(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)

(upbeat music) >> Hi everyone. Welcome back to this Cube conversation here in Palo Alto, California. I'm John Furrier, host of "theCUBE." Got a great conversation around Cloud Native, Cloud Native Journey, how enterprises are looking at Cloud Native and putting it all together. And it comes down to operations, developer productivity, and security. It's the hottest topic in technology. We got Chris Jones here in the studio, director of Product Management for Platform9. Chris, thanks for coming in. >> Hey, thanks. >> So when we always chat about, when we're at KubeCon. KubeConEU is coming up and in a few, in a few months, the number one conversation is developer productivity. And the developers are driving all the standards. It's interesting to see how they just throw everything out there and whatever gets adopted ends up becoming the standard, not the old school way of kind of getting stuff done. So that's cool. Security Kubernetes and Containers are all kind of now that next level. So you're starting to see the early adopters moving to the mainstream. Enterprises, a variety of different approaches. You guys are at the center of this. We've had a couple conversations with your CEO and your tech team over there. What are you seeing? You're building the products. What's the core product focus right now for Platform9? What are you guys aiming for? >> The core is that blend of enabling your infrastructure and PlatformOps or DevOps teams to be able to go fast and run in a stable environment, but at the same time enable developers. We don't want people going back to what I've been calling Shadow IT 2.0. It's, hey, I've been told to do something. I kicked off this Container initiative. I need to run my software somewhere. I'm just going to go figure it out. We want to keep those people productive. At the same time we want to enable velocity for our operations teams, be it PlatformOps or DevOps. >> Take us through in your mind and how you see the industry rolling out this Cloud Native journey. Where do you see customers out there? Because DevOps have been around, DevSecOps is rocking, you're seeing AI, hot trend now. Developers are still in charge. Is there a change to the infrastructure of how developers get their coding done and the infrastructure, setting up the DevOps is key, but when you add the Cloud Native journey for an enterprise, what changes? What is the, what is the, I guess what is the Cloud Native journey for an enterprise these days? >> The Cloud Native journey or the change? When- >> Let's start with the, let's start with what they want to do. What's the goal and then how does that happen? >> I think the goal is that promise land. Increased resiliency, better scalability, and overall reduced costs. I've gone from physical to virtual that gave me a higher level of density, packing of resources. I'm moving to Containers. I'm removing that OS layer again. I'm getting a better density again, but all of a sudden I'm running Kubernetes. What does that, what does that fundamentally do to my operations? Does it magically give me scalability and resiliency? Or do I need to change what I'm running and how it's running so it fits that infrastructure? And that's the reality, is you can't just take a Container and drop it into Kubernetes and say, hey, I'm now Cloud Native. I've got reduced cost, or I've got better resiliency. There's things that your engineering teams need to do to make sure that application is a Cloud Native. And then there's what I think is one of the largest shifts of virtual machines to containers. When I was in the world of application performance monitoring, we would see customers saying, well, my engineering team have this Java app, and they said it needs a VM with 12 gig of RAM and eight cores, and that's what we gave it. But it's running slow. I'm working with the application team and you can see it's running slow. And they're like, well, it's got all of its resources. One of those nice features of virtualization is over provisioning. So the infrastructure team would say, well, we gave it, we gave it all a RAM it needed. And what's wrong with that being over provisioned? It's like, well, Java expects that RAM to be there. Now all of a sudden, when you move to the world of containers, what we've got is that's not a set resource limit, really is like it used to be in a VM, right? When you set it for a container, your application teams really need to be paying attention to your resource limits and constraints within the world of Kubernetes. So instead of just being able to say, hey, I'm throwing over the fence and now it's just going to run on a VM, and that VMs got everything it needs. It's now really running on more, much more of a shared infrastructure where limits and constraints are going to impact the neighbors. They are going to impact who's making that decision around resourcing. Because that Kubernetes concept of over provisioning and the virtualization concept of over provisioning are not the same. So when I look at this problem, it's like, well, what changed? Well, I'll do my scale tests as an application developer and tester, and I'd see what resources it needs. I asked for that in the VM, that sets the high watermark, job's done. Well, Kubernetes, it's no longer a VM, it's a Kubernetes manifest. And well, who owns that? Who's writing it? Who's setting those limits? To me, that should be the application team. But then when it goes into operations world, they're like, well, that's now us. Can we change those? So it's that amalgamation of the two that is saying, I'm a developer. I used to pay attention, but now I need to pay attention. And an infrastructure person saying, I used to just give 'em what they wanted, but now I really need to know what they've wanted, because it's going to potentially have a catastrophic impact on what I'm running. >> So what's the impact for the developer? Because, infrastructure's code is what everybody wants. The developer just wants to get the code going and they got to pay attention to all these things, or don't they? Is that where you guys come in? How do you guys see the problem? Actually scope the problem that you guys solve? 