, that's four, five, eight, ten, ten environments. >> Yeah, I got a lot. >> That's going to be the reality, so, what's the technical answer to that? >> Yeah, well first of all, let me just say, this picture is again not totally representative of reality oftentimes, because while that picture shows a solution for every cloud, oftentimes that's not the case. Oftentimes it's a line of business going off, starting to use a new cloud. They might solve one or two things, but usually not security, usually not some of these other things, right? So, I think from a technical standpoint, where you want to get to is, yes, that sort of common service, with a common operational team behind it, that is trained on that, that can work across clouds. And that's really I think the important evolution here, is that you don't need to replicate these operational teams, one for each cloud. You can actually have them more focused across all those clouds. >> Yeah, in fact, we were commenting on the opening today. Dave and I were talking about the benefits of the cloud. It's heterogeneous, which is a good thing, but it's complex. There's skill gaps and skill required, but at the end of the day, self-service of the cloud, and the elastic nature of it makes it the benefit. So, if you try to create too many common services, you lose the value of the cloud. So, what's the trade off, in your mind right now as customers start to look at okay, identity, maybe I'll have one single sign on, that's an obvious one. Other ones? What are the areas people are looking at from a combination, common set of services? Where do they start? What's the choices? What are some of the trade offs? 'Cause you can't do it everything. >> No, it's a great question. So, that's actually a really good point and as I answer your question, before I answer your question, the important point about that, as you saw here, you know, across cloud services or these set of Cross-Cloud services, the things that comprise the Supercloud, at least in my view, the point is not necessarily to completely abstract the underlying cloud. The point is to give a business optionality and choice, in terms of what it wants to abstract, and I think that gets to your question, is how much do you actually want to abstract from the underlying cloud? Now, what I find, is that typically speaking, cloud choice is driven at least from a developer or app team perspective, by the best of breed services. What higher level application type services do you need? A database or AI, you know, ML systems, for your application, and that's going to drive your choice of the cloud. So oftentimes, businesses I talk to, want to allow those services to shine through, but for other things that are not necessarily highly differentiated and yet are absolutely critical to creating a successful application, those are things that you want to standardize. Again, like things like security, the supply chain piece, cost management, like these things you need to, and you know, things like cogs become really, really important when you start operating at scale. So, those are the things in it that I see people wanting to focus on. >> So, there's a majority model. >> Yes. >> All right, and we heard of earlier from Walmart, who's fairly, you know, advanced, but at the same time their supercloud is pretty immature. So, what are you seeing in terms of supercloud momentum, crosscloud momentum? What's the starting point for customers? >> Yeah, so it's interesting, right, on that that three-tiered journey that I talked about, this Cloud Smart notion is, that is adoption of what you might call a supercloud or architecture, and most folks aren't there yet. Even the really advanced ones, even the really large ones, and I think it's because of the fact that, we as an industry are still figuring this out. We as an industry did not realize this sort of Cloud Chaos state could happen, right? We didn't, I think most folks thought they could standardize on one cloud and that'd be it, but as time has shown, that's simply not the case. As much as one might try to do that, that's not where you end up. So, I think there's two, there's two things here. Number one, for folks that are early in to the cloud, and are in this Cloud Chaos phase, we see the path out through standardization of these cross-cloud services through adoption of this sort of supercloud architecture, but the other thing I think is particularly exciting, 'cause I talked to a number of of businesses who are not yet in the Cloud Chaos phase. They're earlier on in the cloud journey, and I think the opportunity there is that they don't have to go through Cloud Chaos. They can actually skip that whole phase if they adopt this supercloud architecture from the beginning, and I think being thoughtful around that is really the key here. >> It's interesting, 'cause we're going to hear from Ionis Pharmaceuticals later, and they, yes there are multiple clouds, but the multiple clouds are largely separate, and so it's a business unit using that. So, they're not in Cloud Chaos, but they're not tapping the advantages that you could get for best of breed across those business units. So, to your point, they have an opportunity to actually build that architecture or take advantage of those cross-cloud services, prior to reaching cloud chaos. >> Well, I, actually, you know, I'd love to hear from them if, 'cause you say they're not in Cloud Chaos, but are they, I mean oftentimes I find that each BU, each line of business may feel like they're fine, in of themselves. >> Yes, exactly right, yes. >> But when you look at it from an overall company perspective, they're like, okay, things are pretty chaotic here. We don't have standardization, I don't, you know, like, again, security compliance, these things, especially in many regulated industries, become huge problems when you're trying to run applications across multiple clouds, but you don't have any of those company-wide standardizations. >> Well, this is a point. So, they have a big deal with AstraZeneca, who's got this huge ecosystem, they want to start sharing data across those ecosystem, and that's when they will, you know, that Cloud Chaos will, you know, come, come to fore, you would think. I want to get your take on something that Bob Muglia said earlier, which is, he kind of said, "Hey Dave, you guys got to tighten up your definition a little bit." So, he said a supercloud is a platform that provides programmatically consistent services hosted on heterogeneous cloud providers. So, you know, thank you, that was nice and simple. However others in the community, we're going to hear from Dr. Nelu Mihai later, says, no, no, wait a minute, it's got to be an architecture, not a