>>Hi, everyone. Welcome to the cubes coverage of Avis reinvent 2021 we're onsite in person. It's a virtual event, also hybrid events. I'm Jennifer and my host, David Dante ninth year, Dave, we've been doing Avis reinvent the cube and it's 11th season. We've seen a lot. Yeah, I'll say. >>And the show is pretty packed, John. I mean, I think it's surprised some folks over 25,000 people here. I mean, obviously a lot of sponsors, but >>Customers to a bad event for AWS in terms of attendance is like record-breaking for any other company, people are standing in line for sessions. It's definitely happening. People are here to learn. They're not just all employees. So definitely a successful event in person as well in the live stream. But so much news to talk about. Andy Jassy is now the CEO of Amazon. That's the top story Adam's Lipsky's taking over as CEO of AWS time, Amazonian who left Amazon to take the CEO job of Tableau sold that company to Salesforce under mark Benioff. Now back to take the helm from Andy Jassy and quite the pressure cooker here as he takes the stage, a lot of people are asking, is will he do well? Will he fumble on stage? Will he do the right things? And does he have what it takes to take the cloud to the next generation with AWS as their number one clear far and away, then the second competitor in Microsoft and then a look distant third and Google. So Amazon's are under a ton of competitive pressure. At least from an industry standpoint, everyone's still trying to catch up. It's the same theme, Dave, every year Amazon is out front and the lead just gets extended and extended. And again, here, no exception. Well, the Uber >>Of course there's you mentioned is Andy Jassy is now taking over a CEO of Amazon. And you know, history would suggest that a lot of times that companies falter when there's a CEO transition, but it feels like it's different this time. Andy Jassy was here since the beginning launched AWS versus a profit engine of Amazon brought back Adam sill Lipski who has a deep understand. He's not as technical as Andy, but obviously as a deep understanding of the business, yeah, he was comfortable up in the keynote. It wasn't John, a typical firehose of announcements. Even those, a lot of announcements, they didn't shove them down our throat and they didn't in the analyst session as well. Usually in the analyst session, it's hours and hours and hours of firehose Kool-Aid injection, not this year. Why do you think that is, is that a COVID thing? Is that a change in now? >>I think Adam's Leschi wants to be his own guy. As, as leader here, a lot of things were eliminated from the keynote that Andy Jasmine did, for instance, Andy Jesse loves music. So we always had the music walk up music like you see in sports, uh, which is very cool. That's an Andy Jassy kind of tweak. Andy is all about announcements and he was just, uh, pushing the envelope. Adam was much more laid back. He sees, I think, more of a holistic picture being more of an app guy being more of a data guy, less of a, I would say under the covers nerd like Jassy was, Andy was very deep on, on a lot of the tech stuff as is Adam. But I think Andy a little bit more proactive on that. So Adam was very much more about the impact of 80 of us culturally, as a society, as a company and kind of brought in this kind of think different apple vibe, which is, you know, the people who are Pathfinders, um, as he takes that Jassy kind of, um, approach of leaders, but be a builder, be a change agent, be a game changer. >>Adam took it to another level by saying, Hey, it's okay to be a Pathfinder because it's net new disruption with the cloud. And I think that's the story that I see coming out of this where, uh, in talking to Adam one-on-one Amazon absolutely has a secret weapon in it's chips, custom Silicon. They're absolutely crushing it with how they're thinking about SAS and platforms and they have a huge ecosystem. And I think at the end of the day, and we talked about this in our story on Silicon angle, Amazon could actually wipe out Microsoft. And I think Microsoft's core competitive advantage has always been their ecosystem and their developers. I think right now in the next few years, if Microsoft doesn't match Amazon, they will be decimated anyway, you know? >>Yeah, hold on. Okay. Amazon's not going to wipe out Microsoft. Microsoft has too much of a cash cow. Look at the hanging on to windows. Couldn't, you know, the mistake and missing mobile event initially missing the cloud. Didn't wipe out Microsoft. So they've just got too much of a software cashflow. That's not gonna happen maybe a little bit over the top. >>I thought, but Microsoft has done a great job and it's not going to tell it to kind of stay in the game and do more. But if you look at the major inflection points, Dave where's digital equipment corporation, where's prime computer. Well, >>I think this is the point is again, history would show that those companies, when they handed the reigns over to a new CEO failed, they faltered, it was self-inflicted wounds. It almost happened. You thought it would happen with Microsoft, whether it became irrelevant under bomber, but when Nadella came in, he reinvigorated because specifically they had the cashflow to be able to do that. Now. So the big question is, okay, w what's going to happen. We ran a survey to our community to see what could disrupt Amazon. You know, that the us government wants to break them apart or wants to regulate them. But our survey respondents said there's a 60% plus probability that Amazon will be disrupted by other factors. And that's what I was self-inflicted wound that's Jesse's that's right. And that's, Jessie's big challenge is how to not make those disruptions, how to fight those disruptions. >>The number one, uh, reason why they could be disrupted was self-inflicted wounds, which again, history would show what happened. But one of the things we talked about is that normally happens when companies stop innovating when they rest on their laurels. Right. And you kind of saw that with those companies that you mentioned, but you mentioned their secret weapon. We wrote about that in our article, the chips. So we heard no secret. Everybody knew graviton three was coming, right? And so that is Amazon secret up. And you know, I've been thinking about this. John Amazon makes a lot of money on x86 instances that they've deployed years ago and they charge a lot for, I was wondering, you know, is the, or the old X 86 instances actually more profitable than graviton, maybe at this point in time, but long-term graviton. They control their own destiny because they control the hardware and software stack. And I bet you allows them to get better negotiating leverage with >>M D and it's of course, I mean, pat, Kelsey, we should talk about this all the time, but as bad as Jason Intel, you, if you're not out in the next wave, your driftwood, I think Intel and AMD and others, they have purpose-built general purpose chips. They're probably going to be for the lift and shift stuff when you, but if you're actually seriously writing software as an owner on the cloud, and you want specific advantages of speed and performance, you're going to want the custom Silicon that's purpose-built for your application and write code to that stack. So, so I think there's a whole nother level of platform as a service. Dave, that's kind of coming out of this re-invent that I think could be a multi generational trend, which is, Hey, the cloud is of super cloud or platform. Look at the riser, snowflake and Databricks. Those guys are on Amazon. Like they're super clouds in and of themselves they're platforms. They're not appoint SAS solution. I think Microsoft in my, my analysis is, yeah, they got office 365, okay. Word processing stuff. But what other SAS apps do they have besides SQL server and other things that are actually being built on there? And if, if I'm a developer you're going to want to go to the platform. That's the highest performance for office 365. It's a cash cow. But how long is that going to last >>A long time? I mean, major momentum. We argue about that later, but I wanna, I want to touch on graviton three because I think that was the big announcement of the day 25% faster than graviton to at least twice the floating point performance twice the crypto graphic performance in three times for machine learning, learning workloads, and very importantly, 60% less power. So at Amazon scale, uh, Adam said this in our meeting, he said, the economics really favor us because of our scale. And so, and they've also announced new training them instances and, and, and what, what having custom Silicon allows Amazon to do is release on a much, much faster cadence than traditional x86. And they could do, and they could do really cool things. Nitro is there, Nick they're smart NEC, which it says the basis, their new hypervisor, if you will. So it allows them to bring in x86, uh, Nvidia NPUs some of their own or Nvidia GPU, some of their own Silicon. So optionality is really the key there. You heard them announce, uh, an SAP instance. So that's a memory intensive instance. They can dial things up, dial things down. They've got full control of the stack. And by the way, copying them Google's copy of Microsoft is copying them. And who's leading this charge in custom Silicon, AWS, obviously Tesla, apple. I mean, these are leading companies that I don't think they all got it wrong. I think >>The Silicon angle is to have your own custom Silicon. And that's the, that is the clearly the advantage as it's vertically integrated. But the other thing that's coming out of this reinvents, the purpose built software concept where, you know, they're not copying Microsoft playbook as the wall street journal was saying, and some are saying Microsoft copying Amazon, Amazon has always been this horizontally scalable resource that's cloud, but with machine learning and AI, you now have this purpose-built kind of capability from software into the app itself where data has to be addressable. And I think the people in the data business kind of know this, but as the rest of the world comes out, architecturally having that horizontal observation space and data that's vertically tied to machine learning is a huge architectural shift. This is a complete rethinking of how software is built and that's going to be a game changer. I think Amazon's well out on front of that. And I think that's going to be a huge architectural shift. >>Well, let's quantify this a little bit because you know, you're, you're making the point that Amazon is the number one cloud, which I would agree with. We're talking here about IAS infrastructure as a service in the past layer that sits on top of that. Microsoft defines the cloud is we'll put in an office 365, Google we'll put in its Google apps, Amazon pure infrastructure as a service. And if you just look at that space, that's about $120 billion business. When you add up AWS, Azure, Alibaba and GCP, which I would contend are the only four hyperscalers out there. I don't include Oracle as a hyperscale. I don't include IBM. I get a lot of crap for that sometimes. Yeah, but we're talking big scaler, $120 billion. So actually relatively small compared to the trillion dollar opportunity that they have, but it's growing at 35% a year. Amazon will do more than 60 billion this year, 62 billion, just to quantify it in that ISS space. Microsoft will be about 38, 30 9 billion. Okay. So pretty substantial. Those two are far ahead of the others. Everybody else's, you know, Google is still in, you know, under 10 billion, Alibaba is right around there. So those two, it's really a two horse race. And I asked Microsoft using its software estate. Amazon's gotta be the innovator and has to have the best cloud to win. And it does well >>Also a platform. Let's go back to the little history lesson for the younger folks out there. When Microsoft was had a monopoly, they had windows operating system, which has had DAS under the covers, but windows was the operating system. And office was a suite of applications. They encourage software developers to build on top of windows and they had other servers off SQL server all came out of that small history. So their bread and butter was to have developers build on top of windows. Hence the monopoly, of course they had the application and the system software, hence the monopoly, hence the Microsoft breakup by the government in 1997. Now today cloud is essentially one big kind of PC concept. It's like windows, it's windows equivalent. So cloud is essentially an environment platform that has apps that run on top of it. Okay. In that world, Amazon by far is the number one windows model at Amazon's. >>I mean, Microsoft is used to is okay, I got Azure and I got office 365 that keeps them in business that keeps them from losing. So it's a placeholder. So that what I'm looking at is what is Amazon? I mean, Amazon versus Azure, doing relative to ISV and uptake for developers. And I'm suggesting that this trend of Amazon will go, if it goes uncontested by Azure, they'll wipe the table on ISV and suffer developers. If you're an owner of a software, you're not gonna write software, that's gonna be sub-optimized for a platform. That's not going to be before, >>Unless you're, unless you're a Microsoft developer, nearly all.net days. And there are a lot of those. And that's what, that's what Microsoft is doing. They're they're, they're, they've, they've shifted to cloud, they've gone everything into cloud. So Azure is their platform for innovation and acceleration. >>So those developers are going to build a sub application versus going over here on AWS. >>Well, that's the, that's the story with Microsoft. Good enough. I know >>Again, this is we're speculating, but we're going to watch that, but that is, to me, will be the battlefield of what will determine Azure versus AWS. And I think everything else is smoke and mirrors Amazon Webster way ahead of Azure, but the TeleSign is going to be does 80 bus attract those developers on their cloud with the custom Silicon, with the integrated stack and with the purpose-built software. I mean, it's looking really good. I think they've got a really compelling story. >>I think it's less about Azure versus AWS. I mean, that's an interesting storyline and I love to talk about it, but I think they'll go back to 120 billion out of 4 trillion. That's really the, the larger opportunity for, for both Microsoft and AWS to continue to grow. Because you look at, you look at Dell with apex, you look at HPE with GreenLake, Lenovo, Cisco, they've all got their own clouds. One of the things that didn't get into our article, but Adam Lipski when, when you asked him about hybrid is that hybrid cloud. When we were talking about some of the stuff they're doing, he S he said, look, that's not cloud what those guys are doing. That's not what we did. And he talked today about edge has to be AWS, not like AWS. That was the quote to use. Talk about, you know, private 5g, bringing out posts. And he gave some examples of that. The point is they, AWS is bringing its system, its architecture to the edge it's programming model infrastructure as code to the edge. Now, Kubernetes, Kubernetes does moderate that a little bit, but his point was, that's not AWS. That's not the cloud. >>Yeah. I think in summary, Dave had to wrap up what's the big trend this week is that Amazon web services is a, is a heaven environment for a developer, for the elite people who want to roll their own for the folks in it. In these other environments, you can have prefabricated purpose-built software platform to build on top of. And I think that isn't going to address the whole ease of ease of rollout. So if I'm a SAS developer, I don't, I want, I don't want to rebuild that over again. I don't want to roll my own. I'll take what you got and connects a good example. If you want to call shedder, you can take it and use it and then build on top of it and iterate on it. So I think it's more of here's a platform for you and take it. So I think that to me is the big story and that's not and think about it. How many people out there, a role in their own Amazon, you've got to be pretty strong at Amazon, uh, familiar ups to roll your own gut >>Of other quick points that he barely emphasized the primitives, the API APIs, that multiple databases, right tool for the right job, took a shot at Oracle without mentioning Oracle because they had sort of one database, but I will say this is mission critical. Oracle still owns that. Uh, they talked about a mainframe migration, tooling and runtime from mainframe compatible runtime. That's going to allow them to nip at the edges of those mainframe workloads and Oracle workloads. It, they're not going to get to the core anytime soon. They also talked about role level and cell level security. We think that's the squirrel acquisition from years ago. And then he made a statement. We have three X with Redshift price performance better than any cloud data warehouse sort of interesting shot at, at, at, at a snowflake and Databricks Databricks. So, um, anyway, yeah, >>I mean, I think, I think overall, I thought Adam did a good job. I think he didn't, uh, he didn't disappoint. Okay. But that's comfortable. I think his goal was to get through this and not have people go well, it's not Andy Jassy. I thought he did an awesome job and he did a good job. And he, he got, he got what he needed to do >>Comfortable. And he obviously leaned on some of his Pathfinder customers. NASDAQ, I thought was very impressive. United airlines dish. So, >>Okay. Cutie coverage, ninth year of the cube here at ADP reinvent, uh, 2021 is the cube. You're watching the leader in high-tech coverage. The cube.

(upbeat music) >> Hello everyone. Welcome to theCube's presentation of the "AWS Startup Showcase." The topic this episode is AI and machine learning, top startups building foundational model infrastructure. This is season three, episode one of the ongoing series covering exciting startups from the AWS ecosystem. And this time we're talking about AI and machine learning. I'm your host, John Furrier. I'm excited I'm joined today by Robert Nishihara, who's the co-founder and CEO of a hot startup called Anyscale. He's here to talk about Ray, the open source project, Anyscale's infrastructure for foundation as well. Robert, thank you for joining us today. >> Yeah, thanks so much as well. >> I've been following your company since the founding pre pandemic and you guys really had a great vision scaled up and in a perfect position for this big wave that we all see with ChatGPT and OpenAI that's gone mainstream. Finally, AI has broken out through the ropes and now gone mainstream, so I think you guys are really well positioned. I'm looking forward to to talking with you today. But before we get into it, introduce the core mission for Anyscale. Why do you guys exist? What is the North Star for Anyscale? >> Yeah, like you mentioned, there's a tremendous amount of excitement about AI right now. You know, I think a lot of us believe that AI can transform just every different industry. So one of the things that was clear to us when we started this company was that the amount of compute needed to do AI was just exploding. Like to actually succeed with AI, companies like OpenAI or Google or you know, these companies getting a lot of value from AI, were not just running these machine learning models on their laptops or on a single machine. They were scaling these applications across hundreds or thousands or more machines and GPUs and other resources in the Cloud. And so to actually succeed with AI, and this has been one of the biggest trends in computing, maybe the biggest trend in computing in, you know, in recent history, the amount of compute has been exploding. And so to actually succeed with that AI, to actually build these scalable applications and scale the AI applications, there's a tremendous software engineering lift to build the infrastructure to actually run these scalable applications. And that's very hard to do. So one of the reasons many AI projects and initiatives fail is that, or don't make it to production, is the need for this scale, the infrastructure lift, to actually make it happen. So our goal here with Anyscale and Ray, is to make that easy, is to make scalable computing easy. So that as a developer or as a business, if you want to do AI, if you want to get value out of AI, all you need to know is how to program on your laptop. Like, all you need to know is how to program in Python. And if you can do that, then you're good to go. Then you can do what companies like OpenAI or Google do and get value out of machine learning. >> That programming example of how easy it is with Python reminds me of the early days of Cloud, when infrastructure as code was talked about was, it was just code the infrastructure programmable. That's super important. That's what AI people wanted, first program AI. That's the new trend. And I want to understand, if you don't mind explaining, the relationship that Anyscale has to these foundational models and particular the large language models, also called LLMs, was seen with like OpenAI and ChatGPT. Before you get into the relationship that you have with them, can you explain why the hype around foundational models? Why are people going crazy over foundational models? What is it and why is it so important? >> Yeah, so foundational models and foundation models are incredibly important because they enable businesses and developers to get value out of machine learning, to use machine learning off the shelf with these large models that have been trained on tons of data and that are useful out of the box. And then, of course, you know, as a business or as a developer, you can take those foundational models and repurpose them or fine tune them or adapt them to your specific use case and what you want to achieve. But it's much easier to do that than to train them from scratch. And I think there are three, for people to actually use foundation models, there are three main types of workloads or problems that need to be solved. One is training these foundation models in the first place, like actually creating them. The second is fine tuning them and adapting them to your use case. And the third is serving them and actually deploying them. Okay, so Ray and Anyscale are used for all of these three different workloads. Companies like OpenAI or Cohere that train large language models. Or open source versions like GPTJ are done on top of Ray. There are many startups and other businesses that fine tune, that, you know, don't want to train the large underlying foundation models, but that do want to fine tune them, do want to adapt them to their purposes, and build products around them and serve them, those are also using Ray and Anyscale for that fine tuning and that serving. And so the reason that Ray and Anyscale are important here is that, you know, building and using foundation models requires a huge scale. It requires a lot of data. It requires a lot of compute, GPUs, TPUs, other resources. And to actually take advantage of that and actually build these scalable applications, there's a lot of infrastructure that needs to happen under the hood. And so you can either use Ray and Anyscale to take care of that and manage the infrastructure and solve those infrastructure problems. Or you can build the infrastructure and manage the infrastructure yourself, which you can do, but it's going to slow your team down. It's going to, you know, many of the businesses we work with simply don't want to be in the business of managing infrastructure and building infrastructure. They want to focus on product development and move faster. >> I know you got a keynote presentation we're going to go to in a second, but I think you hit on something I think is the real tipping point, doing it yourself, hard to do. These are things where opportunities are and the Cloud did that with data centers. Turned a data center and made it an API. The heavy lifting went away and went to the Cloud so people could be more creative and build their product. In this case, build their creativity. Is that kind of what's the big deal? Is that kind of a big deal happening that you guys are taking the learnings and making that available so people don't have to do that? >> That's exactly right. So today, if you want to succeed with AI, if you want to use AI in your business, infrastructure work is on the critical path for doing that. To do AI, you have to build infrastructure. You have to figure out how to scale your applications. That's going to change. We're going to get to the point, and you know, with Ray and Anyscale, we're going to remove the infrastructure from the critical path so that as a developer or as a business, all you need to focus on is your application logic, what you want the the program to do, what you want your application to do, how you want the AI to actually interface with the rest of your product. Now the way that will happen is that Ray and Anyscale will still, the infrastructure work will still happen. It'll just be under the hood and taken care of by Ray in Anyscale. And so I think something like this is really necessary for AI to reach its potential, for AI to have the impact and the reach that we think it will, you have to make it easier to do. >> And just for clarification to point out, if you don't mind explaining the relationship of Ray and Anyscale real quick just before we get into the presentation. >> So Ray is an open source project. We created it. We were at Berkeley doing machine learning. We started Ray so that, in order to provide an easy, a simple open source tool for building and running scalable applications. And Anyscale is the managed version of Ray, basically we will run Ray for you in the Cloud, provide a lot of tools around the developer experience and managing the infrastructure and providing more performance and superior infrastructure. >> Awesome. I know you got a presentation on Ray and Anyscale and you guys are positioning as the infrastructure for foundational models. So I'll let you take it away and then when you're done presenting, we'll come back, I'll probably grill you with a few questions and then we'll close it out so take it away. >> Robert: Sounds great. So I'll say a little bit about how companies are using Ray and Anyscale for foundation models. The first thing I want to mention is just why we're doing this in the first place. And the underlying observation, the underlying trend here, and this is a plot from OpenAI, is that the amount of compute needed to do machine learning has been exploding. It's been growing at something like 35 times every 18 months. This is absolutely enormous. And other people have written papers measuring this trend and you get different numbers. But the point is, no matter how you slice and dice it, it' a astronomical rate. Now if you compare that to something we're all familiar with, like Moore's Law, which says that, you know, the processor performance doubles every roughly 18 months, you can see that there's just a tremendous gap between the needs, the compute needs of machine learning applications, and what you can do with a single chip, right. So even if Moore's Law were continuing strong and you know, doing what it used to be doing, even if that were the case, there would still be a tremendous gap between what you can do with the chip and what you need in order to do machine learning. And so given this graph, what we've seen, and what has been clear to us since we started this company, is that doing AI requires scaling. There's no way around it. It's not a nice to have, it's really a requirement. And so that led us to start Ray, which is the open source project that we started to make it easy to build these scalable Python applications and scalable machine learning applications. And since we started the project, it's been adopted by a tremendous number of companies. Companies like OpenAI, which use Ray to train their large models like ChatGPT, companies like Uber, which run all of their deep learning and classical machine learning on top of Ray, companies like Shopify or Spotify or Instacart or Lyft or Netflix, ByteDance, which use Ray for their machine learning infrastructure. Companies like Ant Group, which makes Alipay, you know, they use Ray across the board for fraud detection, for online learning, for detecting money laundering, you know, for graph processing, stream processing. Companies like Amazon, you know, run Ray at a tremendous scale and just petabytes of data every single day. And so the project has seen just enormous adoption since, over the past few years. And one of the most exciting use cases is really providing the infrastructure for building training, fine tuning, and serving foundation models. So I'll say a little bit about, you know, here are some examples of companies using Ray for foundation models. Cohere trains large language models. OpenAI also trains large language models. You can think about the workloads required there are things like supervised pre-training, also reinforcement learning from human feedback. So this is not only the regular supervised learning, but actually more complex reinforcement learning workloads that take human input about what response to a particular question, you know is better than a certain other response. And incorporating that into the learning. There's open source versions as well, like GPTJ also built on top of Ray as well as projects like Alpa coming out of UC Berkeley. So these are some of the examples of exciting projects in organizations, training and creating these large language models and serving them using Ray. Okay, so what actually is Ray? Well, there are two layers to Ray. At the lowest level, there's the core Ray system. This is essentially low level primitives for building scalable Python applications. Things like taking a Python function or a Python class and executing them in the cluster setting. So Ray core is extremely flexible and you can build arbitrary scalable applications on top of Ray. So on top of Ray, on top of the core system, what really gives Ray a lot of its power is this ecosystem of scalable libraries. So on top of the core system you have libraries, scalable libraries for ingesting and pre-processing data, for training your models, for fine tuning those models, for hyper parameter tuning, for doing batch processing and batch inference, for doing model serving and deployment, right. And a lot of the Ray users, the reason they like Ray is that they want to run multiple workloads. They want to train and serve their models, right. They want to load their data and feed that into training. And Ray provides common infrastructure for all of these different workloads. So this is a little overview of what Ray, the different components of Ray. So why do people choose to go with Ray? I think there are three main reasons. The first is the unified nature. The fact that it is common infrastructure for scaling arbitrary workloads, from data ingest to pre-processing to training to inference and serving, right. This also includes the fact that it's future proof. AI is incredibly fast moving. And so many people, many companies that have built their own machine learning infrastructure and standardized on particular workflows for doing machine learning have found that their workflows are too rigid to enable new capabilities. If they want to do reinforcement learning, if they want to use graph neural networks, they don't have a way of doing that with their standard tooling. And so Ray, being future proof and being flexible and general gives them that ability. Another reason people choose Ray in Anyscale is the scalability. This is really our bread and butter. This is the reason, the whole point of Ray, you know, making it easy to go from your laptop to running on thousands of GPUs, making it easy to scale your development workloads and run them in production, making it easy to scale, you know, training to scale data ingest, pre-processing and so on. So scalability and performance, you know, are critical for doing machine learning and that is something that Ray provides out of the box. And lastly, Ray is an open ecosystem. You can run it anywhere. You can run it on any Cloud provider. Google, you know, Google Cloud, AWS, Asure. You can run it on your Kubernetes cluster. You can run it on your laptop. It's extremely portable. And not only that, it's framework agnostic. You can use Ray to scale arbitrary Python workloads. You can use it to scale and it integrates with libraries like TensorFlow or PyTorch or JAX or XG Boost or Hugging Face or PyTorch Lightning, right, or Scikit-learn or just your own arbitrary Python code. It's open source. And in addition to integrating with the rest of the machine learning ecosystem and these machine learning frameworks, you can use Ray along with all of the other tooling in the machine learning ecosystem. That's things like weights and biases or ML flow, right. Or you know, different data platforms like Databricks, you know, Delta Lake or Snowflake or tools for model monitoring for feature stores, all of these integrate with Ray. And that's, you know, Ray provides that kind of flexibility so that you can integrate it into the rest of your workflow. And then Anyscale is the scalable compute platform that's built on top, you know, that provides Ray. So Anyscale is a managed Ray service that runs in the Cloud. And what Anyscale does is it offers the best way to run Ray. And if you think about what you get with Anyscale, there are fundamentally two things. One is about moving faster, accelerating the time to market. And you get that by having the managed service so that as a developer you don't have to worry about managing infrastructure, you don't have to worry about configuring infrastructure. You also, it provides, you know, optimized developer workflows. Things like easily moving from development to production, things like having the observability tooling, the debug ability to actually easily diagnose what's going wrong in a distributed application. So things like the dashboards and the other other kinds of tooling for collaboration, for monitoring and so on. And then on top of that, so that's the first bucket, developer productivity, moving faster, faster experimentation and iteration. The second reason that people choose Anyscale is superior infrastructure. So this is things like, you know, cost deficiency, being able to easily take advantage of spot instances, being able to get higher GPU utilization, things like faster cluster startup times and auto scaling. Things like just overall better performance and faster scheduling. And so these are the kinds of things that Anyscale provides on top of Ray. It's the managed infrastructure. It's fast, it's like the developer productivity and velocity as well as performance. So this is what I wanted to share about Ray in Anyscale. >> John: Awesome. >> Provide that context. But John, I'm curious what you think. >> I love it. I love the, so first of all, it's a platform because that's the platform architecture right there. So just to clarify, this is an Anyscale platform, not- >> That's right. >> Tools. So you got tools in the platform. Okay, that's key. Love that managed service. Just curious, you mentioned Python multiple times, is that because of PyTorch and TensorFlow or Python's the most friendly with machine learning or it's because it's very common amongst all developers? >> That's a great question. Python is the language that people are using to do machine learning. So it's the natural starting point. Now, of course, Ray is actually designed in a language agnostic way and there are companies out there that use Ray to build scalable Java applications. But for the most part right now we're focused on Python and being the best way to build these scalable Python and machine learning applications. But, of course, down the road there always is that potential. >> So if you're slinging Python code out there and you're watching that, you're watching this video, get on Anyscale bus quickly. Also, I just, while you were giving the presentation, I couldn't help, since you mentioned OpenAI, which by the way, congratulations 'cause they've had great scale, I've noticed in their rapid growth 'cause they were the fastest company to the number of users than anyone in the history of the computer industry, so major successor, OpenAI and ChatGPT, huge fan. I'm not a skeptic at all. I think it's just the beginning, so congratulations. But I actually typed into ChatGPT, what are the top three benefits of Anyscale and came up with scalability, flexibility, and ease of use. Obviously, scalability is what you guys are called. >> That's pretty good. >> So that's what they came up with. So they nailed it. Did you have an inside prompt training, buy it there? Only kidding. (Robert laughs) >> Yeah, we hard coded that one. >> But that's the kind of thing that came up really, really quickly if I asked it to write a sales document, it probably will, but this is the future interface. This is why people are getting excited about the foundational models and the large language models because it's allowing the interface with the user, the consumer, to be more human, more natural. And this is clearly will be in every application in the future. >> Absolutely. This is how people are going to interface with software, how they're going to interface with products in the future. It's not just something, you know, not just a chat bot that you talk to. This is going to be how you get things done, right. How you use your web browser or how you use, you know, how you use Photoshop or how you use other products. Like you're not going to spend hours learning all the APIs and how to use them. You're going to talk to it and tell it what you want it to do. And of course, you know, if it doesn't understand it, it's going to ask clarifying questions. You're going to have a conversation and then it'll figure it out. >> This is going to be one of those things, we're going to look back at this time Robert and saying, "Yeah, from that company, that was the beginning of that wave." And just like AWS and Cloud Computing, the folks who got in early really were in position when say the pandemic came. So getting in early is a good thing and that's what everyone's talking about is getting in early and playing around, maybe replatforming or even picking one or few apps to refactor with some staff and managed services. So people are definitely jumping in. So I have to ask you the ROI cost question. You mentioned some of those, Moore's Law versus what's going on in the industry. When you look at that kind of scale, the first thing that jumps out at people is, "Okay, I love it. Let's go play around." But what's it going to cost me? Am I going to be tied to certain GPUs? What's the landscape look like from an operational standpoint, from the customer? Are they locked in and the benefit was flexibility, are you flexible to handle any Cloud? What is the customers, what are they looking at? Basically, that's my question. What's the customer looking at? >> Cost is super important here and many of the companies, I mean, companies are spending a huge amount on their Cloud computing, on AWS, and on doing AI, right. And I think a lot of the advantage of Anyscale, what we can provide here is not only better performance, but cost efficiency. Because if we can run something faster and more efficiently, it can also use less resources and you can lower your Cloud spending, right. We've seen companies go from, you know, 20% GPU utilization with their current setup and the current tools they're using to running on Anyscale and getting more like 95, you know, 100% GPU utilization. That's something like a five x improvement right there. So depending on the kind of application you're running, you know, it's a significant cost savings. We've seen companies that have, you know, processing petabytes of data every single day with Ray going from, you know, getting order of magnitude cost savings by switching from what they were previously doing to running their application on Ray. And when you have applications that are spending, you know, potentially $100 million a year and getting a 10 X cost savings is just absolutely enormous. So these are some of the kinds of- >> Data infrastructure is super important. Again, if the customer, if you're a prospect to this and thinking about going in here, just like the Cloud, you got infrastructure, you got the platform, you got SaaS, same kind of thing's going to go on in AI. So I want to get into that, you know, ROI discussion and some of the impact with your customers that are leveraging the platform. But first I hear you got a demo. >> Robert: Yeah, so let me show you, let me give you a quick run through here. So what I have open here is the Anyscale UI. I've started a little Anyscale Workspace. So Workspaces are the Anyscale concept for interactive developments, right. So here, imagine I'm just, you want to have a familiar experience like you're developing on your laptop. And here I have a terminal. It's not on my laptop. It's actually in the cloud running on Anyscale. And I'm just going to kick this off. This is going to train a large language model, so OPT. And it's doing this on 32 GPUs. We've got a cluster here with a bunch of CPU cores, bunch of memory. And as that's running, and by the way, if I wanted to run this on instead of 32 GPUs, 64, 128, this is just a one line change when I launch the Workspace. And what I can do is I can pull up VS code, right. Remember this is the interactive development experience. I can look at the actual code. Here it's using Ray train to train the torch model. We've got the training loop and we're saying that each worker gets access to one GPU and four CPU cores. And, of course, as I make the model larger, this is using deep speed, as I make the model larger, I could increase the number of GPUs that each worker gets access to, right. And how that is distributed across the cluster. And if I wanted to run on CPUs instead of GPUs or a different, you know, accelerator type, again, this is just a one line change. And here we're using Ray train to train the models, just taking my vanilla PyTorch model using Hugging Face and then scaling that across a bunch of GPUs. And, of course, if I want to look at the dashboard, I can go to the Ray dashboard. There are a bunch of different visualizations I can look at. I can look at the GPU utilization. I can look at, you know, the CPU utilization here where I think we're currently loading the model and running that actual application to start the training. And some of the things that are really convenient here about Anyscale, both I can get that interactive development experience with VS code. You know, I can look at the dashboards. I can monitor what's going on. It feels, I have a terminal, it feels like my laptop, but it's actually running on a large cluster. And I can, with however many GPUs or other resources that I want. And so it's really trying to combine the best of having the familiar experience of programming on your laptop, but with the benefits, you know, being able to take advantage of all the resources in the Cloud to scale. And it's like when, you know, you're talking about cost efficiency. One of the biggest reasons that people waste money, one of the silly reasons for wasting money is just forgetting to turn off your GPUs. And what you can do here is, of course, things will auto terminate if they're idle. But imagine you go to sleep, I have this big cluster. You can turn it off, shut off the cluster, come back tomorrow, restart the Workspace, and you know, your big cluster is back up and all of your code changes are still there. All of your local file edits. It's like you just closed your laptop and came back and opened it up again. And so this is the kind of experience we want to provide for our users. So that's what I wanted to share with you. >> Well, I think that whole, couple of things, lines of code change, single line of code change, that's game changing. And then the cost thing, I mean human error is a big deal. People pass out at their computer. They've been coding all night or they just forget about it. I mean, and then it's just like leaving the lights on or your water running in your house. It's just, at the scale that it is, the numbers will add up. That's a huge deal. So I think, you know, compute back in the old days, there's no compute. Okay, it's just compute sitting there idle. But you know, data cranking the models is doing, that's a big point. >> Another thing I want to add there about cost efficiency is that we make it really easy to use, if you're running on Anyscale, to use spot instances and these preemptable instances that can just be significantly cheaper than the on-demand instances. And so when we see our customers go from what they're doing before to using Anyscale and they go from not using these spot instances 'cause they don't have the infrastructure around it, the fault tolerance to handle the preemption and things like that, to being able to just check a box and use spot instances and save a bunch of money. >> You know, this was my whole, my feature article at Reinvent last year when I met with Adam Selipsky, this next gen Cloud is here. I mean, it's not auto scale, it's infrastructure scale. It's agility. It's flexibility. I think this is where the world needs to go. Almost what DevOps did for Cloud and what you were showing me that demo had this whole SRE vibe. And remember Google had site reliability engines to manage all those servers. This is kind of like an SRE vibe for data at scale. I mean, a similar kind of order of magnitude. I mean, I might be a little bit off base there, but how would you explain it? >> It's a nice analogy. I mean, what we are trying to do here is get to the point where developers don't think about infrastructure. Where developers only think about their application logic. And where businesses can do AI, can succeed with AI, and build these scalable applications, but they don't have to build, you know, an infrastructure team. They don't have to develop that expertise. They don't have to invest years in building their internal machine learning infrastructure. They can just focus on the Python code, on their application logic, and run the stuff out of the box. >> Awesome. Well, I appreciate the time. Before we wrap up here, give a plug for the company. I know you got a couple websites. Again, go, Ray's got its own website. You got Anyscale. You got an event coming up. Give a plug for the company looking to hire. Put a plug in for the company. >> Yeah, absolutely. Thank you. So first of all, you know, we think AI is really going to transform every industry and the opportunity is there, right. We can be the infrastructure that enables all of that to happen, that makes it easy for companies to succeed with AI, and get value out of AI. Now we have, if you're interested in learning more about Ray, Ray has been emerging as the standard way to build scalable applications. Our adoption has been exploding. I mentioned companies like OpenAI using Ray to train their models. But really across the board companies like Netflix and Cruise and Instacart and Lyft and Uber, you know, just among tech companies. It's across every industry. You know, gaming companies, agriculture, you know, farming, robotics, drug discovery, you know, FinTech, we see it across the board. And all of these companies can get value out of AI, can really use AI to improve their businesses. So if you're interested in learning more about Ray and Anyscale, we have our Ray Summit coming up in September. This is going to highlight a lot of the most impressive use cases and stories across the industry. And if your business, if you want to use LLMs, you want to train these LLMs, these large language models, you want to fine tune them with your data, you want to deploy them, serve them, and build applications and products around them, give us a call, talk to us. You know, we can really take the infrastructure piece, you know, off the critical path and make that easy for you. So that's what I would say. And, you know, like you mentioned, we're hiring across the board, you know, engineering, product, go-to-market, and it's an exciting time. >> Robert Nishihara, co-founder and CEO of Anyscale, congratulations on a great company you've built and continuing to iterate on and you got growth ahead of you, you got a tailwind. I mean, the AI wave is here. I think OpenAI and ChatGPT, a customer of yours, have really opened up the mainstream visibility into this new generation of applications, user interface, roll of data, large scale, how to make that programmable so we're going to need that infrastructure. So thanks for coming on this season three, episode one of the ongoing series of the hot startups. In this case, this episode is the top startups building foundational model infrastructure for AI and ML. I'm John Furrier, your host. Thanks for watching. (upbeat music)