'Cause I think you're getting at I think the core issue here, which is, I've got Kubernetes, I've got containers, I've got developer productivity that I want to focus on. What's the problem that you guys solve? >> Platform operation teams that are adopting Cloud Native in their environment, they've got that steep learning curve of Kubernetes plus this fundamental change of how an app runs. What we're doing is taking away the burden of needing to operate and run Kubernetes and giving them the choice of the flexibility of infrastructure and location. Be that an air gap environment like a, let's say a telco provider that needs to run a containerized network function and containerized workloads for 5G. That's one thing that we can deploy and achieve in a completely inaccessible environment all the way through to Platform9 running traditionally as SaaS, as we were born, that's remotely managing and controlling your Kubernetes environments on-premise AWS. That hybrid cloud experience that could be also Bare Metal, but it's our platform running your environments with our support there, 24 by seven, that's proactively reaching out. So it's removing a lot of that burden and the complications that come along with operating the environment and standing it up, which means all of a sudden your DevOps and platform operations teams can go and work with your engineers and application developers and say, hey, let's get, let's focus on the stuff that, that we need to be focused on, which is running our business and providing a service to our customers. Not figuring out how to upgrade a Kubernetes cluster, add new nodes, and configure all of the low level. >> I mean there are, that's operations that just needs to work. And sounds like as they get into the Cloud Native kind of ops, there's a lot of stuff that kind of goes wrong. Or you go, oops, what do we buy into? Because the CIOs, let's go, let's go Cloud Native. We want to, we got to get set up for the future. We're going to be Cloud Native, not just lift and shift and we're going to actually build it out right. Okay, that sounds good. And when we have to actually get done. >> Chris: Yeah. >> You got to spin things up and stand up the infrastructure. What specifically use case do you guys see that emerges for Platform9 when people call you up and you go talk to customers and prospects? What's the one thing or use case or cases that you guys see that you guys solve the best? >> So I think one of the, one of the, I guess new use cases that are coming up now, everyone's talking about economic pressures. I think the, the tap blows open, just get it done. CIO is saying let's modernize, let's use the cloud. Now all of a sudden they're recognizing, well wait, we're spending a lot of money now. We've opened that tap all the way, what do we do? So now they're looking at ways to control that spend. So we're seeing that as a big emerging trend. What we're also sort of seeing is people looking at their data centers and saying, well, I've got this huge legacy environment that's running a hypervisor. It's running VMs. Can we still actually do what we need to do? Can we modernize? Can we start this Cloud Native journey without leaving our data centers, our co-locations? Or if I do want to reduce costs, is that that thing that says maybe I'm repatriating or doing a reverse migration? Do I have to go back to my data center or are there other alternatives? And we're seeing that trend a lot. And our roadmap and what we have in the product today was specifically built to handle those, those occurrences. So we brought in KubeVirt in terms of virtualization. We have a long legacy doing OpenStack and private clouds. And we've worked with a lot of those users and customers that we have and asked the questions, what's important? And today, when we look at the world of Cloud Native, you can run virtualization within Kubernetes. So you can, instead of running two separate platforms, you can have one. So all of a sudden, if you're looking to modernize, you can start on that new infrastructure stack that can run anywhere, Kubernetes, and you can start bringing VMs over there as you are containerizing at the same time. So now you can keep your application operations in one environment. And this also helps if you're trying to reduce costs. If you really are saying, we put that Dev environment in AWS, we've got a huge amount of velocity out of it now, can we do that elsewhere? Is there a co-location we can go to? Is there a provider that we can go to where we can run that infrastructure or run the Kubernetes, but not have to run the infrastructure? >> It's going to be interesting too, when you see the Edge come online, you start, we've got Mobile World Congress coming up, KubeCon events we're going to be at, the conversation is not just about public cloud. And you guys obviously solve a lot of do-it-yourself implementation hassles that emerge when people try to kind of stand up their own environment. And we hear from developers consistency between code, managing new updates, making sure everything is all solid so they can go fast. That's the goal. And that, and then people can get standardized on that. But as you get public cloud and do it yourself, kind of brings up like, okay, there's some gaps there as the architecture changes to be more distributed computing, Edge, on-premises cloud, it's cloud operations. So that's cool for DevOps and Cloud Native. How do you guys differentiate from say, some the public cloud opportunities and the folks who are doing it themselves? How do you guys fit in that world and what's the pitch or what's the story? >> The fit that we look at is that third alternative. Let's get your team focused on what's high value to your business and let us deliver that public cloud experience on your infrastructure or in the public cloud, which gives you that