platform. Where do you land on this architecture v. platform thing? >> I look at it as, I dunno if it's, you call it maturity or just kind of a time horizon thing, but for me when I hear the word platform, I typically think of a single vendor. A single vendor provides this platform. That's kind of the beauty of a platform, is that there is a simplicity usually consistency to it. >> They did the architecture. (laughing) >> Yeah, exactly but I mean, well, there's obviously architecture behind it, has to be, but you as a customer don't necessarily need to deal with that. Now, I think one of the opportunities with Supercloud is that it's not going to be, or there is no single vendor that can solve all these problems. It's got to be the industry coming together as a community, inter-operating, working together, and so, that's why, for me, I think about it as an architecture, that there's got to be these sort of, well-defined categories of functionality. There's got to be well-defined interfaces between those categories of functionality to enable modularity, to enable businesses to be able to pick and choose the right sorts of services, and then weave those together into an overall supercloud. >> Okay, so you're not pitching, necessarily the platform, you're saying, hey, we have an architecture that's open. I go back to something that Vittorio said on August 9th, with the first Supercloud, because as well, remember we talked about abstracting, but at the same time giving developers access to those primitives. So he said, and this, I think your answer sort of confirms this. "I want to have my cake eat it too and not gain weight." >> (laughing) Right. Well and I think that's where the platform aspect can eventually come, after we've gotten aligned architecture, you're going to start to naturally see some vendors step up to take on some of the remaining complexity there. So, I do see platforms eventually emerging here, but I think where we have to start as an industry is around aligning, okay, what does this definition mean? What does that architecture look like? How do we enable interoperability? And then we can take the next step. >> Because it depends too, 'cause I would say Snowflake has a platform, and they've just defined the architecture, but we're not talking about infrastructure here, obviously, we're talking about something else. >> Well, I think that the Snowflake talks about, what he talks about, security and data, you're going to start to see the early movement around areas that are very spanning oriented, and I think that's the beginning of the trend and I think there's going to be a lot more, I think on the infrastructure side. And to your point about the platform architecture, that's actually a really good thought exercise because it actually makes you think about what you're designing in the first place, and that's why I want to get your reaction. >> Quote from- >> Well I just have to interrupt since, later on, you're going to hear from near Nir Zuk of Palo Alto Network. He says architecture and security historically, they don't go hand in hand, 'cause it's a big mess. >> It depends if you're whacking the mole or you actually proactively building something. Well Kit, I want to get your reaction from a quote from someone in our community who said about Supercloud, you know, "The Supercloud's great, there are issues around computer science rigors, and customer requirements." So, there's some issues around the science itself as well as not just listen to the customer, 'cause if that's the case, we'd have a better database, a better Oracle, right, so, but there's other, this tech involved, new tech. We need an open architecture with universal data modeling interconnecting among them, connectivity is a part of security, and then, once we get through that gate, figuring out the technical, the data, and the customer requirements, they say "Supercloud should be a loosely coupled platform with open architecture, plug and play, specialized services, ready for optimization, automation that can stand the test of time." What's your reaction to that sentiment? You like it, is that, does that sound good? >> Yeah, no, broadly aligns with my thinking, I think, and what I see from talking with customers as well. I mean, I like the, again, the, you know, listening to customer needs, prioritizing those things, focusing on some of the connective tissue networking, and data and some of these aspects talking about the open architecture, the interoperability, those are all things I think are absolutely critical. And then, yeah, like I think at the end. >> On the computer science side, do you see some science and engineering things that need to be engineered differently? We heard databases are radically going to change and that are inadequate for the new architecture. What are some of the things like that, from a science standpoint? >> Yeah, yeah, yeah. Some of the more academic research type things. >> More tech, or more better tech or is it? >> Yeah, look, absolutely. I mean I think that there's a bunch around, certainly around the data piece, around, you know, there's issues of data gravity, data mobility. How do you want to do that in a way that's performant? There's definitely issues around security as well. Like how do you enable like trust in these environments, there's got to be some sort of hardware rooted trusts, and you know, a whole bunch of various types of aspects there. >> So, a lot of work still be done. >> Yes, I think so. And that's why I look at this as, this is not a one year thing, or you know, it's going to be multi-years, and I think again, it's about all of us in the industry working together to come to an aligned picture of what that looks like. >> So, as the world's moved from private cloud to public cloud and now Cross-cloud services, supercloud, metacloud, whatever you want to call it, how have you sort of changed the way engineering's organized, developers sort of approached the problem? Has it changed and how? >> Yeah, absolutely. So, you know, it's funny, we at VMware, going through the same challenges as our customers and you know, any business, right? We use multiple clouds, we got a big, of course, on-prem footprint. You know, what we're doing is similar to what I see in many other customers, which, you see the evolution of a platform team, and so the platform team is really in charge of trying to develop a lot of these underlying services to allow our lines of business, our product teams, to be able to move as quickly as possible, to focus on the building, while we help with a lot of the operational overheads, right? We maintain security, compliance, all these other things. We also deal with, yeah, just making the