(light music) >> Announcer: TheCUBE's live coverage is made possible by funding from Dell Technologies. Creating technologies that drive human progress. (upbeat music) >> Welcome back to the Fira in Barcelona. Dave Vellante with Dave Nicholson. Lisa Martin's been here all week. John Furrier is in our Palo Alto studio, banging out all the news. Don't forget to check out siliconangle.com, thecube.net. This is day four, our last segment, winding down. MWC23, super excited to be here. Wayne Duso, friend of theCUBE, VP of engineering from products at AWS is here with Iyad Tarazi, who's the CEO of Federated Wireless. Gents, welcome. >> Good to be here. >> Nice to see you. >> I'm so stoked, Wayne, that we connected before the show. We texted, I'm like, "You're going to be there. I'm going to be there. You got to come on theCUBE." So thank you so much for making time, and thank you for bringing a customer partner, Federated Wireless. Everybody knows AWS. Iyad, tell us about Federated Wireless. >> We're a software and services company out of Arlington, Virginia, right outside of Washington, DC, and we're really focused on this new technology called Shared Spectrum and private wireless for 5G. Think of it as enterprises consuming 5G, the way they used to consume WiFi. >> Is that unrestricted spectrum, or? >> It is managed, organized, interference free, all through cloud platforms. That's how we got to know AWS. We went and got maybe about 300 products from AWS to make it work. Quite sophisticated, highly available, and pristine spectrum worth billions of dollars, but available for people like you and I, that want to build enterprises, that want to make things work. Also carriers, cable companies everybody else that needs it. It's really a new revolution for everyone. >> And that's how you, it got introduced to AWS. Was that through public sector, or just the coincidence that you're in DC >> No, I, well, yes. The center of gravity in the world for spectrum is literally Arlington. You have the DOD spectrum people, you have spectrum people from National Science Foundation, DARPA, and then you have commercial sector, and you have the FCC just an Uber ride away. So we went and found the scientists that are doing all this work, four or five of them, Virginia Tech has an office there too, for spectrum research for the Navy. Come together, let's have a party and make a new model. >> So I asked this, I'm super excited to have you on theCUBE. I sat through the keynotes on Monday. I saw Satya Nadella was in there, Thomas Kurian there was no AWS. I'm like, where's AWS? AWS is everywhere. I mean, you guys are all over the show. I'm like, "Hey, where's the number one cloud?" So you guys have made a bunch of announcements at the show. Everybody's talking about the cloud. What's going on for you guys? >> So we are everywhere, and you know, we've been coming to this show for years. But this is really a year that we can demonstrate that what we've been doing for the IT enterprise, IT people for 17 years, we're now bringing for telcos, you know? For years, we've been, 17 years to be exact, we've been bringing the cloud value proposition, whether it's, you know, cost efficiencies or innovation or scale, reliability, security and so on, to these enterprise IT folks. Now we're doing the same thing for telcos. And so whether they want to build in region, in a local zone, metro area, on-prem with an outpost, at the edge with Snow Family, or with our IoT devices. And no matter where they want to start, if they start in the cloud and they want to move to the edge, or they start in the edge and they want to bring the cloud value proposition, like, we're demonstrating all of that is happening this week. And, and very much so, we're also demonstrating that we're bringing the same type of ecosystem that we've built for enterprise IT. We're bringing that type of ecosystem to the telco companies, with CSPs, with the ISP vendors. We've seen plenty of announcements this week. You know, so on and so forth. >> So what's different, is it, the names are different? Is it really that simple, that you're just basically taking the cloud model into telco, and saying, "Hey, why do all this undifferentiated heavy lifting when we can do it for you? Don't worry about all the plumbing." Is it really that simple? I mean, that straightforward. >> Well, simple is probably not what I'd say, but we can make it straightforward. >> Conceptually. >> Conceptually, yes. Conceptually it is the same. Because if you think about, firstly, we'll just take 5G for a moment, right? The 5G folks, if you look at the architecture for 5G, it was designed to run on a cloud architecture. It was designed to be a set of services that you could partition, and run in different places, whether it's in the region or at the edge. So in many ways it is sort of that simple. And let me give you an example. Two things, the first one is we announced integrated private wireless on AWS, which allows enterprise customers to come to a portal and look at the industry solutions. They're not worried about their network, they're worried about solving a problem, right? And they can come to that portal, they can find a solution, they can find a service provider that will help them with that solution. And what they end up with is a fully validated offering that AWS telco SAS have actually put to its paces to make sure this is a real thing. And whether they get it from a telco, and, and quite frankly in that space, it's SIs such as Federated that actually help our customers deploy those in private environments. So that's an example. And then added to that, we had a second announcement, which was AWS telco network builder, which allows telcos to plan, deploy, and operate at scale telco network capabilities on the cloud, think about it this way- >> As a managed service? >> As a managed service. So think about it this way. And the same way that enterprise IT has been deploying, you know, infrastructure as code for years. Telco network builder allows the telco folks to deploy telco networks and their capabilities as code. So it's not simple, but it is pretty straightforward. We're making it more straightforward as we go. >> Jump in Dave, by the way. He can geek out if you want. >> Yeah, no, no, no, that's good, that's good, that's good. But actually, I'm going to ask an AWS question, but I'm going to ask Iyad the AWS question. So when we, when I hear the word cloud from Wayne, cloud, AWS, typically in people's minds that denotes off-premises. Out there, AWS data center. In the telecom space, yes, of course, in the private 5G space, we're talking about a little bit of a different dynamic than in the public 5G space, in terms of the physical infrastructure. But regardless at the edge, there are things that need to be physically at the edge. Do you feel that AWS is sufficiently, have they removed the H word, hybrid, from the list of bad words you're not allowed to say? 'Cause there was a point in time- >> Yeah, of course. >> Where AWS felt that their growth- >> They'll even say multicloud today, (indistinct). >> No, no, no, no, no. But there was a period of time where, rightfully so, AWS felt that the growth trajectory would be supported solely by net new things off premises. Now though, in this space, it seems like that hybrid model is critical. Do you see AWS being open to the hybrid nature of things? >> Yeah, they're, absolutely. I mean, just to explain from- we're a services company and a solutions company. So we put together solutions at the edge, a smart campus, smart agriculture, a deployment. One of our biggest deployment is a million square feet warehouse automation project with the Marine Corps. >> That's bigger than the Fira. >> Oh yeah, it's bigger, definitely bigger than, you know, a small section of here. It's actually three massive warehouses. So yes, that is the edge. What the cloud is about is that massive amount of efficiency has happened by concentrating applications in data centers. And that is programmability, that is APIs that is solutions, that is applications that can run on it, where people know how to do it. And so all that efficiency now is being ported in a box called the edge. What AWS is doing for us is bringing all the business and technical solutions they had into the edge. Some of the data may send back and forth, but that's actually a smaller piece of the value for us. By being able to bring an AWS package at the edge, we're bringing IoT applications, we're bringing high speed cameras, we're able to integrate with the 5G public network. We're able to bring in identity and devices, we're able to bring in solutions for students, embedded laptops. All of these things that you can do much much faster and cheaper if you are able to tap in the 4,000, 5,000 partners and all the applications and all the development and all the models that AWS team did. By being able to bring that efficiency to the edge why reinvent that? And then along with that, there are partners that you, that help do integration. There are development done to make it hardened, to make the data more secure, more isolated. All of these things will contribute to an edge that truly is a carbon copy of the data center. >> So Wayne, it's AWS, Regardless of where the compute, networking and storage physically live, it's AWS. Do you think that the term cloud will sort of drift away from usage? Because if, look, it's all IT, in this case it's AWS and federated IT working together. How, what's your, it's sort of a obscure question about cloud, because cloud is so integrated. >> You Got this thing about cloud, it's just IT. >> I got thing about cloud too, because- >> You and Larry Ellison. >> Because it's no, no, no, I'm, yeah, well actually there's- >> There's a lot of IT that's not cloud, just say that okay. >> Now, a lot of IT that isn't cloud, but I would say- >> But I'll (indistinct) cloud is an IT tool, and you see AWS obviously with the Snow fill in the blank line of products and outpost type stuff. Fair to say that you're, doesn't matter where it is, it could be AWS if it's on the edge, right? >> Well, you know, everybody wants to define the cloud as what it may have been when it started. But if you look at what it was when it started and what it is today, it is different. But the ability to bring the experience, the AWS experience, the services, the operational experience and all the things that Iyad had been talking about from the region all to all the way to, you know, the IoT device, if you would, that entire continuum. And it doesn't matter where you start. Like if you start in region and you need to bring your value to other places because your customers are asking you to do so, we're enabling that experience where you need to bring it. If you started at the edge, and- but you want to build cloud value, you know, whether it's again, cost efficiency, scalability, AI, ML or analytics into those capabilities, you can start at the edge with the same APIs, with the same service, the same capabilities, and you can build that value in right from the get go. You don't build this bifurcation or many separations and try to figure out how do I glue them together? There is no gluing together. So if you think of cloud as being elastic, scalable flexible, where you can drive innovation, it's the same exact model on the continuum. And you can start at either end, it's up to you as a customer. >> And I think if, the key to me is the ecosystem. I mean, if you can do for this industry what you've done for the technology- enterprise technology business from an ecosystem standpoint, you know everybody talks about flywheel, but that gives you like the massive flywheel. I don't know what the ratio is, but it used to be for every dollar spent on a VMware license, $15 is spent in the ecosystem. I've never heard similar ratios in the AWS ecosystem, but it's, I go to reinvent and I'm like, there's some dollars being- >> That's a massive ecosystem. >> (indistinct). >> And then, and another thing I'll add is Jose Maria Alvarez, who's the chairman of Telefonica, said there's three pillars of the future-ready telco, low latency, programmable networks, and he said cloud and edge. So they recognizing cloud and edge, you know, low latency means you got to put the compute and the data, the programmable infrastructure was invented by Amazon. So what's the strategy around the telco edge? >> So, you know, at the end, so those are all great points. And in fact, the programmability of the network was a big theme in the show. It was a huge theme. And if you think about the cloud, what is the cloud? It's a set of APIs against a set of resources that you use in whatever way is appropriate for what you're trying to accomplish. The network, the telco network becomes a resource. And it could be described as a resource. We, I talked about, you know, network as in code, right? It's same infrastructure in code, it's telco infrastructure as code. And that code, that infrastructure, is programmable. So this is really, really important. And in how you build the ecosystem around that is no different than how we built the ecosystem around traditional IT abstractions. In fact, we feel that really the ecosystem is the killer app for 5G. You know, the killer app for 4G, data of sorts, right? We started using data beyond simple SMS messages. So what's the killer app for 5G? It's building this ecosystem, which includes the CSPs, the ISVs, all of the partners that we bring to the table that can drive greater value. It's not just about cost efficiency. You know, you can't save your way to success, right? At some point you need to generate greater value for your customers, which gives you better business outcomes, 'cause you can monetize them, right? The ecosystem is going to allow everybody to monetize 5G. >> 5G is like the dot connector of all that. And then developers come in on top and create new capabilities >> And how different is that than, you know, the original smartphones? >> Yeah, you're right. So what do you guys think of ChatGPT? (indistinct) to Amazon? Amazon turned the data center into an API. It's like we're visioning this world, and I want to ask that technologist, like, where it's turning resources into human language interfaces. You know, when you see that, you play with ChatGPT at all, or I know you guys got your own. >> So I won't speak directly to ChatGPT. >> No, don't speak from- >> But if you think about- >> Generative AI. >> Yeah generative AI is important. And, and we are, and we have been for years, in this space. Now you've been talking to AWS for a long time, and we often don't talk about things we don't have yet. We don't talk about things that we haven't brought to market yet. And so, you know, you'll often hear us talk about something, you know, a year from now where others may have been talking about it three years earlier, right? We will be talking about this space when we feel it's appropriate for our customers and our partners. >> You have talked about it a little bit, Adam Selipsky went on an interview with myself and John Furrier in October said you watch, you know, large language models are going to be enormous and I know you guys have some stuff that you're working on there. >> It's, I'll say it's exciting. >> Yeah, I mean- >> Well proof point is, Siri is an idiot compared to Alexa. (group laughs) So I trust one entity to come up with something smart. >> I have conversations with Alexa and Siri, and I won't judge either one. >> You don't need, you could be objective on that one. I definitely have a preference. >> Are the problems you guys solving in this space, you know, what's unique about 'em? What are they, can we, sort of, take some examples here (indistinct). >> Sure, the main theme is that the enterprise is taking control. They want to have their own networks. They want to focus on specific applications, and they want to build them with a skeleton crew. The one IT person in a warehouse want to be able to do it all. So what's unique about them is that they're now are a lot of automation on robotics, especially in warehousing environment agriculture. There simply aren't enough people in these industries, and that required precision. And so you need all that integration to make it work. People also want to build these networks as they want to control it. They want to figure out how do we actually pick this team and migrate it. Maybe just do the front of the house first. Maybe it's a security team that monitor the building, maybe later on upgrade things that use to open doors and close doors and collect maintenance data. So that ability to pick what you want to do from a new processors is really important. And then you're also seeing a lot of public-private network interconnection. That's probably the undercurrent of this show that haven't been talked about. When people say private networks, they're also talking about something called neutral host, which means I'm going to build my own network, but I want it to work, my Verizon (indistinct) need to work. There's been so much progress, it's not done yet. So much progress about this bring my own network concept, and then make sure that I'm now interoperating with the public network, but it's my domain. I can create air gaps, I can create whatever security and policy around it. That is probably the power of 5G. Now take all of these tiny networks, big networks, put them all in one ecosystem. Call it the Amazon marketplace, call it the Amazon ecosystem, that's 5G. It's going to be tremendous future. >> What does the future look like? We're going to, we just determined we're going to be orchestrating the network through human language, okay? (group laughs) But seriously, what's your vision for the future here? You know, both connectivity and cloud are on on a continuum. It's, they've been on a continuum forever. They're going to continue to be on a continuum. That being said, those continuums are coming together, right? They're coming together to bring greater value to a greater set of customers, and frankly all of us. So, you know, the future is now like, you know, this conference is the future, and if you look at what's going on, it's about the acceleration of the future, right? What we announced this week is really the acceleration of listening to customers for the last handful of years. And, we're going to continue to do that. We're going to continue to bring greater value in the form of solutions. And that's what I want to pick up on from the prior question. It's not about the network, it's not about the cloud, it's about the solutions that we can provide the customers where they are, right? And if they're on their mobile phone or they're in their factory floor, you know, they're looking to accelerate their business. They're looking to accelerate their value. They're looking to create greater safety for their employees. That's what we can do with these technologies. So in fact, when we came out with, you know, our announcement for integrated private wireless, right? It really was about industry solutions. It really isn't about, you know, the cloud or the network. It's about how you can leverage those technologies, that continuum, to deliver you value. >> You know, it's interesting you say that, 'cause again, when we were interviewing Adam Selipsky, everybody, you know, all journalists analysts want to know, how's Adam Selipsky going to be different from Andy Jassy, what's the, what's he going to do to Amazon to change? And he said, listen, the real answer is Amazon has changed. If Andy Jassy were here, we'd be doing all, you know, pretty much the same things. Your point about 17 years ago, the cloud was S3, right, and EC2. Now it's got to evolve to be solutions. 'Cause if that's all you're selling, is the bespoke services, then you know, the future is not as bright as the past has been. And so I think it's key to look for what are those outcomes or solutions that customers require and how you're going to meet 'em. And there's a lot of challenges. >> You continue to build value on the value that you've brought, and you don't lose sight of why that value is important. You carry that value proposition up the stack, but the- what you're delivering, as you said, becomes maybe a bigger or or different. >> And you are getting more solution oriented. I mean, you're not hardcore solutions yet, but we're seeing more and more of that. And that seems to be a trend. We've even seen in the database world, making things easier, connecting things. Not really an abstraction layer, which is sort of antithetical to your philosophy, but it creates a similar outcome in terms of simplicity. Yeah, you're smiling 'cause you guys always have a different angle, you know? >> Yeah, we've had this conversation. >> It's right, it's, Jassy used to say it's okay to be misunderstood. >> That's Right. For a long time. >> Yeah, right, guys, thanks so much for coming to theCUBE. I'm so glad we could make this happen. >> It's always good. Thank you. >> Thank you so much. >> All right, Dave Nicholson, for Lisa Martin, Dave Vellante, John Furrier in the Palo Alto studio. We're here at the Fira, wrapping out MWC23. Keep it right there, thanks for watching. (upbeat music)