ability to still be flexible if you want to make choices to run consistently for your developers in two different locations. So as I touched on earlier, instead of saying go figure out Kubernetes, how do you upgrade a hundred worker nodes in place upgrade. We've solved that problem. That's what we do every single day of the week. Don't go and try to figure out how to upgrade a cluster and then upgrade all of the, what I call Kubernetes friends, your core DNSs, your metrics server, your Kubernetes dashboard. These are all things that we package, we test, we version. So when you click upgrade, we've already handled that entire process. So it's saying don't have your team focused on that lower level piece of work. Get them focused on what is important, which is your business services. >> Yeah, the infrastructure and getting that stood up. I mean, I think the thing that's interesting, if you look at the market right now, you mentioned cost savings and recovery, obviously kind of a recession. I mean, people are tightening their belts for sure. I don't think the digital transformation and Cloud Native spend is going to plummet. It's going to probably be on hold and be squeezed a little bit. But to your point, people are refactoring looking at how to get the best out of what they got. It's not just open the tap of spend the cash like it used to be. Yeah, a couple months, even a couple years ago. So okay, I get that. But then you look at the what's coming, AI. You're seeing all the new data infrastructure that's coming. The containers, Kubernetes stuff, got to get stood up pretty quickly and it's got to be reliable. So to your point, the teams need to get done with this and move on to the next thing. >> Chris: Yeah, yeah, yeah. >> 'Cause there's more coming. I mean, there's a lot coming for the apps that are building in Data Native, AI-Native, Cloud Native. So it seems that this Kubernetes thing needs to get solved. Is that kind of what you guys are focused on right now? >> So, I mean to use a customer, we have a customer that's in AI/ML and they run their platform at customer sites and that's hardware bound. You can't run AI machine learning on anything anywhere. Well, with Platform9 they can. So we're enabling them to deliver services into their customers that's running their AI/ML platform in their customer's data centers anywhere in the world on hardware that is purpose-built for running that workload. They're not Kubernetes experts. That's what we are. We're bringing them that ability to focus on what's important and just delivering their business services whilst they're enabling our team. And our 24 by seven proactive management are always on assurance to keep that up and running for them. So when something goes bump at the night at 2:00am, our guys get woken up. They're the ones that are reaching out to the customer saying, your environments have a problem, we're taking these actions to fix it. Obviously sometimes, especially if it is running on Bare Metal, there's things you can't do remotely. So you might need someone to go and do that. But even when that happens, you're not by yourself. You're not sitting there like I did when I worked for a bank in one of my first jobs, three o'clock in the morning saying, wow, our end of day processing is stuck. Who else am I waking up? Right? >> Exactly, yeah. Got to get that cash going. But this is a great use case. I want to get to the customer. What do some of the successful customers say to you for the folks watching that aren't yet a customer of Platform9, what are some of the accolades and comments or anecdotes that you guys hear from customers that you have? >> It just works, which I think is probably one of the best ones you can get. Customers coming back and being able to show to their business that they've delivered growth, like business growth and productivity growth and keeping their organization size the same. So we started on our containerization journey. We went to Kubernetes. We've deployed all these new workloads and our operations team is still six people. We're doing way more with growth less, and I think that's also talking to the strength that we're bringing, 'cause we're, we're augmenting that team. They're spending less time on the really low level stuff and automating a lot of the growth activity that's involved. So when it comes to being able to grow their business, they can just focus on that, not- >> Well you guys do the heavy lifting, keep on top of the Kubernetes, make sure that all the versions are all done. Everything's stable and consistent so they can go on and do the build out and provide their services. That seems to be what you guys are best at. >> Correct, correct. >> And so what's on the roadmap? You have the product, direct product management, you get the keys to the kingdom. What is, what is the focus? What's your focus right now? Obviously Kubernetes is growing up, Containers. We've been hearing a lot at the last KubeCon about the security containers is getting better. You've seen verification, a lot more standards around some things. What are you focused on right now for at a product over there? >> Edge is a really big focus for us. And I think in Edge you can look at it in two ways. The mantra that I drive is Edge must be remote. If you can't do something remotely at the Edge, you are using a human being, that's not Edge. Our Edge management capabilities and being in the market for over two years are a hundred percent remote. You want to stand up a store, you just ship the server in there, it gets racked, the rest of it's remote. Imagine a store manager in, I don't know, KFC, just plugging in the server, putting in the ethernet cable, pressing the power button. The rest of all that provisioning for that Cloud Native stack, Kubernetes, KubeVirt for virtualization is done remotely. So we're continuing to focus on that. The next piece that is related to that is allowing people to run Platform9 SaaS in their data centers. So we do ag app today and we've had a really strong focus on telecommunications and the containerized network functions that come along with that. So this next piece is saying, we're bringing what we run as SaaS into your data center, so then you can run it. 