developer's life as simple as possible. So, they do need to know some stuff about, you know, each public cloud they're using, those public cloud services, but at the same, time we can abstract a lot of the details they don't need to be in. So, I think this sort of delineation or separation, I should say, between the underlying platform team and the product teams is a very, very common pattern. >> You know, I noticed the four layers you talked about were observability, infrastructure, security and developers, on that slide, the last slide you had at the top, that was kind of the abstraction key areas that you guys at VMware are working? >> Those were just some groupings that we've come up with, but we like to debate them. >> I noticed data's in every one of them. >> Yeah, yep, data is key. >> It's not like, so, back to the data questions that security is called out as a pillar. Observability is just kind of watching everything, but it's all pretty much data driven. Of the four layers that you see, I take that as areas that you can. >> Standardize. >> Consistently rely on to have standard services. >> Yes. >> Which one do you start with? What's the, is there order of operations? >> Well, that's, I mean. >> 'Cause I think infrastructure's number one, but you had observability, you need to know what's going on. >> Yeah, well it really, it's highly dependent. Again, it depends on the business that we talk to and what, I mean, it really goes back to, what are your business priorities, right? And we have some customers who may want to get out of a data center, they want to evacuate the data center, and so what they want is then, consistent infrastructure, so they can just move those applications up to the cloud. They don't want to have to refactor them and we'll do it later, but there's an immediate and sort of urgent problem that they have. Other customers I talk to, you know, security becomes top of mind, or maybe compliance, because they're in a regulated industry. So, those are the sort of services they want to prioritize. So, I would say there is no single right answer, no one size fits all. The point about this architecture is really around the optionality of it, as it allows you as a business to decide what's most important and where you want to prioritize. >> How about the deployment models kit? Do, does a customer have that flexibility from a deployment model standpoint or do I have to, you know, approach it a specific way? Can you address that? >> Yeah, I mean deployment models, you're talking about how they how they consume? >> So, for instance, yeah, running a control plane in the cloud. >> Got it, got it. >> And communicating elsewhere or having a single global instance or instantiating that instance, and? >> So, that's a good point actually, and you know, the white paper that we released back in August, around this sort of concept, the Cross-cloud service. This is some of the stuff we need to figure out as an industry. So, you know when we talk about a Cross-cloud service, we can mean actually any of the things you just talked about. It could be a single instance that runs, let's say in one public cloud, but it supports all of 'em. Or it could be one that's multi-instance and that runs in each of the clouds, and that customers can take dependencies on whichever one, depending on what their use cases are or the, even going further than that, there's a type of Cross-cloud service that could actually be instantiated even in an air gapped or offline environment, and we have many, many businesses, especially heavily regulated ones that have that requirement, so I think, you know. >> Global don't forget global, regions, locales. >> Yeah, there's all sorts of performance latency issues that can be concerned about. So, most services today are the former, there are single sort of instance or set of instances within a single cloud that support multiple clouds, but I think what we're doing and where we're going with, you know, things like what we see with Kubernetes and service meshes and all these things, will better enable folks to hit these different types of cross-cloud service architectures. So, today, you as a customer probably wouldn't have too much choice, but where we're going, you'll see a lot more choice in the future. >> If you had to summarize for folks watching the importance of Supercloud movement, multi-cloud, cross-cloud services, as an industry in flexible, 'cause I'm always riffing on the whole old school network protocol stacks that got disrupted by TCP/IP, that's a little bit dated, we got people on the chat that are like, you know, 20 years old that weren't even born then. So, but this is a, one of those inflection points that's once in a generation inflection point, I'm sure you agree. What scoped the order of magnitude of the change and the opportunity around the marketplace, the business models, the technology, and ultimately benefits the society. >> Yeah. Wow. Getting bigger. >> You have 10 seconds, go. >> I know. Yeah. (laughing) No, look, so I think it is what we're seeing is really the next phase of what you might call cloud, right? This notion of delivering services, the way they've been packaged together, traditionally by the hyperscalers is now being challenged. and what we're seeing is really opening that up to new levels of innovation, and I think that will be huge for businesses because it'll help meet them where they are. Instead of needing to contort the businesses to, you know, make it work with the technology, the technology will support the business and where it's going. Give people more optionality, more flexibility in order to get there, and I think in the end, for us as individuals, it will just make for better experiences, right? You can get better performance, better interactivity, given that devices are so much of what we do, and so much of what we interact with all the time. This sort of flexibility and optionality will fundamentally better for us as individuals in our experiences. >> And we're seeing that with ChatGPT, everyone's talking about, just early days. There'll be more and more of things like that, that are next gen, like obviously like, wow, that's a fall out of your chair moment. >> It'll be the next wave of innovation that's unleashed. >> All right, Kit Colbert, thanks for coming on and sharing and exploring the Supercloud architecture, Cloud Chaos, the Cloud Smart, there's a transition progression happening and it's happening fast. This is the supercloud wave. If you're not on this wave, you'll be driftwood. That's a Pat Gelsinger quote on theCUBE. This is theCUBE Be right back with more Supercloud coverage, here in Palo Alto after this break. (upbeat music) (upbeat music continues)