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

>> Welcome back everyone to the closing remarks here before we kick off our ecosystem portion of the program. We're live in Palo Alto for theCUBE special presentation of Supercloud 2. It's the second edition, the first one was in August. I'm John Furrier with Dave Vellante. Here to wrap up with our special guest analyst George Gilbert, investor and industry legend former colleague of ours, analyst at Wikibon. George great to see you. Dave, you know, wrapping up this day what in a phenomenal program. We had a contribution from industry vendors, industry experts, practitioners and customers building and redefining their company's business model. Rolling out technology for Supercloud and multicloud and ultimately changing how they do data. And data was the theme today. So very, very great program. Before we jump into our favorite parts let's give a shout out to the folks who make this possible. Free contents our mission. We'll always stay true to that mission. We want to thank VMware, alkira, ChaosSearch, prosimo for being sponsors of this great program. We will have Supercloud 3 coming up in a month or so, or two months. We'll see. Or sooner, we don't know. But it'll be more about security, but a lot more momentum. Okay, so that's... >> And don't forget too that this program not going to end now. We've got a whole ecosystem speaks track so stay tuned for that. >> John: Yeah, we got another 20 interviews. Feels like it. >> Well, you're going to hear from Saks, Veronika Durgin. You're going to hear from Western Union, Harveer Singh. You're going to hear from Ionis Pharmaceuticals, Nick Taylor. Brian Gracely chimes in on Supecloud. So he's the man behind the cloud cast. >> Yeah, and you know, the practitioners again, pay attention to also to the cloud networking interviews. Lot of change going on there that's going to be disruptive and actually change the landscape as well. Again, as Supercloud progresses to be the next big thing. If you're not on this next wave, you'll drift what, as Pat Gelsinger says. >> Yep. >> To kick off the closing segments, George, Dave, this is a wave that's been identified. Again, people debate the word all you want Supercloud. It is a gateway to multicloud eventually it is the standard for new applications, new ways to do data. There's new computer science being generated and customer requirements being addressed. So it's the confluence of, you know, tectonic plates shifting in the industry, new computer science seeing things like AI and machine learning and data at the center of it and new infrastructure all kind of coming together. So, to me, that's my takeaway so far. That is the big story and it's going to change society and ultimately the business models of these companies. >> Well, we've had 10, you know, you think about it we came out of the financial crisis. We've had 10, 12 years despite the Covid of tech success, right? And just now CIOs are starting to hit the brakes. And so my point is you've had all this innovation building up for a decade and you've got this massive ecosystem that is running on the cloud and the ecosystem is saying, hey, we can have even more value by tapping best of of breed across clouds. And you've got customers saying, hey, we need help. We want to do more and we want to point our business and our intellectual property, our software tooling at our customers and monetize our data. So you have all these forces coming together and it's sort of entering a new era. >> George, I want to go to you for a second because you are big contributor to this event. Your interview with Bob Moglia with Dave was I thought a watershed moment for me to hear that the data apps, how databases are being rethought because we've been seeing a diversity of databases with Amazon Web services, you know, promoting no one database rules of the world. Now it's not one database kind of architecture that's puling these new apps. What's your takeaway from this event? >> So if you keep your eye on this North Star where instead of building apps that are based on code you're building apps that are defined by data coming off of things that are linked to the real world like people, places, things and activities. Then the idea is, and the example we use is, you know, Uber but it could be, you know, amazon.com is defined by stuff coming off data in the Amazon ecosystem or marketplace. And then the question is, and everyone was talking at different angles on this, which was, where's the data live? How much do you hide from the developer? You know, and when can you offer that? You know, and you started with Walmart which was describing apps, traditional apps that are just code. And frankly that's easier to make that cross cloud and you know, essentially location independent. As soon as you have data you need data management technology that a customer does not have the sophistication to build. And then the argument was like, so how much can you hide from the developer who's building data apps? Tristan's version was you take the modern data stack and you start adding these APIs that define business concepts like bookings, billings and revenue, you know, or in the Uber example like drivers and riders, you know, and ETA's and prices. But those things execute still on the data warehouse or data lakehouse. Then Bob Muglia was saying you're not really hiding enough from the developer because you still got to say how to do all that. And his vision is not only do you hide where the data is but you hide how to sort of get at all that code by just saying what you want. You define how a car and how a driver and how a rider works. And then those things automatically figure out underneath the cover. >> So huge challenges, right? There's governance, there's security, they could be big blockers to, you know, the Supercloud but the industry's going to be attacking that problem. >> Well, what's your take? What's your favorite segment? Zhamak Dehghani came on, she's starting in that company, exclusive news. That was big notable moment for theCUBE. She launched her company. She pioneered the data mesh concept. And I think what George is saying and what data mesh points to is something that we've been saying for a long time. That data is now going to flip the script on how apps behave. And the Uber example I think is illustrated 'cause people can relate to Uber. But imagine that for every business whether it's a manufacturing business or retail or oil and gas or FinTech, they can look at their business like a game almost gamify it with data, riders, cars you know, moving data around the value of data. This is something that Adam Selipsky teased out at AWS, Dave. So what's your takeaway from this Supercloud? Where are we in your mind? Well big thing is data products and decentralizing your data architecture, but putting data in the hands of domain experts who can actually monetize the data. And I think that's, to me that's really exciting. Because look, data products financial industry has always been doing building data products. Mortgage backed securities is a data product. But why should the financial industry have all the fun? I mean virtually every organization can tap its ecosystem build data products, take its internal IP and processes and software and point it to the world and actually begin to make money out of it. >> Okay, so let's go around the horn. I'll start, I'll get you guys some time to think. Next question, what did you learn today? I learned that I think it's an infrastructure game and talking to Kit Colbert at VMware, I think it's all about infrastructure refactoring and I think the data's going to be an ingredient that's going to be operating system like. I think you're going to see the infrastructure influencing operations that will enable Superclouds to be real. And developers won't even know what a Supercloud is because they'll be using it. It's the operations focus is going to be very critical. Just like DevOps movements started Cloud native I think you're going to see a data native movement and I think infrastructure is critical as people go to the next level. That's my big takeaway today. And I'll say the data conversation is at the center. I think security, data are going to be always active horizontally scalable concepts, but every company's going to reset their infrastructure, how it looks and if it's not set up for data and or things that there need to be agile on, it's going to be a non-starter. So I think that's the cloud NextGen, distributed computing. >> I mean, what came into focus for me was I think the hyperscaler is going to continue to do their thing, you know, and be very, very successful and they're each coming at it from different approaches. We talk about this all the time in theCUBE. Amazon the best infrastructure, you know, Google's got its you know, data and AI thing and it's playing catch up and Microsoft's got this massive estate. Okay, cool. Check. The next wave of innovation which is coming from data, I've always said follow the data. That's where the where the money's going to be is going to come from other places. People want to be able to, organizations want to be able to share data across clouds across their organization, outside of their ecosystem and make money with that data sharing. They don't want to FTP it anymore. I got it. You take it. They want to work with live data in real time and I think the edge, we didn't talk much about the edge today is going to even take that to a new level real time inferencing at the edge, AI and and being able to do new things with data that we haven't even seen. But playing around with ChatGPT, it's blowing our mind. And I think you're right, it's like when we first saw the browser, holy crap, this is going to change the world. >> Yeah. And the ChatGPT by the way is going to create a wave of machine learning and data refactoring for sure. But also Howie Liu had an interesting comment, he was asked by a VC how much to replicate that and he said it's in the hundreds of millions, not billions. Now if you asked that same question how much does it cost to replicate AWS? The CapEx alone is unstoppable, they're already done. So, you know, the hyperscalers are going to continue to boom. I think they're going to drive the infrastructure. I think Amazon's going to be really strong at silicon and physics and squeeze every ounce atom out of every physical thing and then get latency as your bottleneck and the rest is all going to be... >> That never blew me away, a hundred million to create kind of an open AI, you know, competitor. Look at companies like Lacework. >> John: Some people have that much cash on the balance sheet. >> These are security companies that have raised a billion dollars, right? To compete. You know, so... >> If you're not shifting left what do you do with data, shift up? >> But, you know. >> What did you learn, George? >> I'm listening to you and I think you're helping me crystallize something which is the software infrastructure to enable the data apps is wide open. The way Zhamak described it is like if you want a data product like a sales and operation plan, that is built on other data products, like a sales plan which has a forecast in it, it has a production plan, it has a procurement plan and then a sales and operation plan is actually a composition of all those and they call each other. Now in her current platform, you need to expose to the developer a certain amount of mechanics on how to move all that data, when to move it. Like what happens if something fails. Now Muglia is saying I can hide that completely. So all you have to say is what you want and the underlying machinery takes care of everything. The problem is Muglia stuff is still a few years off. And Tristan is saying, I can give you much of that today but it's got to run in the data warehouse. So this trade offs all different ways. But again, I agree with you that the Cloud platform vendors or the ecosystem participants who can run across Cloud platforms and private infrastructure will be the next platform. And then the cloud platform is sort of where you run the big honking centralized stuff where someone else manages the operations. >> Sounds like middleware to me, Dave >> And key is, I'll just end with this. The key is being able to get to the data, whether it's in a data warehouse or a data lake or a S3 bucket or an object store, Oracle database, whatever. It's got to be inclusive that is critical to execute on the vision that you just talked about 'cause that data's in different systems and you're not going to put it all into some new system. >> So creating middleware in the cloud that sounds what it sounds like to me. >> It's like, you discovered PaaS >> It's a super PaaS. >> But it's platform services 'cause PaaS connotes like a tightly integrated platform. >> Well this is the real thing that's going on. We're going to see how this evolves. George, great to have you on, Dave. Thanks for the summary. I enjoyed this segment a lot today. This ends our stage performance live here in Palo Alto. As you know, we're live stage performance and syndicate out virtually. Our afternoon program's going to kick in now you're going to hear some great interviews. We got ChaosSearch. Defining the network Supercloud from prosimo. Future of Cloud Network, alkira. We got Saks, a retail company here, Veronika Durgin. We got Dave with Western Union. So a lot of customers, a pharmaceutical company Warner Brothers, Discovery, media company. And then you know, what is really needed for Supercloud, good panels. So stay with us for the afternoon program. That's part two of Supercloud 2. This is a wrap up for our stage live performance. I'm John Furrier with Dave Vellante and George Gilbert here wrapping up. Thanks for watching and enjoy the program. (bright music)

(upbeat music) >> Hey, everyone, welcome back to Las Vegas, "theCube" is on our fourth day of covering AWS re:Invent, live from the Venetian Expo Center. This week has been amazing. We've created a ton of content, as you know, 'cause you've been watching. But, there's been north of 55,000 people here, hundreds of thousands online. We've had amazing conversations across the AWS ecosystem. Lisa Martin, Paul Gillan. Paul, what's your, kind of, take on day four of the conference? It's still highly packed. >> Oh, there's lots of people here. (laughs) >> Yep. Unusual for the final day of a conference. I think Werner Vogels, if I'm pronouncing it right kicked things off today when he talked about asymmetry and how the world is, you know, asymmetric. We build symmetric software, because it's convenient to do so, but asymmetric software actually scales and evolves much better. And I think that that was a conversation starter for a lot of what people are talking about here today, which is how the cloud changes the way we think about building software. >> Absolutely does. >> Our next guest, Holger Mueller, that's one of his key areas of focus. And Holger, welcome, thanks for joining us on the "theCube". >> Thanks for having me. >> What did you take away from the keynote this morning? >> Well, how do you feel on the final day of the marathon, right? We're like 23, 24 miles. Hit the ball yesterday, right? >> We are going strong Holger. And, of course, >> Yeah. >> you guys, we can either talk about business transformation with cloud or the World Cup. >> Or we can do both. >> The World Cup, hands down. World Cup. (Lisa laughs) Germany's out, I'm unbiased now. They just got eliminated. >> Spain is out now. >> What will the U.S. do against Netherlands tomorrow? >> They're going to win. What's your forecast? U.S. will win? >> They're going to win 2 to 1. >> What do you say, 2:1? >> I'm optimistic, but realistic. >> 3? >> I think Netherlands. >> Netherlands will win? >> 2 to nothing. >> Okay, I'll vote for the U.S.. >> Okay, okay >> 3:1 for the U.S.. >> Be optimistic. >> Root for the U.S.. >> Okay, I like that. >> Hope for the best wherever you work. >> Tomorrow you'll see how much soccer experts we are. >> If your prediction was right. (laughs) >> (laughs) Ja, ja. Or yours was right, right, so. Cool, no, but the event, I think the event is great to have 50,000 people. Biggest event of the year again, right? Not yet the 70,000 we had in 2019. But it's great to have the energy. I've never seen the show floor going all the way down like this, right? >> I haven't either. >> I've never seen that. I think it's a record. Often vendors get the space here and they have the keynote area, and the entertainment area, >> Yeah. >> and the food area, and then there's an exposition, right? This is packed. >> It's packed. >> Maybe it'll pay off. >> You don't see the big empty booths that you often see. >> Oh no. >> Exactly, exactly. You know, the white spaces and so on. >> No. >> Right. >> Which is a good thing. >> There's lots of energy, which is great. And today's, of course, the developer day, like you said before, right now Vogels' a rockstar in the developer community, right. Revered visionary on what has been built, right? And he's becoming a little professorial is my feeling, right. He had these moments before too, when it was justifying how AWS moved off the Oracle database about the importance of data warehouses and structures and why DynamoDB is better and so on. But, he had a large part of this too, and this coming right across the keynotes, right? Adam Selipsky talking about Antarctica, right? Scott against almonds and what went wrong. He didn't tell us, by the way, which often the tech winners forget. Scott banked on technology. He had motorized sleds, which failed after three miles. So, that's not the story to tell the technology. Let everything down. Everybody went back to ponies and horses and dogs. >> Maybe goes back to these asynchronous behavior. >> Yeah. >> The way of nature. >> And, yesterday, Swami talking about the bridges, right? The root bridges, right? >> Right. >> So, how could Werner pick up with his video at the beginning. >> Yeah. >> And then talk about space and other things? So I think it's important to educate about event-based architecture, right? And we see this massive transformation. Modern software has to be event based, right? Because, that's how things work and we didn't think like this before. I see this massive transformation in my other research area in other platforms about the HR space, where payrolls are being rebuilt completely. And payroll used to be one of the three peaks of ERP, right? You would size your ERP machine before the cloud to financial close, to run the payroll, and to do an MRP manufacturing run if you're manufacturing. God forbid you run those three at the same time. Your machine wouldn't be able to do that, right? So it was like start the engine, start the boosters, we are running payroll. And now the modern payroll designs like you see from ADP or from Ceridian, they're taking every payroll relevant event. You check in time wise, right? You go overtime, you take a day of vacation and right away they trigger and run the payroll, so it's up to date for you, up to date for you, which, in this economy, is super important, because we have more gig workers, we have more contractors, we have employees who are leaving suddenly, right? The great resignation, which is happening. So, from that perspective, it's the modern way of building software. So it's great to see Werner showing that. The dirty little secrets though is that is more efficient software for the cloud platform vendor too. Takes less resources, gets less committed things, so it's a much more scalable architecture. You can move the events, you can work asynchronously much better. And the biggest showcase, right? What's the biggest transactional showcase for an eventually consistent asynchronous transactional application? I know it's a mouthful, but we at Amazon, AWS, Amazon, right? You buy something on Amazon they tell you it's going to come tomorrow. >> Yep. >> They don't know it's going to come tomorrow by that time, because it's not transactionally consistent, right? We're just making every ERP vendor, who lives in transactional work, having nightmares of course, (Lisa laughs) but for them it's like, yes we have the delivery to promise, a promise to do that, right? But they come back to you and say, "Sorry, we couldn't make it, delivery didn't work and so on. It's going to be a new date. We are out of the product.", right? So these kind of event base asynchronous things are more and more what's going to scale around the world. It's going to be efficient for everybody, it's going to be better customer experience, better employee experience, ultimately better user experience, it's going to be better for the enterprise to build, but we have to learn to build it. So big announcement was to build our environment to build better eventful applications from today. >> Talk about... This is the first re:Invent... Well, actually, I'm sorry, it's the second re:Invent under Adam Selipsky. >> Right. Adam Selipsky, yep. >> But his first year. >> Right >> We're hearing a lot of momentum. What's your takeaway with what he delivered with the direction Amazon is going, their vision? >> Ja, I think compared to the Jassy times, right, we didn't see the hockey stick slide, right? With a number of innovations and releases. That was done in 2019 too, right? So I think it's a more pedestrian pace, which, ultimately, is good for everybody, because it means that when software vendors go slower, they do less width, but more depth. >> Yeah. >> And depth is what customers need. So Amazon's building more on the depth side, which is good news. I also think, and that's not official, right, but Adam Selipsky came from Tableau, right? >> Yeah. So he is a BI analytics guy. So it's no surprise we have three data lake offerings, right? Security data lake, we have a healthcare data lake and we have a supply chain data lake, right? Where all, again, the epigonos mentioned them I was like, "Oh, my god, Amazon's coming to supply chain.", but it's actually data lakes, which is an interesting part. But, I think it's not a surprise that someone who comes heavily out of the analytics BI world, it's off ringside, if I was pitching internally to him maybe I'd do something which he's is familiar with and I think that's what we see in the major announcement of his keynote on Tuesday. >> I mean, speaking of analytics, one of the big announcements early on was Amazon is trying to bridge the gap between Aurora. >> Yep. >> And Redshift. >> Right. >> And setting up for continuous pipelines, continuous integration. >> Right. >> Seems to be a trend that is common to all database players. I mean, Oracle is doing the same thing. SAP is doing the same thing. MariaDB. Do you see the distinction between transactional and analytical databases going away? >> It's coming together, right? Certainly coming together, from that perspective, but there's a fundamental different starting point, right? And with the big idea part, right? The universal database, which does everything for you in one system, whereas the suite of specialized databases, right? Oracle is in the classic Oracle database in the universal database camp. On the other side you have Amazon, which built a database. This is one of the first few Amazon re:Invents. It's my 10th where there was no new database announced. Right? >> No. >> So it was always add another one specially- >> I think they have enough. >> It's a great approach. They have enough, right? So it's a great approach to build something quick, which Amazon is all about. It's not so great when customers want to leverage things. And, ultimately, which I think with Selipsky, AWS is waking up to the enterprise saying, "I have all this different database and what is in them matters to me." >> Yeah. >> "So how can I get this better?" So no surprise between the two most popular database, Aurora and RDS. They're bring together the data with some out of the box parts. I think it's kind of, like, silly when Swami's saying, "Hey, no ETL.". (chuckles) Right? >> Yeah. >> There shouldn't be an ETL from the same vendor, right? There should be data pipes from that perspective anyway. So it looks like, on the overall value proposition database side, AWS is moving closer to the universal database on the Oracle side, right? Because, if you lift, of course, the universal database, under the hood, you see, well, there's different database there, different part there, you do something there, you have to configure stuff, which is also the case but it's one part of it, right, so. >> With that shift, talk about the value that's going to be in it for customers regardless of industry. >> Well, the value for customers is great, because when software vendors, or platform vendors, go in depth, you get more functionality, you get more maturity you get easier ways of setting up the whole things. You get ways of maintaining things. And you, ultimately, get lower TCO to build them, which is super important for enterprise. Because, here, this is the developer cloud, right? Developers love AWS. Developers are scarce, expensive. Might not be want to work for you, right? So developer velocity getting more done with same amount of developers, getting less done, less developers getting more done, is super crucial, super important. So this is all good news for enterprise banking on AWS and then providing them more efficiency, more automation, out of the box. >> Some of your customer conversations this week, talk to us about some of the feedback. What's the common denominator amongst customers right now? >> Customers are excited. First of all, like, first event, again in person, large, right? >> Yeah. >> People can travel, people meet each other, meet in person. They have a good handle around the complexity, which used to be a huge challenge in the past, because people say, "Do I do this?" I know so many CXOs saying, "Yeah, I want to build, say, something in IoT with AWS. The first reference built it like this, the next reference built it completely different. The third one built it completely different again. So now I'm doubting if my team has the skills to build things successfully, because will they be smart enough, like your teams, because there's no repetitiveness and that repetitiveness is going to be very important for AWS to come up with some higher packaging and version numbers.", right? But customers like that message. They like that things are working better together. They're not missing the big announcement, right? One of the traditional things of AWS would be, and they made it even proud, as a system, Jassy was saying, "If we look at the IT spend and we see something which is, like, high margin for us and not served well and we announced something there, right?" So Quick Start, Workspaces, where all liaisons where AWS went after traditional IT spend and had an offering. We haven't had this in 2019, we don't have them in 2020. Last year and didn't have it now. So something is changing on the AWS side. It's a little bit too early to figure out what, but they're not chewing off as many big things as they used in the past. >> Right. >> Yep. >> Did you get the sense that... Keith Townsend, from "The CTO Advisor", was on earlier. >> Yep. >> And he said he's been to many re:Invents, as you have, and he said that he got the sense that this is Amazon's chance to do a victory lap, as he called it. That this is a way for Amazon to reinforce the leadership cloud. >> Ja. >> And really, kind of, establish that nobody can come close to them, nobody can compete with them. >> You don't think that- >> I don't think that's at all... I mean, love Keith, he's a great guy, but I don't think that's the mindset at all, right? So, I mean, Jassy was always saying, "It's still the morning of the day in the cloud.", right? They're far away from being done. They're obsessed over being right. They do more work with the analysts. We think we got something right. And I like the passion, from that perspective. So I think Amazon's far from being complacent and the area, which is the biggest bit, right, the biggest. The only thing where Amazon truly has floundered, always floundered, is the AI space, right? So, 2018, Werner Vogels was doing more technical stuff that "Oh, this is all about linear regression.", right? And Amazon didn't start to put algorithms on silicon, right? And they have a three four trail and they didn't announce anything new here, behind Google who's been doing this for much, much longer than TPU platform, so. >> But they have now. >> They're keen aware. >> Yep. >> They now have three, or they own two of their own hardware platforms for AI. >> Right. >> They support the Intel platform. They seem to be catching up in that area. >> It's very hard to catch up on hardware, right? Because, there's release cycles, right? And just the volume that, just talking about the largest models that we have right now, to do with the language models, and Google is just doing a side note of saying, "Oh, we supported 50 less or 30 less, not little spoken languages, which I've never even heard of, because they're under banked and under supported and here's the language model, right? And I think it's all about little bit the organizational DNA of a company. I'm a strong believer in that. And, you have to remember AWS comes from the retail side, right? >> Yeah. >> Their roll out of data centers follows their retail strategy. Open secret, right? But, the same thing as the scale of the AI is very very different than if you take a look over at Google where it makes sense of the internet, right? The scale right away >> Right. >> is a solution, which is a good solution for some of the DNA of AWS. Also, Microsoft Azure is good. There has no chance to even get off the ship of that at Google, right? And these leaders with Google and it's not getting smaller, right? We didn't hear anything. I mean so much focused on data. Why do they focus so much on data? Because, data is the first step for AI. If AWS was doing a victory lap, data would've been done. They would own data, right? They would have a competitor to BigQuery Omni from the Google side to get data from the different clouds. There's crickets on that topic, right? So I think they know that they're catching up on the AI side, but it's really, really hard. It's not like in software where you can't acquire someone they could acquire in video. >> Not at Core Donovan. >> Might play a game, but that's not a good idea, right? So you can't, there's no shortcuts on the hardware side. As much as I'm a software guy and love software and don't like hardware, it's always a pain, right? There's no shortcuts there and there's nothing, which I think, has a new Artanium instance, of course, certainly, but they're not catching up. The distance is the same, yep. >> One of the things is funny, one of our guests, I think it was Tuesday, it was, it was right after Adam's keynote. >> Sure. >> Said that Adam Selipsky stood up on stage and talked about data for 52 minutes. >> Yeah. Right. >> It was timed, 52 minutes. >> Right. >> Huge emphasis on that. One of the things that Adam said to John Furrier when they were able to sit down >> Yeah >> a week or so ago at an event preview, was that CIOs and CEOs are not coming to Adam to talk about technology. They want to talk about transformation. They want to talk about business transformation. >> Sure, yes, yes. >> Talk to me in our last couple of minutes about what CEOs and CIOs are coming to you saying, "Holger, help us figure this out. We have to transform the business." >> Right. So we advise, I'm going quote our friends at Gartner, once the type A company. So we'll use technology aggressively, right? So take everything in the audience with a grain of salt, followers are the laggards, and so on. So for them, it's really the cusp of doing AI, right? Getting that data together. It has to be in the cloud. We live in the air of infinite computing. The cloud makes computing infinite, both from a storage, from a compute perspective, from an AI perspective, and then define new business models and create new best practices on top of that. Because, in the past, everything was fine out on premise, right? We talked about the (indistinct) size. Now in the cloud, it's just the business model to say, "Do I want to have a little more AI? Do I want a to run a little more? Will it give me the insight in the business?". So, that's the transformation that is happening, really. So, bringing your data together, this live conversation data, but not for bringing the data together. There's often the big win for the business for the first time to see the data. AWS is banking on that. The supply chain product, as an example. So many disparate systems, bring them them together. Big win for the business. But, the win for the business, ultimately, is when you change the paradigm from the user showing up to do something, to software doing stuff for us, right? >> Right. >> We have too much in this operator paradigm. If the user doesn't show up, doesn't find the click, doesn't find where to go, nothing happens. It can't be done in the 21st century, right? Software has to look over your shoulder. >> Good point. >> Understand one for you, autonomous self-driving systems. That's what CXOs, who're future looking, will be talked to come to AWS and all the other cloud vendors. >> Got it, last question for you. We're making a sizzle reel on Instagram. >> Yeah. >> If you had, like, a phrase, like, or a 30 second pitch that would describe re:Invent 2022 in the direction the company's going. What would that elevator pitch say? >> 30 second pitch? >> Yeah. >> All right, just timing. AWS is doing well. It's providing more depth, less breadth. Making things work together. It's catching up in some areas, has some interesting offerings, like the healthcare offering, the security data lake offering, which might change some things in the industry. It's staying the course and it's going strong. >> Ah, beautifully said, Holger. Thank you so much for joining Paul and me. >> Might have been too short. I don't know. (laughs) >> About 10 seconds left over. >> It was perfect, absolutely perfect. >> Thanks for having me. >> Perfect sizzle reel. >> Appreciate it. >> We appreciate your insights, what you're seeing this week, and the direction the company is going. We can't wait to see what happens in the next year. And, yeah. >> Thanks for having me. >> And of course, we've been on so many times. We know we're going to have you back. (laughs) >> Looking forward to it, thank you. >> All right, for Holger Mueller and Paul Gillan, I'm Lisa Martin. You're watching "theCube", the leader in live enterprise and emerging tech coverage. (upbeat music)