'Cause there are many people out there that are saying, we want these capabilities and we want everything that the Platform9 control plane brings and simplifies. But unfortunately, regulatory compliance reasons means that we can't leverage SaaS. So they might be using a cloud, but they're saying that's still our infrastructure. We're still closed that network down, or they're still on-prem. So they're two big priorities for us this year. And that on-premise experiences is paramount, even to the point that we will be delivering a way that when you run an on-premise, you can still say, wait a second, well I can send outbound alerts to Platform9. So their support team can still be proactively helping me as much as they could, even though I'm running Platform9s control plane. So it's sort of giving that blend of two experiences. They're big, they're big priorities. And the third pillar is all around virtualization. It's saying if you have economic pressures, then I think it's important to look at what you're spending today and realistically say, can that be reduced? And I think hypervisors and virtualization is something that should be looked at, because if you can actually reduce that spend, you can bring in some modernization at the same time. Let's take some of those nos that exist that are two years into their five year hardware life cycle. Let's turn that into a Cloud Native environment, which is enabling your modernization in place. It's giving your engineers and application developers the new toys, the new experiences, and then you can start running some of those virtualized workloads with KubeVirt, there. So you're reducing cost and you're modernizing at the same time with your existing infrastructure. >> You know Chris, the topic of this content series that we're doing with you guys is finding the right path, trusting the right path to Cloud Native. What does that mean? I mean, if you had to kind of summarize that phrase, trusting the right path to Cloud Native, what does that mean? It mean in terms of architecture, is it deployment? Is it operations? What's the underlying main theme of that quote? What's the, what's? How would you talk to a customer and say, what does that mean if someone said, "Hey, what does that right path mean?" >> I think the right path means focusing on what you should be focusing on. I know I've said it a hundred times, but if your entire operations team is trying to figure out the nuts and bolts of Kubernetes and getting three months into a journey and discovering, ah, I need Metrics Server to make something function. I want to use Horizontal Pod Autoscaler or Vertical Pod Autoscaler and I need this other thing, now I need to manage that. That's not the right path. That's literally learning what other people have been learning for the last five, seven years that have been focused on Kubernetes solely. So the why- >> There's been a lot of grind. People have been grinding it out. I mean, that's what you're talking about here. They've been standing up the, when Kubernetes started, it was all the promise. >> Chris: Yep. >> And essentially manually kind of getting in in the weeds and configuring it. Now it's matured up. They want stability. >> Chris: Yeah. >> Not everyone can get down and dirty with Kubernetes. It's not something that people want to generally do unless you're totally into it, right? Like I mean, I mean ops teams, I mean, yeah. You know what I mean? It's not like it's heavy lifting. Yeah, it's important. Just got to get it going. >> Yeah, I mean if you're deploying with Platform9, your Ops teams can tinker to their hearts content. We're completely compliant upstream Kubernetes. You can go and change an API server flag, let's go and mess with the scheduler, because we want to. You can still do that, but don't, don't have your team investing in all this time to figure it out. It's been figured out. >> John: Got it. >> Get them focused on enabling velocity for your business. >> So it's not build, but run. >> Chris: Correct? >> Or run Kubernetes, not necessarily figure out how to kind of get it all, consume it out. >> You know we've talked to a lot of customers out there that are saying, "I want to be able to deliver a service to my users." Our response is, "Cool, let us run it. You consume it, therefore deliver it." And we're solving that in one hit versus figuring out how to first run it, then operate it, then turn that into a consumable service. >> So the alternative Platform9 is what? They got to do it themselves or use the Cloud or what's the, what's the alternative for the customer for not using Platform9? Hiring more people to kind of work on it? What's the? >> People, building that kind of PaaS experience? Something that I've been very passionate about for the past year is looking at that world of sort of GitOps and what that means. And if you go out there and you sort of start asking the question what's happening? Just generally with Kubernetes as well and GitOps in that scope, then you'll hear some people saying, well, I'm making it PaaS, because Kubernetes is too complicated for my developers and we need to give them something. There's some great material out there from the likes of Intuit and Adobe where for two big contributors to Argo and the Argo projects, they almost have, well they do have, different experiences. One is saying, we went down the PaaS route and it failed. The other one is saying, well we've built a really stable PaaS and it's working. What are they trying to do? They're trying to deliver an outcome to make it easy to use and consume Kubernetes. So you could go out there and say, hey, I'm going to build a Kubernetes cluster. Sounds like Argo CD is a great way to expose that to my developers so they can use Kubernetes without having to use Kubernetes and start automating things. That is an approach, but you're