(upbeat music) >> Welcome back to theCUBE's live coverage of AWS re:Invent. Friends, it's good to see you. Lisa Martin here with Dave Vellante. This is our fourth day of CUBE wall-to-wall coverage, Dave. I can't believe it. And the expo hall is still going incredibly strong. >> Yeah, it is. It feels like the biggest re:Invent ever. I'm told it's almost as big as 2019. I don't know, maybe I was half asleep at 2019. That's very possible. But I'm excited because in 2017 Andy Jassy came on theCUBE and he said if Amazon had to do it all over again, if it knew then what it had now, we would've done the whole thing in containers or using Lambda, using serverless and using containers. Didn't have that opportunity back then. And I'm excited 'cause Rafay Systems is someone we've worked with a lot as an innovator in this space. >> Yep, and we're going to be talking with Rafay again. I think it's your 10th time Haseeb on the show >> Like once or twice. >> And a great customer who's going to talk about their serverless journey. Haseeb Budhani joins us once again, the CEO of Rafay. Great to see you. Rakesh Singh is here as well, the Head of Cloud and DevOps at Regeneron. Guys, it's great to have you on the program. How you feeling on day four of re:Invent? >> Excitement is as high as ever basically. >> Isn't it amazing? >> Rakesh: That's true. >> Haseeb: I just need some sleep. >> I'm with you on that. Caffeine and sleep. >> So many parties. So many meetings, oh my God. >> But the great thing is, Haseeb, that people want to engage with you. They're loving what Rafay is doing. You guys are a great testament to that, which we're going to uncover on the show. What are some of the things that you're hearing in the booth from customers? What's been some of the feedback? >> So firstly, as I said, it feels like the biggest one ever. I've been coming to re:Invent a long time and I mean, I know the numbers say it's not, but oh my God, this is a lot of people. Every time we've spoken over the last year and the point I always make to you, and we've spoken enough time about this is that enterprises are truly adopting this idea of Kubernetes containers, serverless, et cetera. And they're all trying to figure out what is the enterprise strategy for these things? They're thinking beyond technology and thinking operationalization of these technologies. And that's not the same thing. There's a toy and then there's the real thing. And that's not the same thing. And that's the gap that every enterprise customer I talked to and the booth traffic has been just amazing. I mean, but coming here I was thinking, my God, this is really expensive. And I'm thinking, wow, this is a great investment. Because we met such amazing companies who all essentially are saying exactly the same thing, which is as we go and productize and bring our high value applications to the modern infrastructure space, like Kubernetes, Lambda, et cetera, solving for the automation governance is really, really hard because, well, at one point, I guess when the economy was doing crazy well, I could keep hiring people, but I can't do that anymore either. So they're out looking for automation strategies that allow them to do more with the teams they have. And that's exactly what Rafay is here for. >> Yeah. Lisa, Adam Selipsky in his keynote, I love the, he said, "If you want to save money, the cloud is the place to do it." >> Exactly. Yep. Let's talk about Regeneron. Everyone knows it's a household word especially over the last couple of years, but talk about, Rakesh, Regeneron as a technology company that delivers life-saving pharmaceuticals. And where does cloud and Rafay fit into your strategy? >> So cloud has been a backbone of our compute strategy within Regeneron for a very long time now. The evolution from a traditional compute structure to more serverless compute has been growing at a rapid pace. And I would say like we are seeing exponential growth within the adaption of the compute within containers and Kubernetes world. So we've been on this journey for a long time and I think it's not stopping anytime soon. So we have more and more workload, which is running on Kubernetes containers and we are looking forward to our partnership with Rafay to further enhance it, as Haseeb mentioned, the efficiency is the key. We need to do more with less. Resourcing is critical and cloud is evolved from that journey that do more things in a more efficient manner. >> That was the original catalyst as we got to help our development team, be more productive. >> That's correct. >> Eliminate the heavy lifting. And then you started presumably doing some of the less heavy, but still heavy lifting and we talked off camera and then you're increasingly moving toward serverless. >> Rakesh: That's correct. >> Can you describe that journey? What that's like? >> So I think like with the whole adoption that things are taking a much faster pace. Basically we are putting more compute onto containers and the DevOps journey is increasingly getting more, more faster. >> Go ahead. 'Cause I want to understand where Rafay sits in this whole equation. I was talking about, I'm not a developer, but I was talking to developer yesterday trying to really understand the benefits of containers and serverless and I said, take me through what you have to do when you're using containers. He said, I got to build the container image then I got to deploy an EC2 instance where I got to choose and I got to allocate memory of the fence the app in a VM then I got to run the computing instance against the app. And then, oh by the way, I got to pay 'cause all that EC2 that whole time. Depending on how you approach serverless you're going to eliminate a lot of those steps. >> That is correct. So what we do is basically like in a traditional sense, the computer is sitting idle at quite a lot basically. >> But you're paying. >> And you're still paying for that. Serverless technologies allows us to use the compute as needed basis. So whenever you need it, it is available. You run your workload on that and after that it shuts down or goes to minimal state and you don't need to pay as much as your paying. >> And then where do you guys fit in that whole equation? >> Look, serverless has a paradigm. If you step back from the idea of containers versus Lambda or whatever functions. The idea should be that the list you just read out of what developers have to do. Here's what they really should do. They should write their code, they should check it in, and they never have to think about it again. That should be the case. If they want to debug their application, there should be a nice front end where they go and they interact with their application and that's it. What is Kubernetes? I don't care. That's the right answer. And we did not start this journey as an industry there because usually the initial adopters are developers who do the heavy lifting. Developers want to learn, they want to solve these problems. But then eventually the expectation is that the platform organization and an enterprise is going to own this platform for me so I can go back to doing my job, which is writing code. And that's where Rakesh's team comes in. So Rakesh team is building the standard at Regeneron. Whether you're writing a long-lasting app, which is going to run in a container or you're going to write an event-driven application, which is going to be a function, whatever. You write your app, we will give you the necessary tooling and plumbing to take care of all these things. And this is my problem. My being Rakesh. Rakesh is my customer. He has his customers. We as Rafay, A, we have to make Rakesh's system successful because we have to give them right automation to do all these things so that he can service hundred, or in his case, thousands and thousands of different individuals. But then collectively, we have to make sure that the developer experience is optimal so that truly they just write their code and EC2, they don't want to deal with this. In fact, on Monday evening, in the Kubernetes keynote by Barry Cooks, one of the things he said was that in a CIO sort of survey they did, CIO said, 80% of the time of developers is wasted on infrastructure stuff and not on innovation. We need to bring that 80% back so that a hundred percent of the work is on innovation and today it's not. >> And that's what you do. >> That's what we do. >> In your world as a developer, I only have to worry about my writing my code and what functions I'm going to call. >> That is correct. And it is important because the efficiencies of a developer need to be focused on doing the things which business is asking for. The 80% of the work like to make sure the things are secure, they're done the right way, the standards are followed, scanning part of it, that work if we can offload to a platform, for example, Rafay, saves a lot of works, a lot of work cycles from the developers perspective. >> Thank you for that. It was nice little tutorial on the benefits. >> Absolutely. So you transform the developer experience. >> That's correct. >> How does that impact Regeneron overall business? We uplevel that. Give me that view. >> So with that, like what happens, the key thing is the developers productivity increases. We are able to do more with less. And that is the key thing to our strategy that like with the increase in business demand, with the increase in lot of compute things, which we are doing, we need to do and hiring resources is getting more difficult than ever. And we need to make sure that we are leveraging platforms and tools basically to do, enable our developers to focus on key business activity rather than doing redundant things and things which we can leverage some other tooling and platform for that business. >> Is this something in terms of improving the developer experience and their productivity faster time to market? Is this accelerating? >> That's correct. >> Is this even like accelerating drug discovery in some cases? >> So COVID is like a great example for that. Like we were able to fast track our drug discovery and like we were able to turn it into an experience where we were able to discover new drugs and get it to the market in a much faster pace. That whole process was expedited using these tools and processes basically. So we are very proud of that. >> So my understanding is you're running Rafay with EKS. A lot of choices out there. Why? Why did you choose to go in that direction? >> So Regeneron has heavily invested in cloud recently, over the years basically. And then we are focusing on hybrid cloud now that we we are like, again, these multiple cloud providers of platforms which are coming in are strategies to focus on hybrid cloud and Rafay is big leader in that particular space where we felt that we need to engage or partner with Rafay to enable those capabilities, not just on AWS, but across the board. One single tool, one single process, one single knowledge base helps us achieve more efficiencies. >> Less chaos, less complexity. >> That's correct. Let's say when you're in customer conversations, which I know you've had many this week, but you probably do that all the time. Regeneron is a great use case for Rafay. It's so tangible, life sciences. We all get that, especially coming out of the pandemic. What do you say to customers are the top three differentiators of Rafay and why they should go Rafay on top of EKS? >> What's really interesting about these conversations is that, look, we have some pretty cool features in our product. Obviously we must have something interesting otherwise nobody would buy our product. And we have access management and zero trust models and cluster provisioning, all these very nice things. But it always comes down to exactly the same thing, which is every large enterprise that started a journey, independent or Rafay because they didn't know who we were, it's fine. Last year we were a young company, now we are a larger company and they all are basically building towards a roadmap which Rafay truly understands. And in my opinion, and I'm confident when I say this, we understand their life, their journey better than any other company in the market. The reason why we have the flurry of customers we have, the reason why the product has the capacity that it does is because for whatever reason, look, it's scale lock. That's for the history books. But we have complete clarity on what a pharmaceutical company or financial customers company or a high tech company the journey they will take to the cloud and automation for modern infrastructure, we get it. And what I'm selling them is the is the why, not the what. There's a lot of great answers for the what? What do we do? Rakesh doesn't care. I mean, he's trying to solve a bigger problem. He's trying to get his researchers to go faster. So then when they want to run a model, they should be able to do it right now. That's what he cares about. Then he looks for a tool to solve the business problem. And we figured out how to have that conversation and explain why Rafay helps him, essentially multiply the bandwidth that he has in his organization. And of course to that end we have some great technology/ But that's a secondary issue, the first, to me the why is more important than the what. And then we talk about how, which he has to pay us money. That's the how. But yeah, we get there too. But look, this is the important thing. Every enterprise is on exactly the same journey, Lisa. And that if you think about it from just purely economic efficiencies perspective that is not a good investment for our industry. If everybody's solving the same problem that's a waste of resources. Let's find a way to do, what is the point of the cloud? We used to all build data centers. That was not efficient. We all went to the cloud because it's more efficient to have somebody else, AWS, solve this problem for us so we can now focus on the next level problem. And then Rafay solving that problem so that he can focus on his drug discovery, not on Kubernetes. >> That's correct. It's all about efficiencies. Like doing things, learn from each other's experience and build upon it. So the things have been solved. One way you need to leverage that, reuse it. So the principles are the same. >> So then what's next? You had done an amazing job transforming the company. You're facilitating drug discovery faster than ever before. From an infrastructure perspective, what's next on your journey? >> So right now the roadmap what we have is basically talking about making sure that the workload are running more efficient, they're more secure. As we go into these expandable serverless technology, there are more challenging opportunities for us to solve. Those challenges are coming up. We need to make sure that with the new, the world we are living in, we are more securely doing stuff what we were doing previously. More efficiencies is also the key and more distributed. Like if we can leverage the power of cloud in doing more things on demand is on our roadmap. And I think that is where we are all driving. >> And when you said hybrid, you're talking about connecting to your on-prem tools and data? How about cross cloud? >> We are invested in multiple cloud platform itself and we are looking forward to leveraging a technology, which is truly cloud native and we can leverage things together on that. >> And I presume you're helping with that, obviously. >> Last question for both of you. We're making an Instagram reel. Think of this as a sizzle reel, like a 32nd elevator pitch. Question, first one goes to you, Rakesh. If you had a bumper sticker, you put it on, I don't know, say a DeLorean, I hear those are coming back. What would it say about Regeneron as a technology company that's delivering therapeutics? >> It's a tough question, but I would try my best. The bumper sticker would say, discover drug more faster, more efficient. >> Perfect. Haseeb, question about Rafay. What's the bumper sticker? If you had a billboard in on Highway 101 in Redwood City about Rafay and what it's enabling organizations enterprises across the globe to achieve, what would it say? >> I'll tell you what our customers say. So our customers call us the vCenter for Kubernetes and we all know what a vCenter is. We all know why vCenter's so amazingly successful because it takes IT engineers and gives them superpowers. You can run a data center. What is the vCenter for this new world? It us. So vCenter is obviously a trademark with our friends at VMware, so that's why I'm, but our customers truly call us the vCenter for Kubernetes. And I think that's an incredible moniker because that truly codifies our roadmap. It codifies what we are selling today. >> There's nothing more powerful and potent in the voice of the customer. Thank you both for coming on. Thank you for sharing the Regeneron story. Great to have you back on, Haseeb. You need a pin for the number of times you've been on theCUBE. >> At least a gold star. >> We'll work on that. Guys, thank you. We appreciate your time. >> Haseeb: Thank you very much. >> For our guests and for Dave Vellante, I'm Lisa Martin. You're watching theCUBE, the leader in live enterprise and emerging tech coverage. (upbeat music)

(bright music) >> Welcome back to Vegas, guys and girls. We're pleased that you're watching theCUBE. We know you've been with us. This is our fourth day. We know you've been with us since day one. Why wouldn't you be? Lisa Martin, here. As I mentioned, day four of theCUBE's coverage of AWS re:Invent. There are north of 55,000 people that have been at this event this week. We're hearing hundreds of thousands online. It really feels like old times, which is awesome. We're pleased to welcome back a gentleman from Dataiku who's actually new to theCUBE but Dataiku is not. Jed Dougherty is here, the VP of Platform Strategy. Thanks to joining me today, Jed. >> Oh, I'm so happy to be here. >> Talk a little bit, for anybody that isn't familiar with Dataiku, tell the audience a little bit about the technology, what you guys do. >> Dataiku is an end-to-end data science machine learning platform. We take everything from data ingestion, piplining of that data, bringing it all together, something that's useful for building models, deploying those models and then managing your ML ops workflow. So, really all the way across. And we sit on top of, basically, tons of different AWS stack as well as lots of the partners that are here today. >> Okay, got it. >> Snowflake, Databricks, all that. >> Got it, so one of the things that, it was funny, I think it was Adam's keynote Tuesday morning. I didn't time it, I watched it, but one of my guests said to me earlier this week that Adam spent exactly 52 minutes talking about data. >> Yeah. >> 52 minutes. Obviously, we can't come to an event like this without talking about data. Every company these days has to be a data company. Whether it's my grocery store or a retailer, a hospital, and so- >> Jed: It is the lifeblood of every modern company. >> It is, but you have to be able to access it. You have to be able to harness it, access it, derive insights from it, and be able to act on that faster than the competitors that are waiting, like, right back here. One of the things Adam Selipsky talked about with our boss, John Furrier, who's the co-CEO of theCUBE, they had a sit-down about a week before re:Invent. John always gets a preview of the show and Adam said, you know, he thinks the role of data analyst is going to go away. Or at least the term, because with data democratization that needs to happen. Putting data in the hands of all the business users, that every business user, whether you're in technology or marketing or ops or finance, it's going to have to analyze data to do their jobs. >> Could not agree more. >> Are you hearing that from customers? >> 100% >> Yeah. >> I was just at the CTO Summit of Bank of America two weeks ago out in California, and they told, their CTO had a statistic, 60,000 technologists in Bank of America, all asking data-type questions. You can have the best team of data scientists in the world, and they do. They have some of the best data scientists in the world there. And this team of data scientists could answer any one of the questions that those 60,000 people might have but they can't answer all of them, right? You need those people to be able to answer their own questions. I don't know if the term data analysts are going away. I think, yeah, everybody's just going to have to become a bit more of one. Just like how Excel taught everybody how to use the spreadsheet, in the future, in the next five, 10 years, the democratization of AI means that tools like Dataiku and other data science tools are going to teach everybody how to analyze data. >> Talk about Dataiku as a facilitator of that, of that democratization. Giving, like the citizen technologist who might be in finance, the ability to do that. >> So, a lot of data science tools are aimed at your hardcore coder, right? Somebody who wants to be sitting at a notebook writing (indistinct) or something like that and running models on some big fancy Spark server. Dataiku is still going to be running models on some big fancy Spark server but we're really obfuscating the challenge of writing code away from the user. So we target low code, no code, and high code users all working together in a collaborative platform. So we really do, we believe that there is always going to be a place for data scientists. That role is not going away. You will always need hardcore coders to take on those moonshot very challenging topics. But for every day AI, anybody should be able to do this and it should be open to anybody. >> Right. >> Jed: Really aim to facilitate that. >> I would love to hear some feedback, you know, this is day four of the show as I was saying, and day four is packed. I mean, this is energy-level-wise, guys, it is the same as it was when we started here on Friday night. But I'd love to hear, Jed, from your perspective some of the customer conversations that you've had, what are some of the challenges? They're coming to you saying, "Jed, Dataiku, help us eradicate these challenges so we can transform our business." >> What I'm hearing from customers and partners and AWS here is, over and over, we don't want to buy tools anymore. We want to buy solutions. We want a vertical solution that's pre-built for our industry. And we want it to be, not necessarily click and run out of the box, but we want a template that we can build off of quickly. And I've heard that customers are also looking to understand how tools can be packaged together. You got how many booths are here? 1000 booths? >> Yes, easily. >> You have 1000 different products being talked about, right behind us. Customers need to know which of these products are friends with each other and how they fit together so that they are making sure that when they purchase a set, a suite of tools to do their jobs, it's all going to work naturally together. So, being able, I think this is a really vital concept for GSIs as well. GSIs needs to understand how to package sets of tools together to deliver a full solution to clients. People don't want to be, you know, I think 10 years ago, five years ago, AWS was in the business of selling servers in the cloud. But basically what you do is, you would buy an EC two instance and you install whatever software you wanted on it. I don't know that they're in that business still but customers don't want to buy servers from AWS anymore. They want to buy solutions. >> Right. >> Rent, whatever. >> Yeah. (chuckles) >> That is the big repeated message that I've heard here. >> So you brought up a good point that there are probably 1000 booths here. You could be here every day and not get to see everything that's going on. Plus this show was going on across the strip. We're only getting a fraction of the people that are here. But with that said, to your point, there are so many tools out there. Customers are looking for solutions. One of the things that we say about theCUBE is, we extract the signal from the noise. How does Dataiku get past the noise? How do you get up the stack to really impact customers so they understand the value that you're delivering? >> I think that Data science and ML sound like a very complicated topic but our value prop is relatively simple. And we appeal both to your end users who are excited to learn about how data science works and how they can leverage these tools in their day-to-day jobs, as well as appealing to IT. IT, right now, at major organizations they want to be able to build a full stack that makes sense. And the big choices they're making right now are around infrastructure. Where am I going to run my compute? So, they're choosing between Snowflake or Databricks or a native AWS compute solution, right? And so they make this big choice around compute and then they realize, "Oh, how many of our users across our organization are actually able to leverage this big compute choice?" Oh, maybe 100, maybe 200. That's not incredibly useful for what we've just decided to completely stand behind. Dataiku, all of a sudden, opens that up to 1000s of users across your organization. So it makes IT feel empowered by being able to help more people. And it makes users feel empowered by being able to use a great tool and start answering their own questions. >> And where are your customer conversations these days? As we look at AI and ML, emerging technologies, so many customers and companies, knowing we have to go in this direction. We have to have AI to speed the business. Are you seeing more of the conversations are still in IT or are they actually going up the stack? >> (chuckles) It's a great question. When you're going into large organizations, there's two sales motions, right? There's convincing the business users that this is a great thing and then convincing IT that it's not going to be too painful. You always have to go to both places. IT doesn't want to take on a boondoggler, or there's an albatross, I don't remember the word, but, something that they're going to have to deal with for the next 10 years and then eventually dismantle and pull apart. I think a lot of IT got very scared about big data platforms and solutions because of Hadoop. To be honest, Hadoop was incredibly powerful but maybe not as mature of technology as IT would've liked it to be. From a maintenance and administration standpoint. So yes, you will always have to sell to IT and help IT feel comfortable with the platform. But no, the conversations that I want to have are the use case conversations with a Chief Data Officer, Chief Revenue Officer, Chief Marketing Officer. That's who I really want to convince that this is going to be a worthwhile opportunity. >> And what are some of the key, sorry. What are some of the key use cases that Dataiku is tackling in the market these days? >> So we work a lot. Two of the biggest organizations, or verticals, that I work with personally are finance and pharmaceuticals. In finance, we are closely embedded with wealth management organizations. So, a lot of that is around customer entertainment, churn, relatively obvious, simple concepts but ones where it's worth a lot of money. In pharma, we work both on the supply side. So, doing supply chain optimization, ensuring the right drugs get to the right places at the right time. As well as on the business and marketing side. So, ensuring that your ad spend is correctly distributed across different advertising platforms. >> So if you're working with a financial organization, I want to understand from a consumer, from the end user's perspective, although obviously this technology impacts the end user who's trying to do a transaction. What's in it for me? And I don't know as the end user that Dataiku is under the hood. >> You'd never know. >> Which is good. I shouldn't have to worry about the technology. >> Jed: You shouldn't have to worry about that at all. >> What's in it for the end user customer? What are they gaining from this? >> So, from a very end user perspective, if you think about when you logged onto maybe your Bank of America, your Chase app, five or 10 years ago, maybe you didn't even have it on your phone five years ago. Or when you logged into your account online. We do 95% of our banking online right now, right? I go into a physical location, what? I don't know, once every six months or something? Get a cashier's check? I don't know. The experience that you're getting and the amount of information you're getting back about your spending habits, where your money is going, what your credit score is, all of these things are being driven by these big data organizations inside the banks. Also, any type, this is a little creepier, but any type of promotional emails or the types of things that you get feedback on when you use your credit card and the offers that you get through that, are all being personalized to you through the information that these banks are collecting about your spending habits. >> Yeah, but we want that as a consumer, we want the personalized. >> Yeah, of course. We want it to be magic slash not creepy. (laughs) >> Right, I want them to recommend the best card for me. >> Right. >> The next best thing. >> It's good for me, it's good for them. >> Don't serve me up something that I've already bought. That always bugs me when I'm like, I already bought that. >> I get that all the time. I'm like, yeah, I have that card already. It's in my wallet. Why are you telling me? >> We only have a couple of minutes left Jed, but talk to me about from a platform strategy perspective, what's next for Dataiku and AWS? >> So we are making a matrix transition right now and it's core to our platform. For a long time, the way that we've installed Dataiku is, we help our customers install it on their AWS account so it runs inside their tenant. This is very comfortable for, for example, large banking clients, pharma clients that have personally identifiable information, all that kind of thing. They own everything. However, as we were talking about before, we're really moving from providing a tool to providing solutions. And part of that is obviously a move to SaaS. So two years ago we released a SaaS offering. We've been expanding it more and more to, this year, we want to be pushing SaaS first. So Dataiku online should be the first option when new customers move on. And that is a huge platform shift. It means making sure that we have the right security in place. It means making sure that we have the right scaling in place, that we have 24-7 support. All this has been a big challenge. A big fascinating challenge, actually, to put together. >> Awesome. Last question for you. Say you get a brand new DeLorean, I hear they're coming back, and you want to put, you really, really want to put a bumper sticker on it, 'cause why not? And it's about Dataiku and it's like a sizzle reel kind of thing. >> A sizzle real, alright. >> Yeah. What does it say? >> Extraordinary people, everyday AI. >> Wow. Drop the mic, Jed. That was awesome. Thank you so much for coming on the program. We really appreciate the update on Dataiku. What you guys are doing for customers, your specialization and solutions for verticals. Awesome stuff, we'll have to have you back. >> Thank you so much. >> Alright, my pleasure. >> Bye-Bye. >> For my guest, I'm Lisa Martin. You're watching theCUBE, the leader in live enterprise and emerging tech coverage. (bright music)

(soft music) >> Welcome back to Sin City, guys and girls we're glad you're with us. You've been watching theCUBE all week, we know that. This is theCUBE's live coverage of AWS re:Invent 22, from the Venetian Expo Center where there are tens of thousands of people, and this event if you know it, covers the entire strip. There are over 55,000 people here, hundreds of thousands online. Dave, this has been a fantastic show. It is clear everyone's back. We're hearing phenomenal stories from AWS and it's ecosystem. We got a great customer story coming up next, featured on the main stage. >> Yeah, I mean, you know, post pandemic, you start to think about, okay, how are things changing? And one of the things that we heard from Adam Selipsky, was, we're going beyond digital transformation into business transformation. Okay. That can mean a lot of things to a lot of people. I have a sense of what it means. And I think this next interview really talks to business transformation beyond digital transformation, beyond the IT. >> Excellent. We've got two guests. One of them is an alumni, Scott Mullins joins us, GM, AWS Worldwide Financial Services, and Brad Peterson is here, the EVP, CIO and CTO of NASDAQ. Welcome guys. Great to have you. >> Hey guys. >> Hey guys. Thanks for having us. >> Yeah >> Brad, talk a little bit, there was an announcement with NASDAQ and AWS last year, a year ago, about how they're partnering to transform capital markets. It was a highlight of last year. Remind us what you talked about and what's gone on since then. >> Yeah, so, we are very excited. I work with Adena Friedman, she's my boss, CEO of NASDAQ, and she was on stage with Adam for his first Keynote as CEO of AWS. And we made the commitment that we were going to move our markets to the Cloud. And we've been a long time customer of AWS and everyone said, you know the last piece, the last frontier to be moved was the actual matching where all the messages, the quotes get matched together to become confirmed orders. So that was what we committed to less than a year ago. And we said we were going to move one of our options markets. In the US, we have six of them. And options markets are the most challenging, they're the most high volume and high performance. So we said, let's start with something really challenging and prove we can do it together with AWS. So we committed to that. >> And? Results so far? >> So, I can sit here and say that November 7th so we are live, we're in production and the MRX Exchange is called Mercury, so we shorten it for MRX, we like acronyms in technology. And so, we started with a phased launch of symbols, so you kind of allow yourself to make sure you have all the functionality working then you add some volume on it, and we are going to complete the conversion on Monday. So we are all good so far. And I have some results I can share, but maybe Scott, if you want to talk about why we did that together. >> Yeah. >> And what we've done together over many years. >> Right. You know, Brian, I think it's a natural extension of our relationship, right? You know, you look at the 12 year relationship that AWS and NASDAQ have had together, it's just the next step, in the way that we're going to help the industry transform itself. And so not just NASDAQ's business transformation for itself, but really a blueprint and a template for the entire capital markets industry. And so many times people will ask me, who's using Cloud well? Who's doing well in the Cloud? And NASDAQ is an easy example to point to, of somebody who's truly taking advantage of these capabilities because the Cloud isn't a place, it's a set of capabilities. And so, this is a shining example of how to use these capabilities to actually deliver real business benefit, not just to to your organization, but I think the really exciting part is the market technology piece of how you're serving other exchanges. >> So last year before re:Invent, we said, and it's obvious within the tech ecosystem, that technology companies are building on top of the Cloud. We said, the big trend that we see in the 2020s is that, you know, consumers of IT, historically, your customers are going to start taking their stacks, their software, their data, their services and sassifying, putting it on the Cloud and delivering new services to customers. So when we saw Adena on stage last year, we called it by the way, we called it Super Cloud. >> Yeah. >> Okay. Some people liked the term but I love it. And so yeah, Super Cloud. So when we saw Adena on stage, we said that's a great example. We've seen Capital One doing some similar things, we've had some conversations with US West, it's happening, right? So talk about how you actually do that. I mean, because you've got a lot, you've got a big on-premises stay, are you connecting to that? Is it all in the Cloud? Paint a picture of what the architecture looks like? >> Yeah. And there's, so you started with the business transformation, so I like that. >> Yeah. >> And the Super Cloud designation, what we are is, we own and operate exchanges in the United States and in Europe and in Canada. So we have our own markets that we're looking at modernizing. So we look at this, as a modernization of the capital market infrastructure, but we happen to be the leading technology provider for other markets around the world. So you either build your own or you source from us. And we're by far the leading provider. So a lot of our customers said, how about if you go first? It's kind of like Mikey, you know, give it to Mikey, let him try it. >> See if Mikey likes it. >> Yeah. >> Penguin off the iceberg thing. >> Yeah. And so what we did is we said, to make this easy for our customers, so you want to ask your customers, you want to figure out how you can do it so that you don't disrupt their business. So we took the Edge Compute that was announced a few years ago, Amazon Outposts, and we were one of their early customers. So we started immediately to innovate with, jointly innovate with Amazon. And we said, this looks interesting for us. So we extended the region into our Carteret data center in Northern New Jersey, which gave us all the services that we know and love from Amazon. So our technical operations team has the same tools and services but then, we're able to connect because in the markets what we're doing is we need to connect fairly. So we need to ensure that you still have that fairness element. So by bringing it into our building and extending the Edge Compute platform, the AWS Outpost into Carteret, that allowed us to also talk very succinctly with our regulators. It's a familiar territory, it's all buttoned up. And that simplified the conversion conversation with the regulators. It simplified it with our customers. And then it was up to us to then deliver time and performance >> Because you had alternatives. You could have taken a more mature kind of on-prem legacy stack, figured out how to bolt that in, you know, less cloudy. So why did you choose Outposts? I am curious. >> Well, Outposts looked like when it was announced, that it was really about extending territory, so we had our customers in mind, our global customers, and they don't always have an AWS region in country. So a lot of you think about a regulator, they're going to say, well where is this region located? So finally we saw this ability to grow the Cloud geographically. And of course we're in Sweden, so we we work with the AWS region in Stockholm, but not every country has a region yet. >> And we're working as fast as we can. - Yes, you are. >> Building in every single location around the planet. >> You're doing a good job. >> So, we saw it as an investment that Amazon had to grow the geographic footprint and we have customers in many smaller countries that don't have a region today. So maybe talk a little bit about what you guys had in mind and it's a multi-industry trend that the Edge Compute has four or five industries that you can say, this really makes a lot of sense to extend the Cloud. >> And David, you said it earlier, there's a trend of ecosystems that are coming onto the Cloud. This is our opportunity to bring the Cloud to an ecosystem, to an existing ecosystem. And if you think about NASDAQ's data center in Carteret, there's an ecosystem of NASDAQ's clients there that are there to be with NASDAQ. And so, it was actually much easier for us as we worked together over a really a four year period, thinking about this and how to make this technological transition, to actually bring the capabilities to that ecosystem, rather than trying to bring the ecosystem to AWS in one of our public regions. And so, that's been our philosophy with Outpost all along. It's actually extending our capabilities that our customers know and love into any environment that they need to be able to use that in. And so to Brad's point about servicing other markets in different countries around the world, it actually gives us that ability to do that very quickly, very nimbly and very succinctly and successfully. >> Did you guys write a working backwards document for this initiative? >> We did. >> Yeah, we actually did. So to be, this is one of the fully exercised. We have a couple of... So by the way, Scott used to work at NASDAQ and we have a number of people who have gone from NASDAQ data to AWS, and from AWS to NASDAQ. So we have adopted, that's one of the things that we think is an effective way to really clarify what you're trying to accomplish with a project. So I know you're a little bit kidding on that, but we did. >> No, I was close. Because I want to go to the like, where are we in the milestone? And take us through kind of what we can expect going forward now that we've worked backwards. >> Yep, we did. >> We did. And look, I think from a milestone perspective, as you heard Brad say, we're very excited that we've stood up MRX in production. Having worked at NASDAQ myself, when you make a change and when you stand up a market that's always a moment where you're working with your community, with your clients and you've got a market-wide call that you're working and you're wanting to make sure that everything goes smoothly. And so, when that call went smoothly and that transition went smoothly I know you were very happy, and in AWS, we were also very happy as well that we hit that milestone within the timeframe that Adena set. And that was very important I know to you. >> Yeah. >> And for us as well. >> Yeah. And our commitment, so the time base of this one was by the end of 2022. So November 7th, checked. We got that one done. >> That's awesome. >> The other one is we said, we wanted the performance to be as good or better than our current platform that we have. And we were putting a new version of our derivative or options software onto this platform. We had confidence because we already rolled it to one market in the US then we rolled it earlier this year and that was last year. And we rolled it to our nordic derivatives market. And we saw really good customer feedback. So we had confidence in our software was going to run. Now we had to marry that up with the Outpost platform and we said we really want to achieve as good or better performance and we achieved better performance, so that's noticeable by our customers. And that one was the biggest question. I think our customers understand when we set a date, we test them with them. We have our national test facility that they can test in. But really the big question was how is it going to perform? And that was, I think one of the biggest proof points that we're really proud about, jointly together. And it took both, it took both of us to really innovate and get the platform right, and we did a number of iterations. We're never done. >> Right. >> But we have a final result that says it is better. >> Well, congratulations. - Thank you. >> It sounds like you guys have done a tremendous job. What can we expect in 2023? From NASDAQ and AWS? Any little nuggets you can share? >> Well, we just came from the partner, the partner Keynote with Adam and Ruba and we had another colleague on stage, so Nick Ciubotariu, so he is actually someone who brought digital assets and cryptocurrencies onto the Venmo, PayPal platform. He joined NASDAQ about a year ago and we announced that in our marketplace, the Amazon marketplace, we are going to offer digital custody, digital assets custody solution. So that is certainly going to be something we're excited about in 2023. >> I know we got to go, but I love this story because it fits so great at the Super cloud but we've learned so much from Amazon over the years. Two pieces of teams, we talked about working backwards, customer obsession, but this is a story of NASDAQ pointing its internal capabilities externally. We're already on that journey and then, bringing that to the Cloud. Very powerful story. I wonder what's next in this, because we learn a lot and we, it's like the NFL, we copy it. I think about product market fit. You think about scientific, you know, go to market and seeing that applied to the financial services industry and obviously other industries, it's really exciting to see. So congratulations. >> No, thank you. And look, I think it's an example of Invent and Simplify, that's another Amazon principle. And this is, I think a great example of inventing on behalf of an industry and then continually working to simplify the way that the industry works with all of us. >> Last question and we've got only 30 seconds left. Brad, I'm going to direct it to you. If you had the opportunity to take over the NASDAQ sign in Times Square and say a phrase that summarizes what NASDAQ and AWS are doing together, what would it say? >> Oh, and I think I'm going to put that up on Monday. So we're going to close the market together and it's going to say, "Modernizing the capital market's infrastructure together." >> Very cool. >> Excellent. Drop the mic. Guys, this was fantastic. Thank you so much for joining us. We appreciate you joining us on the show, sharing your insights and what NASDAQ and AWS are doing. We're going to have to keep watching this. You're going to have to come back next year. >> All right. >> For our guests and for Dave Vellante, I'm Lisa Martin. You're watching theCUBE, the leader in live enterprise and emerging tech coverage. (soft music)

>> Good afternoon, fellow cloud nerds and welcome back to AWS Reinvent 2022. We are live here from fabulous Las Vegas, Nevada. My name is Savannah Peterson, joined by Lisa Martin. So excited to be here Lisa, it's my first reinvent. >> Is it really? >> Yeah. >> I think it's only like my fourth or fifth. >> Only your fourth or fifth. >> Only. >> You're such a pro here. >> There's some serious veterans here in attendance that have been to all 11. >> I love that. >> Yeah. Wow, go them. I know, maybe we'll be at that level sooner. >> One day we will. >> Are you enjoying the show so far? >> Absolutely, it is. I cannot believe how many people are here. We've had 70,000 and we're only seeing what's at the foundation Expo Hall, not at the other hotel. So, I can only imagine. >> I mean, there's a world outside of this. >> Yes, and there's sunlight. There's actual sunlight outside of this room. >> Nobel idea. Well, Lisa, I'm very excited to be sitting here next to you and to welcome our fabulous guests, from TEKsystems, we have Brandon and Srini. Thank you so much for being here. How is the show going for you gentlemen so far? >> It's great. Lot of new insights and the customers are going to love what AWS is releasing in this reinvent. >> There is such a community here, and I love that vibe. It's similar to what we had at Cloud Native con in Detroit. So much collaboration going on. I assume most folks know a lot about TEKsystems who are watching, but just in case they don't, Brandon, give us the pitch. >> You bet. So full stack IT solutions firm, been in business for over 40 years, 80,000 global employees, really specializing in digital transformation, enterprise modernization services. We have partners in One Strategy, which is an an acquisition we made, but a well known premier partner in the Amazon partner ecosystem, as well as One North Interactive, who is our boutique brand, creative and digital strategy firm. So together, we really feel like we can bring full end-to-end solutions for digital and modernization initiatives. >> So, I saw some notes where TEKsystems are saying organizations need experienced AWS partners that are not afraid doing the dirty work of digital transformation, who really can advise and execute. Brandon, talk to us about how TEKsystems and AWS are working together to help customers on that journey which is nebulous of digital transformation. >> So, our real hallmark is the ability to scale. We partner with AWS in a lot of different ways. In fact, we just signed our strategic collaboration agreement. So, we're in the one percenter group in the whole partner network. >> Savanna: That's a pretty casual flex there. >> Not bad. >> I love that, top 1%, that no wonder you're wearing that partner pin so proud today. (speaking indistinctly) >> But we're working all the way on the advisory and working with their pro serve organization and then transforming that into large scale mass migration services, a lot of data modernization that Srini is an absolute expert in. I'm sure he can add some context too, but it's been a great partnership for many years now. >> In the keynote, Adam spent almost 52 minutes on data, right? So, it emphasizes how organizations are ready to take data to cloud and actually make meaningful insights and help their own customers come out of it by making meaningful decisions. So, we are glad to be part of this entire ecosystem. >> I love that you quantified how many minutes. >> I know. >> Talked about it, that was impressive. There's a little bit of data driven thinking going on here. >> I think so. >> Yeah. >> Well, we can't be at an event like this without talking about data for copious amounts of time, 52 minutes, has just used this morning. >> Right, absolutely. >> But every company these days has to be a data company. There's no choice to be successful, to thrive, to survive. I mean, even to thrive and grow, if it's a grocery store or your local gas station or what? You name it, that company has to be a data company. But the challenge of the data volume, the explosion in data is huge for organizations to really try to figure out and sift through what they have, where is all of it? How do we make sense of it? How do we act on it and get insights? That's a big challenge. How is TEKsystems helping customers tackle that challenge? >> Yeah, that's a great question because that's the whole fun of handling data. You need to ensure its meaning is first understood. So, we are not just dumping data into a storage place, but rather assign a meaningful context. In today's announcement, again, the data zone was unveiled to give meaning to data. And I think those are key concrete steps that we take to our customers as well with some good blueprints, methodical ways of approaching data and ultimately gaining business insights. >> And maybe I'll add just something real quick to that. The theme we're seeing and hearing a lot about is data monetization. So, technology companies have figured it out and used techniques to personalize things and get you ads, probably that you don't want half the time. But now all industries are really looking to do that. Looking at ways to open new revenue channels, looking at ways to drive a better customer experience, a better employee experience. We've got a ton of examples of that, Big Oil and Gas leveraging like well and machine data, coming in to be more efficient when they're pumping and moving commodities around. We work a lot in the medium entertainment space and so obviously, getting targeted ads to consumers during the right periods of TV or movies or et cetera. Especially with the advert on Netflix and all your streaming videos. So, it's been really interesting but we really see the future in leveraging data as one of your biggest corporate assets. >> Brilliant. >> So, I'm just curious on the ad thing, just real quick and I'll let you go, Lisa. So, do you still fall victim to falling for the advertising even though you know it's been strategically put there for you to consume in that moment? >> Most of the time. >> I mean, I think we all do. We're all, (indistinct), you're behind the curtain so to speak. >> The Amazon Truck shows up every day at my house, which is great, right? >> Hello again >> Same. >> But I think the power of it is you are giving the customer what they're looking for. >> That's it. >> And you know... >> Exactly. We have that expectation, we want it. >> 100%. >> We know that. >> Agree. >> We don't need to buy it. But technology has made it so easy to transact. That's like when developers started going to the cloud years ago, it was just, it was a swipe. It was so simple. Brandon, talk about the changes in cloud and cloud migration that TEKsystems has seen, particularly in the last couple of years as every company was rushing to go digital because they had to. >> So several years ago, we kind of pushed away that cloud first mentality to the side and we use more of a cloud smart kind of fashion, right? Does everything need to go to the cloud? No. Do applications, data, need to go to the cloud in a way that's modern and takes advantages of what the cloud can provide and all the new services that are being released this week and ongoing. So, the other thing we're seeing is initiatives that have traditionally been in the CTO, CIO organization aren't necessarily all that successful because we're seeing a complete misalignment between business goals and IT achievements, outcomes, et cetera. You can automate things, you can move it to the cloud, but if you didn't solve a core business problem or challenge, what'd you really do? >> Yeah, just to add on that, it's all about putting data and people together. And then how we can actually ensure the workforce is equally brought up to speed on these new technologies. That has been something that we have seen tremendous improvement in the last 24 months where customers are ready to take up new challenges and the end users are ready to learn something new and not just stick onto that status quo mindset. >> Where do you guys factor in to bringing in AWS in the customer's cloud journeys? What is that partnership like? >> We always first look for where the customer is in their cloud journey path and make sure we advise them with the right next steps. And AWS having its services across the spectrum makes it even easier for us to look at what business problem they're solving and then align it according to the process and technology so that at the end of the day, we want end user adoption. We don't want to build a fancy new gadget that no one uses. >> Just because you built it doesn't mean they'll come. And I think that's the classic engineering marketing dilemma as well as balance to healthy tension. I would say between both. You mentioned Srini, you mentioned workforce just a second ago. What sort of trends are you seeing in workforce development? >> Generally speaking, there are a lot of services now that can quantify your code for errors and then make sure that the code that you're pushing into production is well tested. So what we are trying to make sure is a healthy mix of trying to solve a business problem and asking the right questions. Like today, even in the keynote, it was all about how QuickSight, for example, has additional features now that tells why something happened. And that's the kind of mindset we want our end users to adopt. Not just restricting themselves to a reactive analytics, but rather ask the question why, why did it happen? Why did my sales go down? And I think those technologies and mindset shift is happening across the workforce. >> From a workforce development standpoint, we're seeing there's not enough workforce and the core skills of data, DevOps, standard cloud type work. So, we're actually an ATP advanced training partner, one of the few within the AWS network. So, we've developed programs like our Rising Talent Program that are allowing us to bring the workforce up to the skills that are necessary in this new world. So, it's a more build versus buy strategy because we're on talents real, though it may start to wane a little bit as we change the macroeconomic outlook in 2023, but it's still there. And we still believe that building those workforce and investing in your people is the right thing to do. >> It is, and I think there's a strong alignment there with AWS and their focus on that as well. I wanted to ask you, Brandon. >> Brandon: Absolutely. >> One of the things, so our boss, John Furrier, the co CEO of theCUBE, talked with Adam Selipsky just a week or maybe 10 days ago. He always gets an exclusive interview with the CEO of AWS before reinvent, and one of the things that Adam shared with him is that customers, CEOs and CIOs are not coming to Adam, to this head of AWS to talk about technology, they want to talk about transformation. He's talking about... >> The topic this year. >> Moving away from amorphous topic of digital transformation to business transformation. Are you seeing the same thing in your customer? >> 100%, and if you're not starting at the business level, these initiatives are going to fail. We see it all the time. Again, it's about that misalignment and there's no good answer to that. But digital, I think is amorphous to some degree. We play a lot with the One North partnership that I mentioned earlier, really focusing on that strategy element because consumer dollars are shrinking via inflation, via what we're heading into, and we have to create the best experience possible. We have to create an omnichannel experience to get our products or services to market. And if we're not looking at those as our core goals and we're looking at them as IT or technology challenges, we're not looking in the right place. >> Well, and businesses aren't going to be successful if they're looking at it in those siloed organizations. Data has to be democratizing and we've spent same data democratization for so long, but really, we're seeing that it has to be moving out into the lines of business because another thing Adam shared with John Furrier is that he sees and I'm curious what your thoughts are on this, the title of data analysts going away because everybody in different functions and different lines of business within an organization are going to have to be data analysts to some degree, to use data whether it's marketing, ops, sales, finance, are you seeing the same? >> That is true. I mean, at this point, we are all in the connected world, right? Every data point is connected in some form or shape to another data point. >> Savanna: There are many data points, just sitting here, yeah. >> Absolutely, so I think if you are strategizing, data needs to be right in the center of it. And then your business problems need to be addressed with reliable data. >> No, I mean, advertising, supply chain, marketing, they're all interconnected now, and we're looking at ways to bring a lot of that siloed data into one place so we can make use to it. It goes back to that monetization element of our data. >> That's a lot about context and situational awareness. We want what we want, when we want it, even before we knew we needed it then. I think I said that right. But you know, it's always more faster, quicker and then scaling things up. You see a lot of different customers across verticals, you have an absolutely massive team. Give us a sneak peek into 2023. What does the future hold? >> 2023 is again, to today's keynote, I'm bringing it back because it was a keynote filled with vision and limitless possibilities. And that's what we see. Right now, our customers, they are no longer scared to go and take the plunge into the cloud. And as Brandon said, it's all about being smart about those decisions. So, we are very excited that together with the partnership that we recently acquired and the services and the depth, along with the horizontal domain expertise, we can actually help customers make meaningful message out of their data points. And that keeps us really excited for next year. >> Love that, Brandon, what about you? >> I think the obvious one is DevOps and a focus on optimization, financially, security, et cetera, just for the changing times. The other one is, I still think that digital is going to continue to be a big push in 2023, namely making sure that experience is at its best, whether that's employee and combating the war on talent, keeping your people or opening new revenue streams, enhancing existing revenue streams. You got to keep working on that. >> We got to keep the people happy with the machines and the systems that we are building as we all know. But it's very nice, it's been a lot of human-centric focus and a lot of customer obsession here at the show. We know it's a big thing for you all, for Amazon, for pretty much everyone who sat here. Hopefully it is in general. Hopefully there's nobody who doesn't care about their community, we're not talking to them, if that's the case, we have a new challenge on theCUBE for the show, this year as we kind of prepped you for and can call it a bumper sticker, you can call it a 30 second sizzle reel. But this is sort of your Instagram moment, your TikTok, your thought of leadership highlight. What's the most important story coming out of the show? Srini, you've been quoting the keynotes very well, so, I'm going to you first on this one. >> I think overall, it's all about owning the change. In our TEKsystems culture, it's all about striving for excellence through serving others and owning the change. And so it makes me very excited that when we get that kind of keynote resonating the same message that we invite culturally, that's a big win-win for all the companies. >> It's all about the shared vision. A lot of people with similar vision in this room right now, in this room, like it's a room, it's a massive expo center, just to be clear, I'm sure everyone can see in the background. Brandon >> I would say partnership, continuing to enhance our strategic partnership with AWS, continuing to be our customers' partners in transformation. And bringing those two things together here has been a predominance of my time this week. And we'll continue throughout the week, but we're in it together with our customers and with AWS and looking forward to the future. >> Yeah, that's a beautiful note to end on there. Brandon, Srini, thank you both so much for being here with us. Fantastic to learn from your insights and to continue to emphasize on this theme of collaboration. We look forward to the next conversation with you. Thank all of you for tuning in wherever you happen to be hanging out and watching this fabulous live stream or the replay. We are here at AWS Reinvent 2022 in wonderful sunny Las Vegas, Nevada with Lisa Martin. My name is Savannah Peterson, we are theCUBE, the leading source for high tech coverage.

(upbeat music) >> Hello, friends. Welcome back to The Cube's live coverage of AWS re:Invent 2022. We're in Vegas. Lovely Las Vegas. Beautiful outside, although I have only seen outside today once, but very excited to be at re:Invent. We're hearing between 50,000 and 70,000 attendees and it's insane, but people are ready to be back. This morning's keynote by CEO Adam Selipsky was full of great messages, big focus on data, customers, partners, the ecosystem. So excited. And I'm very pleased to welcome back one of our alumni to the program, David Shacochis, VP Enterprise Portfolio Strategy Product Management at Lumen. David, welcome back. >> Lisa, good to be here. The Five Timers Club. >> You are in the Five Timers Club. This is David's fifth appearance on the show. And we were talking before we went live- >> Do we do the jacket now and do we do the jacket later? >> Yeah, the jacket will come later. >> Okay. >> The Five Timers Club, like on SNL. We're going to have that for The Cube. We'll get you measured up and get that all fitted for you. >> That'd be better. >> So talk a little bit about Lumen. 'Cause last time you hear it wasn't Lumen. >> We weren't Lumen last time. So this is the first time... last time we were here on The Cube at re:Invent. This was probably 2019 or so. We were a different company. The company was called CenturyLink back then. We rebranded in 2020 to really represent our identity as a delivery of...as a solutions provider over our fiber network. So Lumen is the corporate brand, the company name. It represents basically a lot of the fiber that's been laid throughout the world and in North America and in enterprise metropolitan areas over the past 10 to 15 years. You know, companies like CenturyLink and Quest and Level 3, all those companies have really rolled up into building that core asset of the network. So Lumen is really the brand for the 21st century for the company, really focused on delivering services for the enterprise and then delivering a lot of value added services around that core network asset. >> So rebranding during the pandemic, what's been the customer feedback and sentiment? >> Yeah, I think customers have really actually appreciated it as certainly a more technology oriented brand, right? Sort of shifting away a little bit from some of the communications and telecom background of the company and the heritage. And while those assets that were built up during that period of time have been substantial, and we still build off of those assets going forward, really what a lot of the customer feedback has been is that it puts us in a posture to be a little bit more of a business solutions provider for customers, right? So there's a lot of things that we can do with that core network asset, the fiber networking a lot of the services that we launch on that in terms of public IP, you know, public internet capacity, private networking, private VPNs, VoIP and voice services. These are services that you'd expect from a company like that. But there's a lot of services inside the Lumen brand that you might surprise you, right? There's an edge computing capability that can deliver five milliseconds of latency within 95% of North American enterprise. >> Wow. >> There's a threat detection lab that goes and takes all of the traffic flowing over the public side of our network and analyzes it in a data lake and turns it into threat intelligence that we then offer off to our customers on a subscription basis. There's a production house that goes and, you know, does production networking for major sports arenas and sports events. There's a wide range of services inside of Lumen that really what the Lumen brand allows us to do is start talking about what those services can do and what networking can do for our customers in the enterprise in a more comprehensive way. >> So good changes, big brand changes for Lumen in the last couple of years. Also, I mean, during a time of such turmoil in the world, we've seen work change dramatically. You know, everybody...companies had to pivot massively quickly a couple years ago. >> Yep. >> Almost approaching three years ago, which is crazy amazing to be digital because they had to be able to survive. >> They did >> Now they're looking at being able to thrive, but now we're also in this hybrid work environment. The future of work has changed. >> Totally. >> Almost permanently. >> Yep. >> How is Lumen positioned to address some of the permanent changes to the work environments? Like the last time we were at re:Invented- >> Yeah. >> In person. This didn't exist. >> That's right. So really, it's one of the things we talk to our customers almost the most about is this idea of the future of work. And, you know, we really think about the future of work as about, you know, workers and workloads and the networks that connect them. You think about how much all of those demands are shifting and changing, right? What we were talking about, and it's very easy for all of us to conceptualize what the changing face of the worker looks like, whether those are knowledge workers or frontline workers the venues in which people are working the environments and that connectivity, predictability of those work desk environments changes so significantly. But workloads are changing and, you know we're sitting here at a trade show that does nothing but celebrate the transformation of workloads. Workloads running in ways in business logic and capturing of data and analysis of data. The changing methodologies and the changing formats of workloads, and then the changing venues for workloads. So workloads are running in places that never used to be data centers before. Workloads are running in interesting places and in different and challenging locations for what didn't used to be the data center. And so, you know, the workloads and the workloads are in a very dynamic situation. And the networks that connect them have to be dynamic, and they have to be flexible. And that's really why a lot of what Lumen invests in is working on the networks that connect workers and workloads both from a visibility and a managed services perspective to make sure that we're removing blind spots and then removing potential choke points and capacity issues, but then also being adaptable and dynamic enough to be able to go and reconfigure that network to reach all of the different places that, you know, workers and workloads are going to evolve into. What you'll find in a lot of cases, you know, the workers...a common scenario in the enterprise. A 500 person company with, you know, five offices and maybe one major facility. You know, that's now a 505 office company. >> Right. >> Right? The challenge of the network and the challenge of connecting workers and workloads is really one of the main conversations we have with our customers heading into this 21st century. >> What are some of the things that they're looking forward to in terms of embracing the future of work knowing this is probably how it's going to remain? >> Yeah, I think companies are really starting to experiment carefully and start to think about what they can do and certainly think about what they can do in the cloud with things like what the AWS platform allows them to do with some of the AWS abstractions and the AWS services allow them to start writing software for, and they're starting to really carefully, but very creatively and reach out into their you know, their base of enterprise data, their base of enterprise value to start running some experiments. We actually had a really interesting example of that in a session that Lumen shared here at re:Invent yesterday. You know, for the few hundred people that were there. You know, I think we got a lot of great feedback. It was really interesting session about the...really gets at this issue of the future of work and the changing ways that people are working. It actually was a really cool use case we worked on with Major League Baseball, Fox Sports, and AWS with the... using the Lumen network to essentially virtualize the production truck. Right? So you've all heard that, you know, the sports metaphor of, you know, the folks in the booth were sitting there started looking down and they're saying, oh great job by the guys or the gals in the truck. >> Yep. >> Right? That are, you know, that bring in that replay or great camera angle. They're always talking about the team and their production truck. Well, that production truck is literally a truck sitting outside the stadium. >> Yep. >> Full of electronics and software and gear. We were able to go and for a Major League Baseball game in...back in August, we were able to go and work with AWS, using the Lumen network, working with our partners and our customers at Fox Sports and virtualize all of that gear inside the truck. >> Wow. That's outstanding. >> Yep. So it was a live game. You know, they simulcast it, right? So, you know, we did our part of the broadcast and many hundreds of people, you know, saw that live broadcast was the first time they tried doing it. But, you know, to your point, what are enterprises doing? They're really starting to experiment, sort to push the envelope, right? They're kind of running things in new ways, you know, obviously hedging their bets, right? And sort of moving their way and sort of blue-green testing their way into the future by trying things out. But, you know, this is a massive revenue opportunity for a Major League Baseball game. You know, a premier, you know, Sunday night baseball contest between the Yankees and the Cardinals. We were able to go and take the entire truck, virtualize it down to a small rack of connectivity gear. Basically have that production network run over redundant fiber paths on the Lumen network up into AWS. And AWS is where all that software worked. The technical director of the show sitting in his office in North Carolina. >> Wow. >> The sound engineer is sitting in, you know, on his porch in Connecticut. Right? They were able to go and do the work of production anywhere while connected to AWS and then using the Lumen network, right? You know, the high powered capabilities of Lumens network underlay to be able to, you know, go and design a network topology and a worked topology that really wasn't possible before. >> Right. It's nice to hear, to your point, that customers are really embracing experimentation. >> Right. >> That's challenging to, obviously there was a big massive forcing function a couple of years ago where they didn't have a choice if they wanted to survive and eventually succeed and grow. >> Yeah. >> But the mindset of experimentation requires cultural change and that's a hard thing to do especially for I would think legacy organizations like Major League Baseball, but it sounds like they have the appetite. >> Yeah. They have the interest. >> They've been a fairly innovative organization for some time. But, you know, you're right. That idea of experimenting and that idea of trying out new things. Many people have observed, right? It's that forcing function of the pandemic that really drove a lot of organizations to go and make a lot of moves really quickly. And then they realized, oh, wait a minute. You know... I guess there's some sort of storytelling metaphor in there at some point of people realizing, oh wait, I can swim in these waters, right? I can do this. And so now they're starting to experiment and push the envelope even more using platforms like AWS, but then using a lot of the folks in the AWS partner network like Lumen, who are designing and sort of similarly inspired to deliver, you know, on demand and virtualized and dynamic capabilities within the core of our network and then within the services that our network can and the ways that our network connects to AWS. All of that experimentation now is possible because a lot of the things you need to do to try out the experiment are things you can get on demand and you can kind of pat, you can move back, you can learn. You can try new things and you can evolve. >> Right. >> Yep. >> Right. Absolutely. What are some of the things that you're excited about as, you know, here was this forcing function a couple years ago, we're coming out of that now, but the world has changed. The future of work as you are so brilliantly articulated has changed permanently. What are you excited about in terms of Lumen and AWS going forward? As we saw a lot of announcements this morning, big focus on data, vision of AWS is really that flywheel with Adams Selipsky is really, really going. What are you excited about going forward into 2023? >> Yeah, I mean we've been working with AWS for so long and have been critical partners for so long that, you know, I think a lot of it is continuation of a lot of the great work we've been doing. We've been investing in our own capabilities around the AWS partner network. You know, we're actually in a fairly unique position, you know, and we like to think that we're that unique position around the future of work where between workers, workloads and the networks that connect them. Our fingers are on a lot of those pulse points, right? Our fingers are on at really at the nexus of a lot of those dynamics. And our investment with AWS even puts us even more so in a position to go where a lot of the workloads are being transformed, right? So that's why, you know, we've invested in being one of the few network operators that is in the AWS partner network at the advanced tier that have the managed services competency, that have the migration competency and the network competency. You can count on one hand the number of network operators that have actually invested at that level with AWS. And there's an even smaller number that is, you know, based here in the United States. So, you know, I think that investment with AWS, investment in their partner programs and then investment co-innovation with AWS on things like that MLB use case really puts us in a position to keep on doing these kinds of things within the AWS partner network. And that's one of the biggest things we could possibly be excited about. >> So what does the go to market look like? Is it Lumen goes in, brings in AWS, vice versa? Both? >> Yeah, so a lot of being a member of the AWS partner network you have a lot of flexibility. You know, we have a lot of customers that are, you know, directly working with AWS. We have a lot of customers that would basically look to us to deliver the solution and, you know, and buy it all as a complete turnkey capability. So we have customers that do both. We have customers that, you know, just look to Lumen for the Lumen adjacent services and then pay, you know, pay a separate bill with AWS. So there's a lot of flexibility in the partner network in terms of what Lumen can deliver as a service, Lumen can deliver as a complete solution and then what parts of its with AWS and their platform factors into on an on-demand usage basis. >> And that would all be determined I imagine by what the customer really needs in their environment? >> Yeah, and sort of their own cloud strategy. There's a lot of customers who are all in on AWS and are really trying to driving and innovating and using some of the higher level services inside the AWS platform. And then there are customers who kind of looked at AWS as one of a few cloud platforms that they want to work with. The Lumen network is compatible and connected to all of them and our services teams are, you know, have the ability to go and let customers sort of take on whatever cloud posture they need. But if they are all in on AWS, there's, you know. Not many networks better to be on than Lumen in order to enable that. >> With that said, last question for you is if you had a bumper sticker or a billboard. Lumen's rebranded since we last saw you. What would that tagline or that phrase of impact be on that bumper sticker? >> Yeah, I'd get in a lot of trouble with our marketing team if I didn't give the actual bumper sticker for the company. But we really think of ourselves as the platform for amazing things. The fourth industrial revolution, everything going on in terms of the future of work, in terms of the future of industrial innovation, in terms of all the data that's being gathered. You know, Adam in the keynote this morning really went into a lot of detail on, you know, the depth of data and the mystery of data and how to harness it all and wrangle it all. It requires a lot of networking and a lot of connectivity. You know, for us to acquire, analyze and act on all that data and Lumen's platform for amazing things really helps forge that path forward to that fourth industrial revolution along with great partners like AWS. >> Outstanding. David, it's been such a pleasure having you back on The Cube. We'll get you fitted for that five timers club jacket. >> It sounds good. (Lisa laughs) >> I'll be back. >> Thanks so much for your insights and your time and well done with what you guys are doing at Lumen and AWS. >> Thanks Lisa. >> For David Shacochis, I'm Lisa Martin. You've been watching The Cube hopefully all day. This is our first full day of coverage at AWS re:Invent '22. Stick around. We'll be back tomorrow, and we know we're going to see you then. Have a great night. (upbeat music)