going to be going completely open source and you're going to have to bring in all the individual components, or you could just lay that, lay it down, and consume it as a service and not have to- >> And mentioned to it. They were the ones who kind of brought that into the open. >> They did. Inuit is the primary contributor to the Argo set of products. >> How has that been received in the market? I mean, they had the event at the Computer History Museum last fall. What's the momentum there? What's the big takeaway from that project? >> Growth. To me, growth. I mean go and track the stars on that one. It's just, it's growth. It's unlocking machine learning. Argo workflows can do more than just make things happen. Argo CD I think the approach they're taking is, hey let's make this simple to use, which I think can be lost. And I think credit where credit's due, they're really pushing to bring in a lot of capabilities to make it easier to work with applications and microservices on Kubernetes. It's not just that, hey, here's a GitOps tool. It can take something from a Git repo and deploy it and maybe prioritize it and help you scale your operations from that perspective. It's taking a step back and saying, well how did we get to production in the first place? And what can be done down there to help as well? I think it's growth expansion of features. They had a huge release just come out in, I think it was 2.6, that brought in things that as a product manager that I don't often look at like really deep technical things and say wow, that's powerful. But they have, they've got some great features in that release that really do solve real problems. >> And as the product, as the product person, who's the target buyer for you? Who's the customer? Who's making that? And you got decision maker, influencer, and recommender. Take us through the customer persona for you guys. >> So that Platform Ops, DevOps space, right, the people that need to be delivering Containers as a service out to their organization. But then it's also important to say, well who else are our primary users? And that's developers, engineers, right? They shouldn't have to say, oh well I have access to a Kubernetes cluster. Do I have to use kubectl or do I need to go find some other tool? No, they can just log to Platform9. It's integrated with your enterprise id. >> They're the end customer at the end of the day, they're the user. >> Yeah, yeah. They can log in. And they can see the clusters you've given them access to as a Platform Ops Administrator. >> So job well done for you guys. And your mind is the developers are moving 'em fast, coding and happy. >> Chris: Yeah, yeah. >> And and from a customer standpoint, you reduce the maintenance cost, because you keep the Ops smoother, so you got efficiency and maintenance costs kind of reduced or is that kind of the benefits? >> Yeah, yep, yeah. And at two o'clock in the morning when things go inevitably wrong, they're not there by themselves, and we're proactively working with them. >> And that's the uptime issue. >> That is the uptime issue. And Cloud doesn't solve that, right? Everyone experienced that Clouds can go down, entire regions can go offline. That's happened to all Cloud providers. And what do you do then? Kubernetes isn't your recovery plan. It's part of it, right, but it's that piece. >> You know Chris, to wrap up this interview, I will say that "theCUBE" is 12 years old now. We've been to OpenStack early days. We had you guys on when we were covering OpenStack and now Cloud has just been booming. You got AI around the corner, AI Ops, now you got all this new data infrastructure, it's just amazing Cloud growth, Cloud Native, Security Native, Cloud Native, Data Native, AI Native. It's going to be all, this is the new app environment, but there's also existing infrastructure. So going back to OpenStack, rolling our own cloud, building your own cloud, building infrastructure cloud, in a cloud way, is what the pioneers have done. I mean this is what we're at. Now we're at this scale next level, abstracted away and make it operational. It seems to be the key focus. We look at CNCF at KubeCon and what they're doing with the cloud SecurityCon, it's all about operations. >> Chris: Yep, right. >> Ops and you know, that's going to sound counterintuitive 'cause it's a developer open source environment, but you're starting to see that Ops focus in a good way. >> Chris: Yeah, yeah, yeah. >> Infrastructure as code way. >> Chris: Yep. >> What's your reaction to that? How would you summarize where we are in the industry relative to, am I getting, am I getting it right there? Is that the right view? What am I missing? What's the current state of the next level, NextGen infrastructure? >> It's a good question. When I think back to sort of late 2019, I sort of had this aha moment as I saw what really truly is delivering infrastructure as code happening at Platform9. There's an open source project Ironic, which is now also available within Kubernetes that is Metal Kubed that automates Bare Metal as code, which means you can go from an empty server, lay down your operating system, lay down Kubernetes, and you've just done everything delivered to your customer as code with a Cloud Native platform. That to me was sort of the biggest realization that I had as I was moving into this industry was, wait, it's there. This can be done. And the evolution of tooling and operations is getting to the point where that can be achieved and it's focused on by a number of different open source projects. Not just Ironic and and Metal Kubed, but that's a huge win. That is truly getting your infrastructure. >> John: That's an inflection point, really. >> Yeah. >> If you think about it, 'cause that's one of the problems. We had with the Bare Metal piece was the automation and also making it Cloud Ops, cloud operations. >> Right, yeah. I mean, one of the things that I think Ironic did really well was saying let's just treat that piece of Bare Metal like a Cloud VM or an instance. If you got a problem with it, just give the person using it or whatever's using it, a new one and reimage it. Just tell it to reimage itself and it'll just (snaps fingers) go. You can do self-service with it. In Platform9, if you log in to our SaaS Ironic, you can go and say, I want that physical server to myself, because I've got a giant workload, or let's turn it into a Kubernetes cluster. That whole thing is automated. To me that's infrastructure as code. I think one of the other important things that's happening at the same time is we're seeing GitOps, we're seeing things like Terraform. I think it's important for organizations to look at what they have and ask, am I using tools that are fit for tomorrow or am I using tools that are yesterday's tools to solve tomorrow's problems? And when especially it comes to modernizing infrastructure as code, I think that's a big piece to look at. >> Do you see Terraform as old or new? >> I see Terraform as old. It's a fantastic tool, capable of many great things and it can work with basically every single provider out there on the planet. It is able to do things. Is it best fit to run in a GitOps methodology? I don't think it is quite at that point. In fact, if you went and looked at Flux, Flux has ways that make Terraform GitOps compliant, which is absolutely fantastic. It's using two tools, the best of breeds, which is solving that tomorrow problem with tomorrow solutions. >> Is the new solutions old versus new. I like this old way, new way. I mean, Terraform is not that old and it's been around for about eight years or so, whatever. But HashiCorp is doing a great job with that. I mean, so okay with Terraform, what's the new address? Is it more complex environments? Because Terraform made sense when you had basic DevOps, but now it sounds like there's a whole another level of complexity. >> I got to say. >> New tools. >> That kind of amalgamation of that application into infrastructure. Now my app team is paying way more attention to that manifest file, which is what GitOps is trying to solve. Let's templatize things. Let's version control our manifest, be it helm, customize, or just a straight up Kubernetes manifest file, plain and boring. Let's get that version controlled. Let's make sure that we know what is there, why it was changed. Let's get some auditability and things like that. And then let's get that deployment all automated. So that's predicated on the cluster existing. Well why can't we do the same thing with the cluster, the inception problem. So even if you're in public cloud, the question is like, well what's calling that API to call that thing to happen? Where is that file living? How well can I manage that in a large team? Oh my God, something just changed. Who changed it? Where is that file? And I think that's one of big, the big pieces to be sold. >> Yeah, and you talk about Edge too and on-premises. I think one of the things I'm observing and certainly when DevOps was rocking and rolling and infrastructures code was like the real push, it was pretty much the public cloud, right? >> Chris: Yep. >> And you did Cloud Native and you had stuff on-premises. Yeah you did some lifting and shifting in the cloud, but the cool stuff was going in the public cloud and you ran DevOps. Okay, now you got on-premise cloud operation and Edge. Is that the new DevOps? I mean 'cause what you're kind of getting at with old new, old new Terraform example is an interesting point, because you're pointing out potentially that that was good DevOps back in the day or it still is. >> Chris: It is, I was going to say. >> But depending on how you define what DevOps is. So if you say, I got the new DevOps with public on-premise and Edge, that's just not all public cloud, that's essentially distributed Cloud Native. >> Correct. Is that the new DevOps in your mind or is that? How would you, or is that oversimplifying it? >> Or is that that term where everyone's saying Platform Ops, right? Has it shifted? >> Well you bring up a good point about Terraform. I mean Terraform is well proven. People love it. It's got great use cases and now there seems to be new things happening. We call things like super cloud emerging, which is multicloud and abstraction layers. So you're starting to see stuff being abstracted away for the benefits of moving to the next level, so teams don't get stuck doing the same old thing. They can move on. Like what you guys are doing with Platform9 is providing a service so that teams don't have to do it. >> Correct, yeah. >> That makes a lot of sense, So you just, now it's running and then they move on to the next thing. >> Chris: Yeah, right. >> So what is that next thing? >> I think Edge is a big part of that next thing. The propensity for someone to put up with a delay, I think it's gone. For some reason, we've all become fairly short-tempered, Short fused. You know, I click the button, it should happen now, type people. And for better or worse, hopefully it gets better and we all become a bit more patient. But how do I get more effective and efficient at delivering that to that really demanding- >> I think you bring up a great point. I mean, it's not just people are getting short-tempered. I think it's more of applications are being deployed faster, security is more exposed if they don't see things quicker. You got data now infrastructure scaling up massively. So, there's a double-edged swords to scale. >> Chris: Yeah, yeah. I mean, maintenance, downtime, uptime, security. So yeah, I think there's a tension around, and one hand enthusiasm around pushing a lot of code and new apps. But is the confidence truly there? It's interesting one little, (snaps finger) supply chain software, look at Container Security for instance. >> Yeah, yeah. It's big. I mean it was codified. >> Do you agree that people, that's kind of an issue right now. >> Yeah, and it was, I mean even the supply chain has been codified by the US federal government saying there's things we need to improve. We don't want to see software being a point of