(upbeat music) >> Welcome back friends. It's theCUBE LIVE in Las Vegas at the Venetian Expo, covering the first full day of AWS re:Invent 2022. I'm Lisa Martin, and I have the privilege of working much of this week with Dave Vellante. >> Hey. Yeah, it's good to be with you Lisa. >> It's always good to be with you. Dave, this show is, I can't say enough about the energy. It just keeps multiplying as I've been out on the show floor for a few minutes here and there. We've been having great conversations about cloud migration, digital transformation, business transformation. You name it, we're talking about it. >> Yeah, and I got to say the soccer Christians are really happy. (Lisa laughing) >> Right? Because the USA made it through. So that's a lot of additional excitement. >> That's true. >> People were crowded around the TVs at lunchtime. >> They were, they were. >> So yeah, but back to data. >> Back to data. We have a couple of guests here. We're going to be talking a lot with customer challenges, how they're helping to overcome them. Please welcome Kevin Zawodzinski, VP of Sales Engineering at COMMVAULT. >> Thank you. >> And Paul Meighan, Director of Product Management at AWS. Guys, it's great to have you on the program. Thank you for joining us. >> Thanks for having us. >> Thanks for having us. >> Isn't it great to be back in person? >> Paul: It really is. >> Kevin: Hell, yeah. >> You cannot replicate this on virtual, you just can't. It's nice to see how excited people are to be back. There's been a ton of buzz on our program today about Adam's keynote this morning. Amazing. A lot of synergies with the direction, Paul, that AWS is going in and where we're seeing its ecosystem as well. Paul, first question for you. Talk about, you know, in the customer environment, we know AWS is very customer obsessed. Some of the main challenges customers are facing today is they really continue this business transformation, this digital transformation, and they move to cloud native apps. What are some of those challenges and how do you help them eradicate those? >> Well, I can tell you that the biggest contribution that we make is really by focusing on the fundamentals when it comes to running storage at scale, right? So Amazon S3 is unique, distributed architecture, you know, it really does deliver on those fundamentals of durability, availability, performance, security and it does it at virtually unlimited scale, right? I mean, you guys have talked to a lot of storage folks in the industry and anyone who's run an estate at scale knows that doing that and executing on those fundamentals day after day is just super hard, right? And so we come to work every day, we focus on the fundamentals, and that focus allows customers to spend their time thinking about innovation instead of on how to keep their data durably stored. >> Well, and you guys both came out of the storage world. >> Right. >> Yeah, yeah. >> It was a box world, (Kevin laughs) and it ain't no more. >> Kevin: That's right, absolutely. >> It's a service and a service of scale. >> Kevin: Yeah. So architecture matters, right? >> Yeah. >> Yeah. >> Paul, talk a little bit about, speaking of innovation, talk about the evolution of S3. It's been around for a while now. Everyone knows it, loves it, but how has AWS architected it to really help meet customers where they are? >> Paul: Right. >> Because we know, again, there's that customer first focus. You write the press release down the road, you then follow that. How is it evolving? >> Well, I can tell you that architecture matters a lot and the architecture of Amazon S3 is pretty unique, right? I think, you know, the most important thing to understand about the architecture of S3 is that it is truly a regional service. So we're laid out across a minimum of 3 Availability Zones, or AZs, which are physically separated and isolated and have a distance of miles between them to protect against local events like floods and fires and power interruption, stuff like that. And so when you give us an object, we distribute that data across that minimum of 3 Availability Zones and then within multiple devices within each AZ, right? And so what that means is that when you store data with us, your data is on storage that's able to tolerate the failure of multiple devices with no impact to the integrity of your data, which is super powerful. And then again, super hard to do when you're trying to roll your own. So that's sort of a, like an overview of the architecture. In terms of how we think about our roadmap, you know, 90% of our roadmap comes directly from what customers tell us matters, and that's a tenant of how we think about customer obsession at AWS and it really is how we drive a roadmap. >> Right, so speaking of customers Kevin, what are customers asking you guys- >> Yeah. >> for, how does it relate to what you're doing with S3? >> Yeah, it's a wonderful question and one that is actually really appropriate for us being at re:Invent, right? So we got, last three years we've had customers here with us on stage talking about it. First of all, 3 years ago we did a virtual session, unfortunately, but glad to be back as you mentioned, with Coca-Cola and theirs was about scale and scope and really about how can we protect hundreds of thousands of objects, petabyte to data, in a simple and secure way, right. Then last year we actually met with a ACT, Inc. as well and co-presented with them and really talked about how we could protect modern workloads and their modern workloads around whether it was Aurora or as well as EKS and how they continue to evolve as well. And, last but not least it's going to be, this year we're talking with Illinois State University as well about how they're going to continue to grow, adapt and really leverage AWS and ourselves to further their support of their teachers and their staff. So that is really helping us quite a bit to continue to move forward. And the things we're doing, again, with our customer base it's really around, focused on what's important to them, right? Customer obsession, how are we working with that? How are we making sure that we're listening to them? Again, working with AWS to understand how can we evolve together and really ultimately their journeys. As you heard, even with those 3 examples they're all very different, right? And that's the point, is that everybody's at a different point in the journey. They're at a different place from a modernization perspective. So we're helping them evolve, as they're helping us evolve as well, and transform with AWS. >> So very mature COMMVAULT stack, the S3 bucket and all the other capabilities. Paul, you just talked about coming together- >> Right. >> Dave: for your customers. >> Yeah, yeah, absolutely. And just, you know, we were talking the other day, Paul and I were talking the other day, it's been, you know, we've worked with AWS, with integration since 2009, right? So a long time, right? I mean, for some that may not seem like a long time ago, but it is, right? It's, you know, over a decade of time and we've really advanced that integration considerably as well. >> What are some of the things that, I don't know if you had a chance to see the keynote this morning? >> Yeah, a little bit. >> What are some of the things that there was, and in fact this is funny, funny data point for you on data. One of my previous guests told me that Adam Selipsky spent exactly 52 minutes talking about data this morning. 52 minutes. >> Okay. >> That there's a data point. But talk about some of the things that he talked about, the direction AWS is going in, obviously new era in the last year. Talk about what you heard and how you think that will evolve the COMMVAULT-AWS relationship. >> Yeah, I think part of that is about flexibility, as Paul mentioned too, architecture matters, right? So as we evolve and some of the things that we pride ourselves on is that we developed our systems and our software and everything else to not worry about what do I have to build to today but how do I continue to evolve with my customer base? And that's what AWS does, right? And continues to do. So that's really how we would see the data environment. It's really about that integration. As they grow, as they add more features we're going to add more features as well. And we're right there with them, right? So there's a lot of things that we also talk about, Paul and I talk about, around, you know, how do we, like Graviton3 was brought up today around some of the innovations around that. We're supporting that with Auto Scale right now, right? So we're right there releasing, right when AWS releasing, co-developing things when necessary as well. >> So let's talk about security a little bit. First of all, what is COMMVAULT, right? You're not a security company but you're an adjacency to security. It's sort of, we're rethinking security. >> Kevin: Yep. >> including data protection, not a bolt-on anymore. You guys both have a background in that world and I'm sure that resonates. >> Yeah. >> So what is the security play here? What role does COMMVAULT play? I think we know pretty well what role AWS plays, but love to hear, Paul, your thoughts as well on security. >> Yeah, I'll start I guess. >> Go on Paul. >> Okay. Yeah, so on the security side of things, there's a quite a few things. So again, on the development side of things, we do things like file anomaly detection, so seeing patterns in data. We talked a lot about analytics as well in the keynote this morning. We look at what is happening in the customer environment, if there's something odd or out of place that's happening, we can detect that and we'll notify people. And we've seen that, we have case studies about that. Other things we do are simple, simple but elegant. Is with our security dashboard. So we'll use our security dashboard to show best practices. Are they using Multi-Factor Authentication? Are you viewing password complexity? You know, things like that. And allows people to understand from a security landscape perspective, how do we layer in protection with their other systems around security. We don't profess to be the security company, or a security company, but we help, you know, obviously add in those additional layers. >> And obviously you're securing, you know, the S3 piece of it. >> Mmmhmm. >> You know, from your standpoint because building it in. >> That's right. And we can tell you that for us, security is job zero. And anyone at AWS will tell you that, and not only that but it will always be our top priority. Right from the infrastructure on down. We're very focused on our shared responsibility model where we handle security from the hypervisor, or host operating system level, down to the physical security of the facilities in which our services run and then it's our customer's responsibility to build secure applications, right. >> Yeah. And you talk about Graviton earlier, Nitro comes into play and how you're, sort of, fencing off, you know, the various components of the system from the operating system, the VMs, and then that is designed in and that's a new evolution that it comes as part of the package. >> Yeah, absolutely. >> Absolutely. >> Paul, talk a little bit about, you know, security, talking about that we had so many conversations this year alone about the threat landscape and how it's dramatically changing, it's top of mind for everybody. Huge rise in ransomware attacks. Ransomware is now, when are we going to get hit? How often? What's the damage going to be? Rather than, are we going to get hit? It's, unfortunately it's progressed in that direction. How does ensuring data security impact how you're planning the roadmap at AWS and how are partners involved in shaping that? >> Right, so like I said, you know, 90% of our roadmap comes from what customers tell us matters, right? And clearly this is an issue that matters very much to customers right now, right? And so, you know, we're certainly hearing that from customers, and COMMVAULT, and partners like COMMVAULT have a big role to play in helping customers to secure and protect their applications, right? And that's why it's so critical that we come together here at re:Invent and we have a bunch of time here at the show with the COMMVAULT technical folks to talk through what they're hearing from customers and what we're hearing. And we have a number of regular touch points throughout the year as well, right? And so what COMMVAULT gets from the relationship is, sort of, early access and feedback into our features and roadmap. And what we get out of it really is that feedback from that large number of customers who interface with Amazon S3 through COMMVAULT. Who are using S3 as a backup target behind COMMVAULT, right? And so, you know, that partnership really allows us to get close to those customers and understand what really matters to them. >> Are you doing joint engineering, or is it more just, hey here you go COMMVAULT, here's the tools available, go, go build. Can you address that? >> Yeah, no, absolutely. There's definitely joint engineering like even things around, you know, data migration and movement of data, we integrate really well and we talk a lot about, hey, what are you, like as Paul mentioned, what are you seeing out there? We actually, I just left a conversation about an hour ago where we're talking about, you know, where are we seeing placement of data and how does that matter to, do you put it on, you know, instant access, or do you put it on Glacier, you know, what should be the best practices? And we tell them, again, some of the telemetry data that we have around what do we see customers doing, what's the patterns of data? And then we feed that back in and we use that to create joint solutions as well. >> You know, I wonder if we could talk about cloud, you know, optimization of cloud costs for a minute. That's obviously a big discussion point in the hallways with customers. And on your earnings call you guys talked about specifically some customers and they specifically mentioned, for example, pushing storage to lower cost tiers. So you brought up Glacier just then. What are you seeing in the field in that regard? How are customers taking advantage of that? And where does COMMVAULT play in, sort of, helping make that decision? >> You want to take part one or you want me to take it? >> I can take part one. I can tell you that, you know, we're very focused on helping customers optimize costs, however necessary, right? And, you know, we introduced intelligent hearing here at the show in 2019 and since launch it's helped customers to reduce costs by over $750 million, right? So that's a real commitment to optimizing costs on behalf of customers. We also launched, you know, later in 2020, Glacier Deep Archive, which is the lowest cost storage in the cloud. So it's an important piece of the puzzle, is to provide those storage options that can allow customers to match the workloads that are, that need to be on folder storage to the appropriate store. >> Yeah, and so, you know, S3 is not this, you know, backup and recovery system, not an archiving system and, you know, in terms of, but you have that intelligence in your platform. 'Cause when I heard that from the earnings call I was like, okay, how do customers then go about deciding what they can, you know, when it's all good times, like yeah, who cares? You know, just go, go, go. But when you got to tighten the belt, how do you guys? >> Yeah, and that goes back to understanding the data pattern. So some of that is we have intelligence and artificial intelligence and everything else and machine learning within our, so we can detect those patterns, right? We understand the patterns, we learn from that and we help customers right size, right. So ultimately we do see a blend, right? As Paul mentioned, we see, you know, hey I'm not going to put everything on Glacier necessarily upfront. Maybe they are, it all depends on their workloads and patterns. So we use the data that we collect from the different customers that we have to share those best practices out and create, you know, the right templates, so to speak, in ways for people to apply it. >> Guys, great joint, you talked about the joint engineering, joint go to market, obviously a very strong synergistic partnership between the two. A lot of excitement. This is only day one, I can only imagine what's going to be coming the next couple of days. But I have one final question for you, but I have same question for both of you. You had the chance to create your own bumper sticker, so you get a shiny new car and for some reason you want to put a bumper sticker on it. About COMMVAULT, what would it say? >> Yeah, so for me I would say comprehensive, yet simple, right? So ultimately about giving you all the bells and whistles but if you want to be very simple we can help you in every shape and form. >> Paul, what's your bumper sticker say about AWS? >> I would say that AWS starts with the customer and works backwards from there. >> Great one. >> Excellent. Guys- >> Kevin: Well done. >> it's been a pleasure to have you on the program. Thank you- >> Kevin: Thank you. >> for sharing what's going on, the updates on the AWS-COMMVAULT partnership and what's in it for customers. We appreciate it. >> Dave: Thanks you guys. >> Thanks a lot. >> Thank you. >> All right. For our guests and Dave Vellante, I'm Lisa Martin. You're watching theCUBE, the leader in live enterprise and emerging tech coverage. (upbeat music)

>> 10, nine, eight, (clears throat) four, three. >> Good afternoon, fellow cloud nerds and welcome back to AWS Reinvent 2022. We are live here from fabulous Las Vegas, Nevada. My name is Savannah Peterson, joined by Lisa Martin. So excited to be here Lisa, it's my first reinvent. >> Is it really? >> Yeah. >> I think it's only like my fourth or fifth. >> Only your fourth or fifth. >> Only. >> You're such a pro here. >> There's some serious veterans here in attendance that have been to all 11. >> I love that. >> Yeah. Wow, go them. I know, maybe we'll be at that level sooner. >> One day we will. >> Are you enjoying the show so far? >> Absolutely, it is. I cannot believe how many people are here. We've had 70,000 and we're only seeing what's at the foundation Expo Hall, not at the other hotel. So, I can only imagine. >> I mean, there's a world outside of this. >> Yes, and there's sunlight. There's actual sunlight outside of this room. >> Nobel idea. Well, Lisa, I'm very excited to be sitting here next to you and to welcome our fabulous guests, from TEKsystems, we have Brandon and Srini. Thank you so much for being here. How is the show going for you gentlemen so far? >> It's great. Lot of new insights and the customers are going to love what AWS is releasing in this reinvent. >> There is such a community here, and I love that vibe. It's similar to what we had at Cloud Native con in Detroit. So much collaboration going on. I assume most folks know a lot about TEKsystems who are watching, but just in case they don't, Brandon, give us the pitch. >> You bet. So full stack IT solutions firm, been in business for over 40 years, 80,000 global employees, really specializing in digital transformation, enterprise modernization services. We have partners in One Strategy, which is an an acquisition we made, but a well known premier partner in the Amazon partner ecosystem, as well as One North Interactive, who is our boutique brand, creative and digital strategy firm. So together, we really feel like we can bring full end-to-end solutions for digital and modernization initiatives. >> So, I saw some notes where TEKsystems are saying organizations need experienced AWS partners that are not afraid doing the dirty work of digital transformation, who really can advise and execute. Brandon, talk to us about how TEKsystems and AWS are working together to help customers on that journey which is nebulous of digital transformation. >> So, our real hallmark is the ability to scale. We partner with AWS in a lot of different ways. In fact, we just signed our strategic collaboration agreement. So, we're in the one percenter group in the whole partner network. >> Savanna: That's a pretty casual flex there. >> Not bad. >> I love that, top 1%, that no wonder you're wearing that partner pin so proud today. (speaking indistinctly) >> But we're working all the way on the advisory and working with their pro serve organization and then transforming that into large scale mass migration services, a lot of data modernization that Srini is an absolute expert in. I'm sure he can add some context too, but it's been a great partnership for many years now. >> In the keynote, Adam spent almost 52 minutes on data, right? So, it emphasizes how organizations are ready to take data to cloud and actually make meaningful insights and help their own customers come out of it by making meaningful decisions. So, we are glad to be part of this entire ecosystem. >> I love that you quantified how many minutes. >> I know. >> Talked about it, that was impressive. There's a little bit of data driven thinking going on here. >> I think so. >> Yeah. >> Well, we can't be at an event like this without talking about data for copious amounts of time, 52 minutes, has just used this morning. >> Right, absolutely. >> But every company these days has to be a data company. There's no choice to be successful, to thrive, to survive. I mean, even to thrive and grow, if it's a grocery store or your local gas station or what? You name it, that company has to be a data company. But the challenge of the data volume, the explosion in data is huge for organizations to really try to figure out and sift through what they have, where is all of it? How do we make sense of it? How do we act on it and get insights? That's a big challenge. How is TEKsystems helping customers tackle that challenge? >> Yeah, that's a great question because that's the whole fun of handling data. You need to ensure its meaning is first understood. So, we are not just dumping data into a storage place, but rather assign a meaningful context. In today's announcement, again, the data zone was unveiled to give meaning to data. And I think those are key concrete steps that we take to our customers as well with some good blueprints, methodical ways of approaching data and ultimately gaining business insights. >> And maybe I'll add just something real quick to that. The theme we're seeing and hearing a lot about is data monetization. So, technology companies have figured it out and used techniques to personalize things and get you ads, probably that you don't want half the time. But now all industries are really looking to do that. Looking at ways to open new revenue channels, looking at ways to drive a better customer experience, a better employee experience. We've got a ton of examples of that, Big Oil and Gas leveraging like well and machine data, coming in to be more efficient when they're pumping and moving commodities around. We work a lot in the medium entertainment space and so obviously, getting targeted ads to consumers during the right periods of TV or movies or et cetera. Especially with the advert on Netflix and all your streaming videos. So, it's been really interesting but we really see the future in leveraging data as one of your biggest corporate assets. >> Brilliant. >> So, I'm just curious on the ad thing, just real quick and I'll let you go, Lisa. So, do you still fall victim to falling for the advertising even though you know it's been strategically put there for you to consume in that moment? >> Most of the time. >> I mean, I think we all do. We're all, (indistinct), you're behind the curtain so to speak. >> The Amazon Truck shows up every day at my house, which is great, right? >> Hello again >> Same. >> But I think the power of it is you are giving the customer what they're looking for. >> That's it. >> And you know... >> Exactly. We have that expectation, we want it. >> 100%. >> We know that. >> Agree. >> We don't need to buy it. But technology has made it so easy to transact. That's like when developers started going to the cloud years ago, it was just, it was a swipe. It was so simple. Brandon, talk about the changes in cloud and cloud migration that TEKsystems has seen, particularly in the last couple of years as every company was rushing to go digital because they had to. >> So several years ago, we kind of pushed away that cloud first mentality to the side and we use more of a cloud smart kind of fashion, right? Does everything need to go to the cloud? No. Do applications, data, need to go to the cloud in a way that's modern and takes advantages of what the cloud can provide and all the new services that are being released this week and ongoing. So, the other thing we're seeing is initiatives that have traditionally been in the CTO, CIO organization aren't necessarily all that successful because we're seeing a complete misalignment between business goals and IT achievements, outcomes, et cetera. You can automate things, you can move it to the cloud, but if you didn't solve a core business problem or challenge, what'd you really do? >> Yeah, just to add on that, it's all about putting data and people together. And then how we can actually ensure the workforce is equally brought up to speed on these new technologies. That has been something that we have seen tremendous improvement in the last 24 months where customers are ready to take up new challenges and the end users are ready to learn something new and not just stick onto that status quo mindset. >> Where do you guys factor in to bringing in AWS in the customer's cloud journeys? What is that partnership like? >> We always first look for where the customer is in their cloud journey path and make sure we advise them with the right next steps. And AWS having its services across the spectrum makes it even easier for us to look at what business problem they're solving and then align it according to the process and technology so that at the end of the day, we want end user adoption. We don't want to build a fancy new gadget that no one uses. >> Just because you built it doesn't mean they'll come. And I think that's the classic engineering marketing dilemma as well as balance to healthy tension. I would say between both. You mentioned Srini, you mentioned workforce just a second ago. What sort of trends are you seeing in workforce development? >> Generally speaking, there are a lot of services now that can quantify your code for errors and then make sure that the code that you're pushing into production is well tested. So what we are trying to make sure is a healthy mix of trying to solve a business problem and asking the right questions. Like today, even in the keynote, it was all about how QuickSight, for example, has additional features now that tells why something happened. And that's the kind of mindset we want our end users to adopt. Not just restricting themselves to a reactive analytics, but rather ask the question why, why did it happen? Why did my sales go down? And I think those technologies and mindset shift is happening across the workforce. >> From a workforce development standpoint, we're seeing there's not enough workforce and the core skills of data, DevOps, standard cloud type work. So, we're actually an ATP advanced training partner, one of the few within the AWS network. So, we've developed programs like our Rising Talent Program that are allowing us to bring the workforce up to the skills that are necessary in this new world. So, it's a more build versus buy strategy because we're on talents real, though it may start to wane a little bit as we change the macroeconomic outlook in 2023, but it's still there. And we still believe that building those workforce and investing in your people is the right thing to do. >> It is, and I think there's a strong alignment there with AWS and their focus on that as well. I wanted to ask you, Brandon. >> Brandon: Absolutely. >> One of the things, so our boss, John Furrier, the co CEO of theCUBE, talked with Adam Selipsky just a week or maybe 10 days ago. He always gets an exclusive interview with the CEO of AWS before reinvent, and one of the things that Adam shared with him is that customers, CEOs and CIOs are not coming to Adam, to this head of AWS to talk about technology, they want to talk about transformation. He's talking about... >> The topic this year. >> Moving away from amorphous topic of digital transformation to business transformation. Are you seeing the same thing in your customer? >> 100%, and if you're not starting at the business level, these initiatives are going to fail. We see it all the time. Again, it's about that misalignment and there's no good answer to that. But digital, I think is amorphous to some degree. We play a lot with the One North partnership that I mentioned earlier, really focusing on that strategy element because consumer dollars are shrinking via inflation, via what we're heading into, and we have to create the best experience possible. We have to create an omnichannel experience to get our products or services to market. And if we're not looking at those as our core goals and we're looking at them as IT or technology challenges, we're not looking in the right place. >> Well, and businesses aren't going to be successful if they're looking at it in those siloed organizations. Data has to be democratizing and we've spent same data democratization for so long, but really, we're seeing that it has to be moving out into the lines of business because another thing Adam shared with John Furrier is that he sees and I'm curious what your thoughts are on this, the title of data analysts going away because everybody in different functions and different lines of business within an organization are going to have to be data analysts to some degree, to use data whether it's marketing, ops, sales, finance, are you seeing the same? >> That is true. I mean, at this point, we are all in the connected world, right? Every data point is connected in some form or shape to another data point. >> Savanna: There are many data points, just sitting here, yeah. >> Absolutely, so I think if you are strategizing, data needs to be right in the center of it. And then your business problems need to be addressed with reliable data. >> No, I mean, advertising, supply chain, marketing, they're all interconnected now, and we're looking at ways to bring a lot of that siloed data into one place so we can make use to it. It goes back to that monetization element of our data. >> That's a lot about context and situational awareness. We want what we want, when we want it, even before we knew we needed it then. I think I said that right. But you know, it's always more faster, quicker and then scaling things up. You see a lot of different customers across verticals, you have an absolutely massive team. Give us a sneak peek into 2023. What does the future hold? >> 2023 is again, to today's keynote, I'm bringing it back because it was a keynote filled with vision and limitless possibilities. And that's what we see. Right now, our customers, they are no longer scared to go and take the plunge into the cloud. And as Brandon said, it's all about being smart about those decisions. So, we are very excited that together with the partnership that we recently acquired and the services and the depth, along with the horizontal domain expertise, we can actually help customers make meaningful message out of their data points. And that keeps us really excited for next year. >> Love that, Brandon, what about you? >> I think the obvious one is DevOps and a focus on optimization, financially, security, et cetera, just for the changing times. The other one is, I still think that digital is going to continue to be a big push in 2023, namely making sure that experience is at its best, whether that's employee and combating the war on talent, keeping your people or opening new revenue streams, enhancing existing revenue streams. You got to keep working on that. >> We got to keep the people happy with the machines and the systems that we are building as we all know. But it's very nice, it's been a lot of human-centric focus and a lot of customer obsession here at the show. We know it's a big thing for you all, for Amazon, for pretty much everyone who sat here. Hopefully it is in general. Hopefully there's nobody who doesn't care about their community, we're not talking to them, if that's the case, we have a new challenge on theCUBE for the show, this year as we kind of prepped you for and can call it a bumper sticker, you can call it a 30 second sizzle reel. But this is sort of your Instagram moment, your TikTok, your thought of leadership highlight. What's the most important story coming out of the show? Srini, you've been quoting the keynotes very well, so, I'm going to you first on this one. >> I think overall, it's all about owning the change. In our TEKsystems culture, it's all about striving for excellence through serving others and owning the change. And so it makes me very excited that when we get that kind of keynote resonating the same message that we invite culturally, that's a big win-win for all the companies. >> It's all about the shared vision. A lot of people with similar vision in this room right now, in this room, like it's a room, it's a massive expo center, just to be clear, I'm sure everyone can see in the background. Brandon >> I would say partnership, continuing to enhance our strategic partnership with AWS, continuing to be our customers' partners in transformation. And bringing those two things together here has been a predominance of my time this week. And we'll continue throughout the week, but we're in it together with our customers and with AWS and looking forward to the future. >> Yeah, that's a beautiful note to end on there. Brandon, Srini, thank you both so much for being here with us. Fantastic to learn from your insights and to continue to emphasize on this theme of collaboration. We look forward to the next conversation with you. Thank all of you for tuning in wherever you happen to be hanging out and watching this fabulous live stream or the replay. We are here at AWS Reinvent 2022 in wonderful sunny Las Vegas, Nevada with Lisa Martin. My name is Savannah Peterson, we are theCUBE, the leading source for high tech coverage.