vulnerability, and software includes that whole process of getting it to a running point. >> It's funny you mentioned remote and one of the thing things that you're passionate about, certainly Edge has to be remote. You don't want to roll a truck or labor at the Edge. But I was doing a conversation with, at Rebars last year about space. It's hard to do brake fix on space. It's hard to do a, to roll a someone to configure satellite, right? Right? >> Chris: Yeah. >> So Kubernetes is in space. We're seeing a lot of Cloud Native stuff in apps, in space, so just an example. This highlights the fact that it's got to be automated. Is there a machine learning AI angle with all this ChatGPT talk going on? You see all the AI going the next level. Some pretty cool stuff and it's only, I know it's the beginning, but I've heard people using some of the new machine learning, large language models, large foundational models in areas I've never heard of. Machine learning and data centers, machine learning and configuration management, a lot of different ways. How do you see as the product person, you incorporating the AI piece into the products for Platform9? >> I think that's a lot about looking at the telemetry and the information that we get back and to use one of those like old idle terms, that continuous improvement loop to feed it back in. And I think that's really where machine learning to start with comes into effect. As we run across all these customers, our system that helps at two o'clock in the morning has that telemetry, it's got that data. We can see what's changing and what's happening. So it's writing the right algorithms, creating the right machine learning to- >> So training will work for you guys. You have enough data and the telemetry to do get that training data. >> Yeah, obviously there's a lot of investment required to get there, but that is something that ultimately that could be achieved with what we see in operating people's environments. >> Great. Chris, great to have you here in the studio. Going wide ranging conversation on Kubernetes and Platform9. I guess my final question would be how do you look at the next five years out there? Because you got to run the product management, you got to have that 20 mile steer, you got to look at the customers, you got to look at what's going on in the engineering and you got to kind of have that arc. This is the right path kind of view. What's the five year arc look like for you guys? How do you see this playing out? 'Cause KubeCon is coming up and we're you seeing Kubernetes kind of break away with security? They had, they didn't call it KubeCon Security, they call it CloudNativeSecurityCon, they just had in Seattle inaugural events seemed to go well. So security is kind of breaking out and you got Kubernetes. It's getting bigger. Certainly not going away, but what's your five year arc of of how Platform9 and Kubernetes and Ops evolve? >> It's to stay on that theme, it's focusing on what is most important to our users and getting them to a point where they can just consume it, so they're not having to operate it. So it's finding those big items and bringing that into our platform. It's something that's consumable, that's just taken care of, that's tested with each release. So it's simplifying operations more and more. We've always said freedom in cloud computing. Well we started on, we started on OpenStack and made that simple. Stable, easy, you just have it, it works. We're doing that with Kubernetes. We're expanding out that user, right, we're saying bring your developers in, they can download their Kube conflict. They can see those Containers that are running there. They can access the events, the log files. They can log in and build a VM using KubeVirt. They're self servicing. So it's alleviating pressures off of the Ops team, removing the help desk systems that people still seem to rely on. So it's like what comes into that field that is the next biggest issue? Is it things like CI/CD? Is it simplifying GitOps? Is it bringing in security capabilities to talk to that? Or is that a piece that is a best of breed? Is there a reason that it's been spun out to its own conference? Is this something that deserves a focus that should be a specialized capability instead of tooling and vendors that we work with, that we partner with, that could be brought in as a service. I think it's looking at those trends and making sure that what we bring in has the biggest impact to our users. >> That's awesome. Thanks for coming in. I'll give you the last word. Put a plug in for Platform9 for the people who are watching. What should they know about Platform9 that they might not know about it or what should? When should they call you guys and when should they engage? Take a take a minute to give the plug. >> The plug. I think it's, if your operations team is focused on building Kubernetes, stop. That shouldn't be the cloud. That shouldn't be in the Edge, that shouldn't be at the data center. They should be consuming it. If your engineering teams are all trying different ways and doing different things to use and consume Cloud Native services and Kubernetes, they shouldn't be. You want consistency. That's how you get economies of scale. Provide them with a simple platform that's integrated with all of your enterprise identity where they can just start consuming instead of having to solve these problems themselves. It's those, it's those two personas, right? Where the problems manifest. What are my operations teams doing, and are they delivering to my company or are they building infrastructure again? And are my engineers sprinting or crawling? 'Cause if they're not sprinting, you should be asked the question, do I have the right Cloud Native tooling in my environment and how can I get them back? >> I think it's developer productivity, uptime, security are the tell signs. You get that done. That's the goal of what you guys are doing, your mission. >> Chris: Yep. >> Great to have you on, Chris. Thanks for coming on. Appreciate it. >> Chris: Thanks very much. 0 Okay, this is "theCUBE" here, finding the right path to Cloud Native. I'm John Furrier, host of "theCUBE." Thanks for watching. (upbeat music)