(soft techno upbeat music) >> Hi there. Welcome back to Las Vegas. This is Dave Villante with Paul Gillon. Reinvent day one and a half. We started last night, Monday, theCUBE after dark. Now we're going wall to wall. Today. Today was of course the big keynote, Adam Selipsky, kind of the baton now handing, you know, last year when he did his keynote, he was very new. He was sort of still getting his feet wet and finding his guru swing. Settling in a little bit more this year, learning a lot more, getting deeper into the tech, but of course, sharing the love with other leaders like Peter DeSantis. Tomorrow's going to be Swamy in the keynote. Adrian Cockcroft is here. Former AWS, former network Netflix CTO, currently an analyst. You got your own firm now. You're out there. Great to see you again. Thanks for coming on theCUBE. >> Yeah, thanks. >> We heard you on at Super Cloud, you gave some really good insights there back in August. So now as an outsider, you come in obviously, you got to be impressed with the size and the ecosystem and the energy. Of course. What were your thoughts on, you know what you've seen so far, today's keynotes, last night Peter DeSantis, what stood out to you? >> Yeah, I think it's great to be back at Reinvent again. We're kind of pretty much back to where we were before the pandemic sort of shut it down. This is a little, it's almost as big as the, the largest one that we had before. And everyone's turned up. It just feels like we're back. So that's really good to see. And it's a slightly different style. I think there were was more sort of video production things happening. I think in this keynote, more storytelling. I'm not sure it really all stitched together very well. Right. Some of the stories like, how does that follow that? So there were a few things there and some of there were spelling mistakes on the slides, you know that ELT instead of ETL and they spelled ZFS wrong and something. So it just seemed like there was, I'm not quite sure just maybe a few things were sort of rushed at the last minute. >> Not really AWS like, was it? It's kind of remind the Patriots Paul, you know Bill Belichick's teams are fumbling all over the place. >> That's right. That's right. >> Part of it may be, I mean the sort of the market. They have a leader in marketing right now but they're going to have a CMO. So that's sort of maybe as lack of a single threaded leader for this thing. Everything's being shared around a bit more. So maybe, I mean, it's all fixable and it's mine. This is minor stuff. I'm just sort of looking at it and going there's a few things that looked like they were not quite as good as they could have been in the way it was put together. Right? >> But I mean, you're taking a, you know a year of not doing Reinvent. Yeah. Being isolated. You know, we've certainly seen it with theCUBE. It's like, okay, it's not like riding a bike. You know, things that, you know you got to kind of relearn the muscle memories. It's more like golf than is bicycle riding. >> Well I've done AWS keynotes myself. And they are pretty much scrambled. It looks nice, but there's a lot of scrambling leading up to when it actually goes. Right? And sometimes you can, you sometimes see a little kind of the edges of that, and sometimes it's much more polished. But you know, overall it's pretty good. I think Peter DeSantis keynote yesterday was a lot of really good meat there. There was some nice presentations, and some great announcements there. And today I was, I thought I was a little disappointed with some of the, I thought they could have been more. I think the way Andy Jesse did it, he crammed more announcements into his keynote, and Adam seems to be taking sort of a bit more of a measured approach. There were a few things he picked up on and then I'm expecting more to be spread throughout the rest of the day. >> This was more poetic. Right? He took the universe as the analogy for data, the ocean for security. Right? The Antarctic was sort of. >> Yeah. It looked pretty, >> yeah. >> But I'm not sure that was like, we're not here really to watch nature videos >> As analysts and journalists, You're like, come on. >> Yeah, >> Give it the meat >> That was kind the thing, yeah, >> It has always been the AWS has always been Reinvent has always been a shock at our approach. 100, 150 announcements. And they're really, that kind of pressure seems to be off them now. Their position at the top of the market seems to be unshakeable. There's no clear competition that's creeping up behind them. So how does that affect the messaging you think that AWS brings to market when it doesn't really have to prove that it's a leader anymore? It can go after maybe more of the niche markets or fix the stuff that's a little broken more fine tuning than grandiose statements. >> I think so AWS for a long time was so far out that they basically said, "We don't think about the competition, we are listen to the customers." And that was always the statement that works as long as you're always in the lead, right? Because you are introducing the new idea to the customer. Nobody else got there first. So that was the case. But in a few areas they aren't leading. Right? You could argue in machine learning, not necessarily leading in sustainability. They're not leading and they don't want to talk about some of these areas and-- >> Database. I mean arguably, >> They're pretty strong there, but the areas when you are behind, it's like they kind of know how to play offense. But when you're playing defense, it's a different set of game. You're playing a different game and it's hard to be good at both. I think and I'm not sure that they're really used to following somebody into a market and making a success of that. So there's something, it's a little harder. Do you see what I mean? >> I get opinion on this. So when I say database, David Foyer was two years ago, predicted AWS is going to have to converge somehow. They have no choice. And they sort of touched on that today, right? Eliminating ETL, that's one thing. But Aurora to Redshift. >> Yeah. >> You know, end to end. I'm not sure it's totally, they're fully end to end >> That's a really good, that is an excellent piece of work, because there's a lot of work that it eliminates. There's are clear pain points, but then you've got sort of the competing thing, is like the MongoDB and it's like, it's just a way with one database keeps it simple. >> Snowflake, >> Or you've got on Snowflake maybe you've got all these 20 different things you're trying to integrate at AWS, but it's kind of like you have a bag of Lego bricks. It's my favorite analogy, right? You want a toy for Christmas, you want a toy formula one racing car since that seems to be the theme, right? >> Okay. Do you want the fully built model that you can play with right now? Or do you want the Lego version that you have to spend three days building. Right? And AWS is the Lego technique thing. You have to spend some time building it, but once you've built it, you can evolve it, and you'll still be playing those are still good bricks years later. Whereas that prebuilt to probably broken gathering dust, right? So there's something about having an vulnerable architecture which is harder to get into, but more durable in the long term. And so AWS tends to play the long game in many ways. And that's one of the elements that they do that and that's good, but it makes it hard to consume for enterprise buyers that are used to getting it with a bow on top. And here's the solution. You know? >> And Paul, that was always Andy Chassy's answer to when we would ask him, you know, all these primitives you're going to make it simpler. You see the primitives give us the advantage to turn on a dime in the marketplace. And that's true. >> Yeah. So you're saying, you know, you take all these things together and you wrap it up, and you put a snowflake on top, and now you've got a simple thing or a Mongo or Mongo atlas or whatever. So you've got these layered platforms now which are making it simpler to consume, but now you're kind of, you know, you're all stuck in that ecosystem, you know, so it's like what layer of abstractions do you want to tie yourself to, right? >> The data bricks coming at it from more of an open source approach. But it's similar. >> We're seeing Amazon direct more into vertical markets. They spotlighted what Goldman Sachs is doing on their platform. They've got a variety of platforms that are supposedly targeted custom built for vertical markets. How do successful do you see that play being? Is this something that the customers you think are looking for, a fully integrated Amazon solution? >> I think so. There's usually if you look at, you know the MongoDB or data stacks, or the other sort of or elastic, you know, they've got the specific solution with the people that really are developing the core technology, there's open source equivalent version. The AWS is running, and it's usually maybe they've got a price advantage or it's, you know there's some data integration in there or it's somehow easier to integrate but it's not stopping those companies from growing. And what it's doing is it's endorsing that platform. So if you look at the collection of databases that have been around over the last few years, now you've got basically Elastic Mongo and Cassandra, you know the data stacks as being endorsed by the cloud vendors. These are winners. They're going to be around for a very long time. You can build yourself on that architecture. But what happened to Couch base and you know, a few of the other ones, you know, they don't really fit. Like how you going to bait? If you are now becoming an also ran, because you didn't get cloned by the cloud vendor. So the customers are going is that a safe place to be, right? >> But isn't it, don't they want to encourage those partners though in the name of building the marketplace ecosystem? >> Yeah. >> This is huge. >> But certainly the platform, yeah, the platform encourages people to do more. And there's always room around the edge. But the mainstream customers like that really like spending the good money, are looking for something that's got a long term life to it. Right? They're looking for a long commitment to that technology and that it's going to be invested in and grow. And the fact that the cloud providers are adopting and particularly AWS is adopting some of these technologies means that is a very long term commitment. You can base, you know, you can bet your future architecture on that for a decade probably. >> So they have to pick winners. >> Yeah. So it's sort of picking winners. And then if you're the open source company that's now got AWS turning up, you have to then leverage it and use that as a way to grow the market. And I think Mongo have done an excellent job of that. I mean, they're top level sponsors of Reinvent, and they're out there messaging that and doing a good job of showing people how to layer on top of AWS and make it a win-win both sides. >> So ever since we've been in the business, you hear the narrative hardware's going to die. It's just, you know, it's commodity and there's some truth to that. But hardware's actually driving good gross margins for the Cisco's of the world. Storage companies have always made good margins. Servers maybe not so much, 'cause Intel sucked all the margin out of it. But let's face it, AWS makes most of its money. We know on compute, it's got 25 plus percent operating margins depending on the seasonality there. What do you think happens long term to the infrastructure layer discussion? Okay, commodity cloud, you know, we talk about super cloud. Do you think that AWS, and the other cloud vendors that infrastructure, IS gets commoditized and they have to go up market or you see that continuing I mean history would say that still good margins in hardware. What are your thoughts on that? >> It's not commoditizing, it's becoming more specific. We've got all these accelerators and custom chips now, and this is something, this almost goes back. I mean, I was with some micro systems 20,30 years ago and we developed our own chips and HP developed their own chips and SGI mips, right? We were like, the architectures were all squabbling of who had the best processor chips and it took years to get chips that worked. Now if you make a chip and it doesn't work immediately, you screwed up somewhere right? It's become the technology of building these immensely complicated powerful chips that has become commoditized. So the cost of building a custom chip, is now getting to the point where Apple and Amazon, your Apple laptop has got full custom chips your phone, your iPhone, whatever and you're getting Google making custom chips and we've got Nvidia now getting into CPUs as well as GPUs. So we're seeing that the ability to build a custom chip, is becoming something that everyone is leveraging. And the cost of doing that is coming down to startups are doing it. So we're going to see many, many more, much more innovation I think, and this is like Intel and AMD are, you know they've got the compatibility legacy, but of the most powerful, most interesting new things I think are going to be custom. And we're seeing that with Graviton three particular in the three E that was announced last night with like 30, 40% whatever it was, more performance for HPC workloads. And that's, you know, the HPC market is going to have to deal with cloud. I mean they are starting to, and I was at Supercomputing a few weeks ago and they are tiptoeing around the edge of cloud, but those supercomputers are water cold. They are monsters. I mean you go around supercomputing, there are plumbing vendors on the booth. >> Of course. Yeah. >> Right? And they're highly concentrated systems, and that's really the only difference, is like, is it water cooler or echo? The rest of the technology stack is pretty much off the shelf stuff with a few tweets software. >> You point about, you know, the chips and what AWS is doing. The Annapurna acquisition. >> Yeah. >> They're on a dramatically different curve now. I think it comes down to, again, David Floyd's premise, really comes down to volume. The arm wafer volumes are 10 x those of X 86, volume always wins. And the economics of semis. >> That kind of got us there. But now there's also a risk five coming along if you, in terms of licensing is becoming one of the bottlenecks. Like if the cost of building a chip is really low, then it comes down to licensing costs and do you want to pay the arm license And the risk five is an open source chip set which some people are starting to use for things. So your dis controller may have a risk five in it, for example, nowadays, those kinds of things. So I think that's kind of the the dynamic that's playing out. There's a lot of innovation in hardware to come in the next few years. There's a thing called CXL compute express link which is going to be really interesting. I think that's probably two years out, before we start seeing it for real. But it lets you put glue together entire rack in a very flexible way. So just, and that's the entire industry coming together around a single standard, the whole industry except for Amazon, in fact just about. >> Well, but maybe I think eventually they'll get there. Don't use system on a chip CXL. >> I have no idea whether I have no knowledge about whether going to do anything CXL. >> Presuming I'm not trying to tap anything confidential. It just makes sense that they would do a system on chip. It makes sense that they would do something like CXL. Why not adopt the standard, if it's going to be as the cost. >> Yeah. And so that was one of the things out of zip computing. The other thing is the low latency networking with the elastic fabric adapter EFA and the extensions to that that were announced last night. They doubled the throughput. So you get twice the capacity on the nitro chip. And then the other thing was this, this is a bit technical, but this scalable datagram protocol that they've got which basically says, if I want to send a message, a packet from one machine to another machine, instead of sending it over one wire, I consider it over 16 wires in parallel. And I will just flood the network with all the packets and they can arrive in any order. This is why it isn't done normally. TCP is in order, the packets come in order they're supposed to, but this is fully flooding them around with its own fast retry and then they get reassembled at the other end. So they're not just using this now for HPC workloads. They've turned it on for TCP for just without any change to your application. If you are trying to move a large piece of data between two machines, and you're just pushing it down a network, a single connection, it takes it from five gigabits per second to 25 gigabits per second. A five x speed up, with a protocol tweak that's run by the Nitro, this is super interesting. >> Probably want to get all that AIML that stuff is going on. >> Well, the AIML stuff is leveraging it underneath, but this is for everybody. Like you're just copying data around, right? And you're limited, "Hey this is going to get there five times faster, pushing a big enough chunk of data around." So this is turning on gradually as the nitro five comes out, and you have to enable it at the instance level. But it's a super interesting announcement from last night. >> So the bottom line bumper sticker on commoditization is what? >> I don't think so. I mean what's the APIs? Your arm compatible, your Intel X 86 compatible or your maybe risk five one day compatible in the cloud. And those are the APIs, right? That's the commodity level. And the software is now, the software ecosystem is super portable across those as we're seeing with Apple moving from Intel to it's really not an issue, right? The software and the tooling is all there to do that. But underneath that, we're going to see an arms race between the top providers as they all try and develop faster chips for doing more specific things. We've got cranium for training, that instance has they announced it last year with 800 gigabits going out of a single instance, 800 gigabits or no, but this year they doubled it. Yeah. So 1.6 terabytes out of a single machine, right? That's insane, right? But what you're doing is you're putting together hundreds or thousands of those to solve the big machine learning training problems. These super, these enormous clusters that they're being formed for doing these massive problems. And there is a market now, for these incredibly large supercomputer clusters built for doing AI. That's all bandwidth limited. >> And you think about the timeframe from design to tape out. >> Yeah. >> Is just getting compressed It's relative. >> It is. >> Six is going the other way >> The tooling is all there. Yeah. >> Fantastic. Adrian, always a pleasure to have you on. Thanks so much. >> Yeah. >> Really appreciate it. >> Yeah, thank you. >> Thank you Paul. >> Cheers. All right. Keep it right there everybody. Don't forget, go to thecube.net, you'll see all these videos. Go to siliconangle.com, We've got features with Adam Selipsky, we got my breaking analysis, we have another feature with MongoDB's, Dev Ittycheria, Ali Ghodsi, as well Frank Sluman tomorrow. So check that out. Keep it right there. You're watching theCUBE, the leader in enterprise and emerging tech, right back. (soft techno upbeat music)

(upbeat music) >> Welcome back to Vegas. Lisa Martin and Dave Vellante here with theCUBE live on the Venetian Expo Hall Floor, talking all things AWS re:Invent 2022. This is the first full day of coverage. It is jam-packed here. People are back. They are ready to hear all the new innovations from AWS. Dave, how does it feel to be back yet again in Vegas? >> Yeah, Vegas. I think it's my 10th time in Vegas this year. So, whatever. >> This year alone. You must have a favorite steak restaurant then. >> There are several. The restaurants in Vegas are actually really good. >> You know? >> They are good. >> They used to be terrible. But I'll tell you. My favorite? The place that closed. >> Oh! >> Yeah, closed. In between where we are in the Wynn and the Venetian. Anyway. >> Was it CUT? >> No, I forget what the name was. >> Something else, okay. >> It was like a Greek sort of steak place. Anyway. >> Now, I'm hungry. >> We were at Pure Accelerate a couple years ago. >> Yes, we were. >> When they announced Cloud Block Store. >> That's right. >> Pure was the first- >> In Austin. >> To do that. >> Yup. >> And then they made the acquisition of Portworx which was pretty prescient given that containers have been going through the roof. >> Yeah. >> So I'm sort of excited to have these guys on and talk about that. >> We're going to unpack all of this. We've got one of our alumni back with us, Venkat Ramakrishna, VP of Product, Portworx by Pure Storage. And Dan Kogan joins us for the first time, VP of Product Management and Product Marketing, FlashArray at Pure Storage. Guys, welcome to the program. >> Thank you. >> Hey, guys. >> Dan: Thanks for having us. >> Do you have a favorite steak restaurant in Vegas? Dave said there's a lot of good choices. >> There's a lot of good steak restaurants here. >> I like SDK. >> Yeah, that's a good one. >> That's the good one. >> That's a good one. >> Which one? >> SDK. >> SDK. >> Where's that? >> It's, I think, in Cosmopolitan. >> Ooh. >> Yeah. >> Oh, yeah, yeah, yeah. >> It's pretty good, yeah. >> There's one of the Western too that's pretty. >> I'm an Herbs and Rye guy. Have you ever been there? >> No. >> No. >> Herbs and Rye is off strip, but it's fantastic. It's kind of like a locals joint. >> I have to dig through all of this great stuff today and then check that out. Talk to me. This is our first day, obviously. First main day. I want to get both of your perspectives. Dan, we'll start with you since you're closest to me. How are you finding this year's event so far? Obviously, tons of people. >> Busy. >> Busy, yeah. >> Yeah, it is. It is old times. Bigger, right? Last re:Invent I was at was 2019 right before everything shut down and it's probably half the size of this which is a different trend than I feel like most other tech conferences have gone where they've come back, but a little bit smaller. re:Invent seems to be the IT show. >> It really does. Venkat, are you finding the same? In terms of what you're experiencing so far on day one of the events? >> Yeah, I mean... There's tremendous excitement. Overall, I think it's good to be back. Very good crowd, great turnout, lot of excitement around some of the new offerings we've announced. The booth traffic has been pretty good. And just the quality of the conversations, the customer meetings, have been really good. There's very interesting use cases shaping up and customers really looking to solve real large scale problems. Yeah, it's been a phenomenal first day. >> Venkat, talk a little bit about, and then we'll get to you Dan as well, the relationship that Portworx by Pure Storage has with AWS. Maybe some joint customers. >> Yeah, so we... Definitely, we have been a partner of AWS for quite some time, right? Earlier this year, we signed what is called a strategic investment letter with AWS where we kind of put some joint effort together like to better integrate our products. Plus, kind of get in front of our customers more together and educate them on how going to how they can deploy and build vision critical apps on EKS and EKS anywhere and Outpost. So that partnership has grown a lot over the last year. We have a lot of significant mutual customer wins together both on the public cloud on EKS as well as on EKS anywhere, right? And there are some exciting use cases around Edge and Edge deployments and different levels of Edge as well with EKS anywhere. And there are pretty good wins on the Outpost as well. So that partnership I think is kind of like growing across not just... We started off with the one product line. Now our Portworx backup as a service is also available on EKS and along with the Portworx Data Services. So, it is also expanded across the product lanes as well. >> And then Dan, you want to elaborate a bit on AWS Plus Pure? >> Yeah, it's for kind of what we'll call the core Pure business or the traditional Pure business. As Dave mentioned, Cloud Block Store is kind of where things started and we're seeing that move and evolve from predominantly being a DR site and kind of story into now more and more production applications being lifted and shifted and running now natively in AWS honor storage software. And then we have a new product called Pure Fusion which is our storage as code automation product essentially. It takes you from moving and managing of individual arrays, now obfuscates a fleet level allows you to build a very cloud-like backend and consume storage as code. Very, very similar to how you do with AWS, with an EBS. That product is built in AWS. So it's a SaaS product built in AWS, really allowing you to turn your traditional Pure storage into an AWS-like experience. >> Lisa: Got it. >> What changed with Cloud Block Store? 'Cause if I recall, am I right that you basically did it on S3 originally? >> S3 is a big... It's a number of components. >> And you had a high performance EC2 instances. >> Dan: Yup, that's right. >> On top of lower cost object store. Is that still the case? >> That's still the architecture. Yeah, at least for AWS. It's a different architecture in Azure where we leverage their disc storage more. But in AWS were just based on essentially that backend. >> And then what's the experience when you go from, say, on-prem to AWS to sort of a cross cloud? >> Yeah, very, very simple. It's our replication technology built in. So our sync rep, our async rep, our active cluster technology is essentially allowing you to move the data really, really seamlessly there and then again back to Fusion, now being that kind of master control plan. You can have availability zones, running Cloud Block Store instances in AWS. You can be running your own availability zones in your data centers wherever those may happen to be, and that's kind of a unification layer across it all. >> It looks the same to the customer. >> To the customer, at the end of the day, it's... What the customer sees is the purity operating system. We have FlashArray proprietary hardware on premises. We have AWS's hardware that we run it on here. But to the customer, it's just the FlashArray. >> That's a data super cloud actually. Yeah, it's a data super cloud. >> I'd agree. >> It spans multiple clouds- >> Multiple clouds on premises. >> It extracts all the complexity of the underlying muck and the primitives and presents a common experience. >> Yeah, and it's the same APIs, same management console. >> Dave: Yeah, awesome. >> Everything's the same. >> See? It's real. It's a thing, On containers, I have a question. So we're in this environment, everybody wants to be more efficient, what's happening with containers? Is there... The intersection of containers and serverless, right? You think about all the things you have to do to run containers in VMs, configure everything, configure the memory, et cetera, and then serverless simplifies all that. I guess Knative in between or I guess Fargate. What are you seeing with customers between stateless apps, stateful apps, and how it all relates to containers? >> That's a great question, right? I think that one of the things that what we are seeing is that as people run more and more workloads in the cloud, right? There's this huge movement towards being the ability to bring these applications to run anywhere, right? Not just in one public cloud, but in the data centers and sometimes the Edge clouds. So there's a lot of portability requirements for the applications, right? I mean, yesterday morning I was having breakfast with a customer who is a big AWS customer but has to go into an on-prem air gap deployment for one of their large customers and is kind of re-platforming some other apps into containers in Kubernetes because it makes it so much easier for them to deploy. So there is no longer the debate of, is it stateless versus it stateful, it's pretty much all applications are moving to containers, right? And in that, you see people are building on Kubernetes and containers is because they wanted multicloud portability for their applications. Now the other big aspect is cost, right? You can significantly run... You know, like lower cost by running with Kubernetes and Portworx and by on the public cloud or on a private cloud, right? Because it lets you get more out of your infrastructure. You're not all provisioning your infrastructure. You are like just deploying the just-enough infrastructure for your application to run with Kubernetes and scale it dynamically as your application load scales. So, customers are better able to manage costs. >> Does serverless play in here though? Right? Because if I'm running serverless, I'm not paying for the compute the whole time. >> Yeah. >> Right? But then stateless and stateful come into play. >> Serverless has a place, but it is more for like quick event-driven decision. >> Dave: The stateless apps. >> You know, stuff that needs to happen. The serverless has a place, but majority of the applications have need compute and more compute to run because there's like a ton of processing you have to do, you're serving a whole bunch of users, you're serving up media, right? Those are not typically good serverless apps, right? The several less apps do definitely have a place. There's a whole bunch of minor code snippets or events you need to process every now and then to make some decisions. In that, yeah, you see serverless. But majority of the apps are still requiring a lot of compute and scaling the compute and scaling storage requirements at a time. >> So what Venkat was talking about is cost. That is probably our biggest tailwind from a cloud adoption standpoint. I think initially for on-premises vendors like Pure Storage or historically on-premises vendors, the move to the cloud was a concern, right? In that we're getting out the data center business, we're going all in on the cloud, what are you going to do? That's kind of why we got ahead of that with Cloud Block Store. But as customers have matured in their adoption of cloud and actually moved more applications, they're becoming much more aware of the costs. And so anywhere you can help them save money seems to drive adoption. So they see that on the Kubernetes side, on our side, just by adding in things that we do really well: Data reduction, thin provisioning, low cost snaps. Those kind of things, massive cost savings. And so it's actually brought a lot of customers who thought they weren't going to be using our storage moving forward back into the fold. >> Dave: Got it. >> So cost saving is great, huge business outcomes potentially for customers. But what are some of the barriers that you're helping customers to overcome on the storage side and also in terms of moving applications to Kubernetes? What are some of those barriers that you could help us? >> Yeah, I mean, I can answer it simply from a core FlashArray side, it's enabling migration of applications without having to refactor them entirely, right? That's Kubernetes side is when they think about changing their applications and building them, we'll call quote unquote more cloud native, but there are a lot of customers that can't or won't or just aren't doing that, but they want to run those applications in the cloud. So the movement is easier back to your data super cloud kind of comment, and then also eliminating this high cost associated with it. >> I'm kind of not a huge fan of the whole repatriation narrative. You know, you look at the numbers and it's like, "Yeah, there's something going on." But the one use case that looks like it's actually valid is, "I'm going to test in the cloud and I'm going to deploy on-prem." Now, I dunno if that's even called repatriation, but I'm looking to help the repatriation narrative because- >> Venkat: I think it's- >> But that's a real thing, right? >> Yeah, it's more than repatriation, right? It's more about the ability to run your app, right? It's not just even test, right? I mean, you're going to have different kinds of governance and compliance and regulatory requirements have to run your apps in different kinds of cloud environments, right? There are certain... Certain regions may not have all of the compliance and regulatory requirements implemented in that cloud provider, right? So when you run with Kubernetes and containers, I mean, you kind of do the transformation. So now you can take that app and run an infrastructure that allows you to deliver under those requirements as well, right? So that portability is the major driver than repatriation. >> And you would do that for latency reasons? >> For latency, yeah. >> Or data sovereign? >> Data sovereignty. >> Data sovereignty. >> Control. >> I mean, yeah. Availability of your application and data just in that region, right? >> Okay, so if the capability is not there in the cloud region, you come in and say, "Hey, we can do that on-prem or in a colo and get you what you need to comply to your EDX." >> Yeah, or potentially moves to a different cloud provider. It's just a lot more control that you're providing on customer at the end of the day. >> What's that move like? I mean, now you're moving data and everybody's going to complain about egress fees. >> Well, you shouldn't be... I think it's more of a one-time move. You're probably not going to be moving data between cloud providers regularly. But if for whatever reasons you decide that I'm going to stop running in X Cloud and I'm going to move to this cloud, what's the most seamless way to do? >> So a customer might say, "Okay, that's certification's not going to be available in this region or gov cloud or whatever for a year, I need this now." >> Yeah, or various commercial. Whatever it might be. >> "And I'm going to make the call now, one-way door, and I'm going to keep it on-prem." And then worry about it down the road. Okay, makes sense. >> Dan, I got to talk to you about the sustainability element there because it's increasingly becoming a priority for organizations in every industry where they need to work with companies that really have established sustainability programs. What are some of the factors that you talk with customers about as they have choice in all FlashArray between Pure and competitors where sustainability- >> Yeah, I mean we've leaned very heavily into that from a marketing standpoint recently because it has become so top of mind for so many customers. But at the end of the day, sustainability was built into the core of the Purity operating system in FlashArray back before it was FlashArray, right? In our early generation of products. The things that drive that sustainability of high density, high data reduction, small footprint, we needed to build that for Pure to exist as a company. And we are maybe kind of the last all-flash vendor standing that came ground up all-flash, not just the disc vendor that's refactored, right? And so that's sort of engineering from the ground up that's deeply, deeply into our software as a huge sustainability payout now. And we see that and that message is really, really resonating with customers. >> I haven't thought about that in a while. You actually are. I don't think there's any other... Nobody else made it through the knothole. And you guys hit escape velocity and then some. >> So we hit escape velocity and it hasn't slowed down, right? Earnings will be tomorrow, but the last many quarters have been pretty good. >> Yeah, we follow you pretty closely. I mean, there was one little thing in the pandemic and then boom! It's just kept cranking since, so. >> So at the end of the day though, right? We needed that level to be economically viable as a flash bender going against disc. And now that's really paying off in a sustainability equation as well because we consume so much less footprint, power cooling, all those factors. >> And there's been some headwinds with none pricing up until recently too that you've kind of blown right through. You know, you dealt with the supply issues and- >> Yeah, 'cause the overall... One, we've been, again, one of the few vendors that's been able to navigate supply really well. We've had no major delays in disruptions, but the TCO argument's real. Like at the end of the day, when you look at the cost of running on Pure, it's very, very compelling. >> Adam Selipsky made the statement, "If you're looking to tighten your belt, the cloud is the place to do it." Yeah, okay. It might be that, but... Maybe. >> Maybe, but you can... So again, we are seeing cloud customers that are traditional Pure data center customers that a few years ago said, "We're moving these applications into the cloud. You know, it's been great working with you. We love Pure. We'll have some on-prem footprint, but most of everything we're going to do is in the cloud." Those customers are coming back to us to keep running in the cloud. Because again, when you start to factor in things like thin provisioning, data reduction, those don't exist in the cloud. >> So, it's not repatriation. >> It's not repatriation. >> It's we want Pure in the cloud. >> Correct. We want your software. So that's why we built CBS, and we're seeing that come all the way through. >> There's another cost savings is on the... You know, with what we are doing with Kubernetes and containers and Portworx Data Services, right? So when we run Portworx Data Services, typically customers spend a lot of money in running the cloud managed services, right? Where there is obviously a sprawl of those, right? And then they end up spending a lot of item costs. So when we move that, like when they run their data, like when they move their databases to Portworx Data Services on Kubernetes, because of all of the other cost savings we deliver plus the licensing costs are a lot lower, we deliver 5X to 10X savings to our customers. >> Lisa: Significant. >> You know, significant savings on cloud as well. >> The operational things he's talking about, too. My Fusion engineering team is one of his largest customers from Portworx Data Services. Because we don't have DBAs on that team, it's just developers. But they need databases. They need to run those databases. We turn to PDS. >> This is why he pays my bills. >> And that's why you guys have to come back 'cause we're out of time, but I do have one final question for each of you. Same question. We'll start with you Dan, the Venkat we'll go to you. Billboard. Billboard or a bumper sticker. We'll say they're going to put a billboard on Castor Street in Mountain View near the headquarters about Pure, what does it say? >> The best container for containers. (Dave and Lisa laugh) >> Venkat, Portworx, what's your bumper sticker? >> Well, I would just have one big billboard that goes and says, "Got PX?" With the question mark, right? And let people start thinking about, "What is PX?" >> I love that. >> Dave: Got Portworx, beautiful. >> You've got a side career in marketing, I can tell. >> I think they moved him out of the engineering. >> Ah, I see. We really appreciate you joining us on the program this afternoon talking about Pure, Portworx, AWS. Really compelling stories about how you're helping customers just really make big decisions and save considerable costs. We appreciate your insights. >> Awesome. Great. Thanks for having us. >> Thanks, guys. >> Thank you. >> For our guests and for Dave Vellante, I'm Lisa Martin. You're watching theCUBE, the leader in live enterprise and emerging tech coverage. (upbeat music)

(upbeat music) >> Hello friends and welcome back to theCUBE's Live coverage of AWS re:Invent 2022 from the Venetian Expo in Vegas, baby. This show is absolutely packed. Lisa Martin with Dave Vellante, Dave this is day two, but really full day one of our wall to wall coverage on theCUBE. We've had great conversations the last half day this morning already, we've been talking with a lot of companies, a lot of Amazonians and some Amazonians that have left and gone on to interesting more things, which is what we're going to talk about next. >> Well, I'm excited about this segment because it's a really interesting space. You've got a search company who's gotten into observability and security and through our ETR partner our research, we do quarterly research and Elastic off the charts. Obviously they're the public company, so you can see how well they're doing. But the spending momentum on this platform is very, very strong and it has been consistently for quite some time. So really excited to learn more. >> The voice of the customer speaking loudly, from Elastic, its Chief Product Officer joins us, Ken Exner. Ken, welcome to the program. Hi, thank you, good to be here. >> Dave Vellante: Hey Ken. >> So a lot of us know about Elastic from Elastic Search but it's so much more than that these days. Talk about Elastic, what's going on now? What's the current product strategy? What's your vision? >> Yeah. So people know Elastic from the ELK Stack, you know Elastic Search, Logstash, Kibana. Very, very popular open source projects. They've been used by millions of developers for years and years. But one of the things that we started noticing over the years is that people were using it for all kinds of different use cases beyond just traditional search. So people started using Elastic Search to search through operational data, search through logs, search through all kinds of other types of data just to find different answers. And what we started realizing is the customers were taking us into different spaces. They took us into log analytics they started building log management solutions. And we said, cool, we can actually help these customers by providing solutions that already do this for them. So it took us into observability, they took us into security, and we started building solutions for security and observability based on what customers were starting to do with the platform. So customers can still use the platform for any number of different use cases for how do you get answers added data or they can use our pre-built packaged solutions for observability and security. >> So you were a longtime Amazonian. >> I was. I was. >> Talk a little bit about some of the things that you did there and what attracted you to Elastic? 'Cause it's only been a couple months, right? >> I've been here three months, I think three months as of yesterday. And I was at AWS for 16 years. So I was there a long, long time. I was there pretty much from the beginning. I was hired as one of the first product managers in AWS. Adam Selipsky hired me. And it was a great run. I had a ton of fun, I learned a lot. But you know, after 16 years I was kind of itching to do something new and it was going to take something special because I had a great gig and enjoyed the team at AWS. But I saw in Elastic sort of a great foundational technology they had a lot of momentum, a huge community behind it. I saw the business opportunity where they were going. I saw, you know the business opportunity of observability and security. These are massive industries with tons of business problems. Customers are excited about trying to get more answers out of data about their operational environment. And I saw, you know, that customers were struggling with their operating environments and things were becoming increasingly complicated. We used to talk in AWS about, you know how customers want to move from monolithic applications to monoliths, but one of the secrets was that things were increasingly complicated. Suddenly people had all these different microservices they had all these different managed services and their operating environment got complicated became this constellation of different systems, all emitting data. So companies like Elastic were helping people find answers in that data, find the problems with their systems so helping tame that complexity. So I saw that opportunity and I said I want to jump on that. Great foundational technology, good community and building solutions that actually helped solve real problems. >> Right. >> So, before you joined you probably looked back, and said, let think about the market, what's happening in the market space. What were the big trends that you saw that sort of informed your decision? >> Well, just sort of the mountain of data that was sort of emerging. Adam Selipsky in his talk this morning began by talking about how data is just multiplying constant. And I saw this, I saw how much data businesses were drowning in. Operational data, security data. You know, if you're trying to secure your business you have all these different endpoints you have all these different devices, you have different systems that you need to monitor all tons of data. And companies like Elastic were helping companies sort of manage that complexity, helping them find answers in that. So, when you're trying to track intruders or trying to track you know, malicious activity, there's a ton of different systems you need to pay attention to. And you know, there's a bunch of data. It's different devices, laptops and phone devices and stuff that you need to pay attention to. And you find correlations across that to figure out what is going on in your network, what is going on in your business. And that was exciting to me. This is a company sort of tackling one of the hardest problems which is helping you understand your operating environment, helping you understand and secure your business. >> So everybody's getting into observability. >> Yep. >> Right, it's a very crowded space right now. First of all, you know it's like overnight it just became the hottest thing going. VCs were throwing money at it. Why was that and how were you guys different? >> Well, we began by focusing on log analytics because that was the core of what we were doing. But customers started using it beyond log analytics and started using it for APM and started using it for performance data. And what we realized is that we could do all this for customers. So we ended up, sort of overnight over the course of three years building that a complete observe observability suite. So you can do APM, you can do profiling, you can do tracing, sort of distributed tracing, you can do synthetic monitoring everything you want to do, wheel user wondering. >> Metrics? >> All of it, metrics, all of it. And you can use the same system for this. So this was sort of a powerful concept, not only is it the best in leading log system, it also provides everything you need for complete observability. And because it's based on this open platform you can extend it to a number of different scenarios. So this is important, a lot of the different observability companies provide you something that's sort of packaged and as long as you're trying to do what it wants to support, it's great. But with Elastic, you have this flexible data architecture that you can use for anything. So companies use it to monitor assembly lines, they use it to monitor dish networks, for example use it to not only manage their fleet of servers they also use it to manage all their devices. So 25 million desktop devices. So, you know, observability systems like that that can do a number of different scenarios, I think that's a powerful thing. It's not just about how do you manage your servers how do you manage the things that are simple. It's how do you manage anything? How do you get observability into anything. >> Multiple use cases. >> Sorry, when you say complete, okay you talked about all the different APM, log analytics tracing, metrics, and also end-to-end. >> Ken Exner: End-to-end, yeah. >> Could you talk about that component of complete? >> So, if you're trying to find an issue like you have some metric that goes into alarm. You want to have a metric system that has alarming. Once that metric goes in alarm you're going to want to dig into your log. So you're going to want it to take you to the area of your logs that has that issue. Once you gets to there, you're going to want to find the trace ID that takes you to your traces and looks at sort of profiling, distributed tracing information. So a system that can do all of that end-to-end is a powerful solution. So it not only helps you track things end-to-end across the different signals that you're monitoring, but it actually helps you remediate more quickly. And the other thing that Elastic does that is unique is a lot of ML in this. So not only helping you find the information but surfacing things before you even know of them. So anomaly detection for example, helps you know about something before you even realize that there was an issue. So you should pay attention to this because it's anomalous. So a lot of systems help you find something if you know what to look for. But we're trying to help you not only find the things that you know to look for, but help you find the things that you didn't even think to know about. >> And it's fair to say one of your differentiators is you're open, open source. I mean, maybe talk about the ELK stack a little bit and how that plays. >> Yeah, well, so the great thing about this is we've extended that openness to both security and to observability. An example of this on the security side is all the detection rules that you use for looking for intrusion all the detection rules are open source and there's an entire community around this. So if you wanted to create a detection rule you can publish an open source, there's a bunch in GitHub you can benefit from what the community is doing as well. So in the world of security you want to be supported by the entire community, everyone looking for the same kind of issues. And there's an entire community around Elastic that is helping support these detection rules. So that approach, you know wanting to focus on community is differentiating for us. Not just, we got you covered as long you use things from us you can use it from the entire community. >> Well there implies the name Elastic. >> Yeah >> Talk a little bit about the influence that the customer has in the product roadmap and the direction. You've talked a little bit in the beginning about customers were leading us in different directions. It sounds very Amazonian in terms of following the customers where they go. >> It does, it actually does, it was one of the things that resonated for me personally is the journey that Elastic took to observability and security was customer led. So, we started looking at what customers were doing and realized that they were taking us into log analytics they were taking us into APM, they were taking us into these different solutions, and yeah, it is an Amazonian thing, so it resonated for me personally. And they're going to continue taking us in new places. Like we love seeing all the novel things that customers do with the platform and it's sort of one of the hallmarks of a great platform is you can have all kinds of novel things that, novel use cases for how people use your platform and we'll continue to see things and we may get taken into other solutions as well as we start seeing things emerge, like common patterns. But for now we're really excited about security and observability. >> So what do you see, so security's a big space, right? >> Yep. >> You see the optiv taxonomy and it makes your eyes bleed 'cause there's so many tools in there. Where do you fit in that taxonomy? How do you see and think about the security space and the opportunity for your customers? >> Yeah, so we began with logs in the security space as well. So SIEM, which is intrusion detection is based on aggregating a bunch of logs and helping you do threat hunting on those logs. So looking for patterns of malicious behavior or intrusion. So we started there and we did both detections as well as just ad hoc threat hunting. But then we started expanding into endpoint protection. So if we were going to have agents on all these different devices they were gathering logs, what if we also started providing remediation. So if you had malicious activity that was happening on one of the servers, don't just grab the information quarantine it, isolate it. So that took us into sort of endpoint protection or XDR. And then beyond that, we recently got into cloud security as well. So similar to observability, we started with logs but expanded to a full suite so that you can do everything. You can have both endpoint protection, you can have cloud security, all of it from one solution. >> Security is a very crowded market as well. What's your superpower? >> Ken Exner: What's our super power? >> Yeah. >> I think it, a lot of it is just the openness. It's the open platform, there's the community around it. People know and love the, the Elastic Search ELK stack and use it, we go into businesses all the time and they're familiar, their security engineers are using our product for searching through logs. So they're familiar with the product already and the community behind it. So they were excited about being able to use detection rules from other businesses and stay on top of that and be part of that community. The transparency of that is important to the customers. So if you're trying to be the most secure place, the most secure business, you want to basically invest in a community that's going to support that and not be alone in that. >> Right, absolutely, so much that rides on that. Favorite customer example that you think really articulates the value of Elastic, its openness, its transparency. >> Well, there's a customer Dish Media Dish Networks that's going to present here at re:Invent tomorrow at 1:45 at Mandalay Bay. I'm excited about their example because they use it to manage, I think it's 10 billion records a day across 25 million devices. So it illustrates the scale that we can support for managing observability for a company but also just sort of the unique use cases. We can use this for set top boxes for all their customers and they can track the performance that those customers are having. It's a unique case that a lot of vendors couldn't support but we can support because of the openness of the platform, the open data architecture that we have. So I think it illustrates the scale that we support, the elasticity, but also the openness of the data platform. >> Awesome and folks can catch that tomorrow, 1:45 PM at the Mandalay Bay. Last question for you, Ken, is you have a bumper sticker. >> Ken Exner: A bumper sticker? >> A bumper sticker you're going to put it on your fancy sexy new car and it's about elastic, what does it say? >> Helping you get answers out of data. So yeah. >> Love it, love it. Brilliant. >> Ken Exner: Thank you. >> Short and sweet. Ken, it's been a pleasure. >> It's been a pleasure being here, thank you. >> Thank you so much for sharing your journey with us as an Amazonian now into Elastic what Elastic is doing from a product perspective. We will keep our eyes peeled as Dave was saying. >> Ken Exner: Fantastic. >> The data show is really strong spending momentum so well done. >> Thank you very much, good to meet you. >> Our pleasure. For our guest and Dave Vellante, I'm Lisa Martin. You're watching theCUBE, the leader in live enterprise and emerging tech coverage. (upbeat music)

(upbeat music) >> Welcome back to Vegas. It's theCUBE live at AWS re:Invent 2022. We're hearing up to 50,000 people here. It feels like if the energy at this show is palpable. I love that. Lisa Martin here with Dave Vellante. Dave, we had the keynote this morning that Adam Selipsky delivered lots of momentum in his first year. One of the things that you said that you were looking in your breaking analysis that was released a few days ago, four trends and one of them, he said under Selipsky's rule in the 2020s, there's going to be a rush of data that will dwarf anything we have ever seen. >> Yeah, it was at least a quarter, maybe a third of his keynote this morning was all about data and the theme is simplifying data and doing better data integration, integrating across different data platforms. And we're excited to talk about that. Always want to simplify data. It's like the rush of data is so fast. It's hard for us to keep up. >> It is hard to keep that up. We're going to be talking with an alumni next about how his company is helping organizations like Cisco Meraki keep up with that data explosion. Please welcome back to the program, Matthew Scullion, the CEO of Matillion and how Hoshang Chenoy joins us, data scientist at Cisco Meraki. Guys, great to have you on the program. >> Thank you. >> Thank you for having us. >> So Matthew, we last saw you just a few months ago in Vegas at Snowflake Summits. >> Matthew: We only meet in Vegas. >> I guess we do, that's okay. Talk to us about some of the things, I know that Matillion is a data transformation solution that was originally introduced for AWS for Redshift. But talk to us about Matillion. What's gone on since we've seen you last? >> Well, I mean it's not that long ago but actually quite a lot. And it's all to do with exactly what you guys were just talking about there. This almost hard to comprehend way the world is changing with the amounts of data that we now can and need to put to work. And our worldview is there's no shortage of data but the choke points certainly one of the choke points. Maybe the choke point is our ability to make that data useful, to make it business ready. And we always talk about the end use cases. We talk about the dashboard or the AI model or the data science algorithm. But until before we can do any of that fun stuff, we have to refine raw data into business ready, usable data. And that's what Matillion is all about. And so since we last met, we've made a couple of really important announcements and possibly at the top of the list is what we call the data productivity cloud. And it's really squarely addressed this problem. It's the results of many years of work, really the apex of many years of the outsize engineering investment, Matillion loves to make. And the Data Productivity Cloud is all about helping organizations like Cisco Meraki and hundreds of others enterprise organizations around the world, get their data business ready, faster. >> Hoshang talk to us a little bit about what's going on at Cisco Meraki, how you're leveraging Matillion from a productivity standpoint. >> I've really been a Matillion fan for a while, actually even before Cisco Meraki at my previous company, LiveRamp. And you know, we brought Matillion to LiveRamp because you know, to Matthew's point, there is a stage in every data growth as I want to call it, where you have different companies at different stages. But to get data, data ready, you really need a platform like Matillion because it makes it really easy. So you have to understand Matillion, I think it's designed for someone that uses a lot of code but also someone that uses no code because the UI is so good. Someone like a marketer who doesn't really understand what's going on with that data but wants to be a data driven marketer when they look at the UI they immediately get it. They're just like, oh, I get what's happening with my data. And so that's the brilliance of Matillion and to get data to that data ready part, Matillion does a really, really good job because what we've been able to do is blend so many different data sources. So there is an abundance of data. Data is siloed though. And the connectivity between different data is getting harder and harder. And so here comes the Matillion with it's really simple solution, easy to use platform, powerful and we get to use all of that. So to really change the way we've thought about our analytics, the way we've progressed our division, yeah. >> You're always asking about superpowers and that is a superpower of Matillion 'cause you know, low-code, no-code sounds great but it only gets you a quarter of the way there, maybe 50% of the way there. You're kind of an "and" not an "or." >> That's a hundred percent right. And so I mentioned the Data Productivity Cloud earlier which is the name of this platform of technology we provide. That's all to do with making data business ready. And so I think one of the things we've seen in this industry over the past few years is a kind of extreme decomposition in terms of vendors of making data business ready. You've got vendors that just do loading, you've got vendors that just do a bit of data transformation, you've got vendors that do data ops and orchestration, you've got vendors that do reverse ETL. And so with the data productivity platform, you've got all of that. And particularly in this kind of, macroeconomic heavy weather that we're now starting to face, I think companies are looking for that. It's like, I don't want to buy five things, five sets of skills, five expensive licenses. I want one platform that can do it. But to your point David, it's the and not the or. We talk about the Data Productivity Cloud, the DPC, as being everyone ready. And what we mean by that is if you are the tech savvy marketer who wants to get a particular insight and you understand what a Rowan economy is, but you're not necessarily a hardcore super geeky data engineer then you can visual low-code, no-code, your data to a point where it's business ready. You can do that really quick. It's easy to understand, it's faster to ramp people onto those projects cause it like explains itself, faster to hand it over cause it's self-documenting. But, they'll always be individuals, teams, "and", "or" use cases that want to high-code as well. Maybe you want to code in SQL or Python, increasingly of course in DBT and you can do that on top of the Data Productivity Cloud as well. So you're not having to make a choice, but is that right? >> So one of the things that Matillion really delivers is speed to insight. I've always said that, you know, when you want to be business ready you want to make fast decisions, you want to act on data quickly, Matillion allows you to, this feed to insight is just unbelievably fast because you blend all of these different data sources, you can find the deficiencies in your process, you fix that and you can quickly turn things around and I don't think there's any other platform that I've ever used that has that ability. So the speed to insight is so tremendous with Matillion. >> The thing I always assume going on in our customers teams, like you run Hoshang is that the visual metaphor, be it around the orchestration and data ops jobs, be it around the transformation. I hope it makes it easier for teams not only to build it in the first place, but to live with it, right? To hand it over to other people and all that good stuff. Is that true? >> Let me highlight that a little bit more and better for you. So, say for example, if you don't have a platform like Matillion, you don't really have a central repository. >> Yeah. >> Where all of your codes meet, you could have a get repository, you could do all of those things. But, for example, for definitions, business definitions, any of those kind of things, you don't want it to live in just a spreadsheet. You want it to have a central platform where everybody can go in, there's detailed notes, copious notes that you can make on Matillion and people know exactly which flow to go to and be part of, and so I kind of think that that's really, really important because that's really helped us in a big, big way. 'Cause when I first got there, you know, you were pulling code from different scripts and things and you were trying to piece everything together. But when you have a platform like Matillion and you actually see it seamlessly across, it's just so phenomenal. >> So, I want to pick up on something Matthew said about, consolidating platforms and vendors because we have some data from PTR, one of our survey partners and they went out, every quarter they do surveys and they asked the customers that were going to decrease their spending in the quarter, "How are you going to do it?" And number one, by far, like, over a third said, "We're going to consolidate redundant vendors." Way ahead of cloud, we going to optimize cloud resource that was next at like 15%. So, confirms what you were saying and you're hearing that a lot. Will you wait? And I think we never get rid of stuff, we talk about it all the time. We call it GRS, get rid of stuff. Were you able to consolidate or at least minimize your expense around? >> Hoshang: Yeah, absolutely. >> What we were able to do is identify different parts of our tech stack that were just either deficient or duplicate, you know, so they're just like, we don't want any duplicate efforts, we just want to be able to have like, a single platform that does things, does things well and Matillion helped us identify all of those different and how do we choose the right tech stack. It's also about like Matillion is so easy to integrate with any tech stack, you know, it's just they have a generic API tool that you can log into anything besides all of the components that are already there. So it's a great platform to help you do that. >> And the three things we always say about the Data Productivity Cloud, everyone ready, we spoke about this is whether low-code, no-code, quasi-technical, quasi-business person using it, through to a high-end data engineer. You're going to feel at home on the DPC. The second one, which Hoshang was just alluding to there is stack ready, right? So it is built for AWS, built for Snowflake, built for Redshift, pure tight integration, push down ELT better than you could write yourself by hand. And then the final one is future ready, which is this idea that you can start now super easy. And we buy software quickly nowadays, right? We spin it up, we try it out and before we know it, the whole organization is using it. And so the future ready talks about that continuum of being able to launch in five minutes, learn it in five hours, deliver your first project in five days and yet still be happy that it's an enterprise scalable platform, five years down track including integrating with all the different things. So Matillion's job holding up the end of the bargain that Hoshang was just talking about there is to ensure we keep putting the features integrations and support into the Data Productivity Cloud to make sure that Hoshang's team can continue to live inside it and do all the things they need to do. >> Hoshang, you talked about the speed to insight being tremendously fast, but if I'm looking at Cisco Meraki from a high level business outcome perspective, what are some of those outcomes that a Matillion is helping Cisco Meraki to achieve. >> So I can just talk in general, not giving you like any specific numbers or anything, but for example, we were trying to understand how well our small and medium business campaigns were doing and we had to actually pull in data from multiple different sources. So not just, our instances of Marketo and Salesforce, we had to look at our internal databases. So Matillion helped us blend all of that together. Once I had all of that data blended, it was then ready to be analyzed. And once we had that analysis done, we were able to confirm that our SMB campaigns were doing well but these the things that we need to do to improve them. When we did that and all of that happened so quickly because they were like, well you need to get data from here, you need to get data from there. And we're like, great, we'll just plug, plug, plug. We put it all together, build transformations and you know we produced this insight and then we were able to reform, refine, and keep getting better and better at it. And you know, we had a 40X return on SMB campaigns. It's unbelievable. >> And there's the revenue tie in right there. >> Hoshang: Yeah. >> Matthew, I know you've been super busy, tons of meetings, you didn't get to see the whole keynote, but one of the themes of Adam Selipsky's keynote was, you know, the three letter word of ETL, they laid out a vision of zero ETL and then they announced zero ETL for Aurora and Redshift. And you think about ETL, I remember the days they said, "Okay, we're going to do ELT." Which is like, raising the debt ceiling, we're just going to kick the can down the road. So, what do you think about that vision? You know, how does it relate to what you guys are doing? >> So there was a, I don't know if this only works in the UK or it works globally. It was a good line many years ago. Rumors of my death are premature or so I think it was an obituary had gone out in the times by accident and that's how the guy responded to it. Something like that. It's a little bit like that. The announcement earlier within the AWS space of zero ETL between platforms like Aurora and Redshift and perhaps more over time is really about data movement, right? So it's about do I need to do a load of high cost in terms of coding and compute, movement of data between one platform, another. At Matillion, we've always seen data movement as an enabling technology, which gets you to the value add of transformation. My favorite metaphor to bring this to life is one of iron. So the world's made of iron, right? The world is literally made of iron ore but iron ore isn't useful until you turn it to steel. Loading data is digging out iron ore from the ground and moving it to the refinery. Transformation of data is turning iron ore into steel and what the announcements you saw earlier from AWS are more about the quarry to the factory bit than they are about the iron ore to the steel bit. And so, I think it's great that platforms are making it easier to move data between them, but it doesn't change the need for Hoshang's business professionals to refine that data into something useful to drive their marketing campaigns. >> Exactly, it's quarry to the factory and a very Snowflake like in a way, right? You make it easy to get in. >> It's like, don't get me wrong, I'm great to see investment going into the Redshift business and the AWS data analytics stack. We do a lot of business there. But yes, this stuff is also there on Snowflake, already. >> I mean come on, we've seen this for years. You know, I know there's a big love fest between Snowflake and AWS 'cause they're selling so much business in the field. But look that we saw it separating computing from storage, then AWS does it and now, you know, why not? It's good sense. That's what customers want. The customer obsessed data sharing is another thing. >> And if you take data sharing as an example from our friends at Snowflake, when that was announced a few people possibly, yourselves, said, "Oh, Matthew what do you think about this? You're in the data movement business." And I was like, "Ah, I'm not really actually, some of my competitors are in the data movement business. I have data movement as part of my platform. We don't charge directly for it. It's just part of the platform." And really what it's to do is to get the data into a place where you can do the fun stuff with it of refining into steel. And so if Snowflake or now AWS and the Redshift group are making that easier that's just faster to fun for me really. >> Yeah, sure. >> Last question, a question for both of you. If you had, you have a brand new shiny car, you got a bumper sticker that you want to put on that car to tell everyone about Matillion, everyone about Cisco Meraki, what does that bumper sticker say? >> So for Matillion, it says Matillion is the Data Productivity Cloud. We help you make your data business ready, faster. And then for a joke I'd write, "Which you are going to need in the face of this tsunami of data." So that's what mine would say. >> Love it. Hoshang, what would you say? >> I would say that Cisco makes some of the best products for IT professionals. And I don't think you can, really do the things you do in IT without any Cisco product. Really phenomenal products. And, we've gone so much beyond just the IT realm. So you know, it's been phenomenal. >> Awesome. Guys, it's been a pleasure having you back on the program. Congrats to you now Hoshang, an alumni of theCUBE. >> Thank you. >> But thank you for talking to us, Matthew, about what's going on with Matillion so much since we've seen you last. I can imagine how much worse going to go on until we see you again. But we appreciate, especially having the Cisco Meraki customer example that really articulates the value of data for everyone. We appreciate your insights and we appreciate your time. >> Thank you. >> Privilege to be here. Thanks for having us. >> Thank you. >> Pleasure. For our guests and Dave Vellante, I'm Lisa Martin. You're watching theCUBE, the leader in live enterprise and emerging tech coverage.