>> Hello everyone. Welcome to theCUBEs coverage of Compute Engineered for your Hybrid World sponsored by HPE and Intel. Today we're going to dive into advanced performance of VDI with the fourth gen Intel Zion scalable processors. Hello I'm John Furrier, the host of theCUBE. My guests today are Alan Chu, Director of Data Center Performance and Competition for Intel as well as Denis Kondakov who's the VDI product manager at HPE, and also joining us is Cynthia Sustiva, CAD/CAM product manager at HPE. Thanks for coming on, really appreciate you guys taking the time. >> Thank you. >> So accelerating VDI to the Edge. That's the topic of this topic here today. Let's get into it, Dennis, tell us about the new HPE ProLiant DL321 Gen 11 server. >> Okay, absolutely. Hello everybody. So HP ProLiant DL320 Gen 11 server is the new age center CCO and density optimized compact server, compact form factor server. It enables to modernize and power at the next generation of workloads in the diverse rec environment at the Edge in an industry standard designed with flexible scale for advanced graphics and compute. So it is one unit, one processor rec optimized server that can be deployed in the enterprise data center as well as at the remote office at end age. >> Cynthia HPE has announced another server, the ProLiant ML350. What can you tell us about that? >> Yeah, so the HPE ProLiant ML350 Gen 11 server is a powerful tower solution for a wide range of workloads. It is ideal for remote office compute with NextGen performance and expandability with two processors in tower form factor. This enables the server to be used not only in the data center environment, but also in the open office space as a powerful workstation use case. >> Dennis mentioned both servers are empowered by the fourth gen Intel Zion scale of process. Can you talk about the relationship between Intel HPE to get this done? How do you guys come together, what's behind the scenes? Share as much as you can. >> Yeah, thanks a lot John. So without a doubt it takes a lot to put all this together and I think the partnership that HPE and Intel bring together is a little bit of a critical point for us to be able to deliver to our customers. And I'm really thrilled to say that these leading Edge solutions that Dennis and Cynthia just talked about, they're built on the foundation of our fourth Gen Z on scalable platform that's trying to meet a wide variety of deployments for today and into the future. So I think the key point of it is we're together trying to drive leading performance with built-in acceleration and in order to deliver a lot of the business values to our customers, both HP and Intels, look to scale, drive down costs and deliver new services. >> You got the fourth Gen Z on, you got the Gen 11 and multiple ProLiants, a lot of action going on. Again, I love when these next gens come out. Can each of you guys comment and share what are the use cases for each of the systems? Because I think what we're looking at here is the next level innovation. What are some of the use cases on the systems? >> Yeah, so for the ML350, in the modern world where more and more data are generated at the Edge, we need to deploy computer infrastructure where the data is generated. So smaller form factor service will satisfy the requirements of S&B customers or remote and branch offices to deliver required performance redundancy where we're needed. This type of locations can be lacking dedicated facilities with strict humidity, temperature and noise isolation control. The server, the ML350 Gen 11 can be used as a powerful workstation sitting under a desk in the office or open space as well as the server for visualized workloads. It is a productivity workhorse with the ability to scale and adapt to any environment. One of the use cases can be for hosting digital workplace for manufacturing CAD/CAM engineering or oil and gas customers industry. So this server can be used as a high end bare metal workstation for local end users or it can be virtualized desktop solution environments for local and remote users. And talk about the DL320 Gen 11, I will pass it on to Dennis. >> Okay. >> Sure. So when we are talking about age of location we are talking about very specific requirements. So we need to provide solution building blocks that will empower and performance efficient, secure available for scaling up and down in a smaller increments than compared to the enterprise data center and of course redundant. So DL 320 Gen 11 server is the perfect server to satisfy all of those requirements. So for example, S&B customers can build a video solution, for example starting with just two HP ProLiant TL320 Gen 11 servers that will provide sufficient performance for high density video solution and at the same time be redundant and enable it for scaling up as required. So for VGI use cases it can be used for high density general VDI without GP acceleration or for a high performance VDI with virtual VGPU. So thanks to the modern modular architecture that is used on the server, it can be tailored for GPU or high density storage deployment with software defined compute and storage environment and to provide greater details on your Intel view I'm going to pass to Alan. >> Thanks a lot Dennis and I loved how you're both seeing the importance of how we scale and the applicability of the use cases of both the ML350 and DL320 solutions. So scalability is certainly a key tenant towards how we're delivering Intel's Zion scalable platform. It is called Zion scalable after all. And we know that deployments are happening in all different sorts of environments. And I think Cynthia you talked a little bit about kind of a environmental factors that go into how we're designing and I think a lot of people think of a traditional data center with all the bells and whistles and cooling technology where it sometimes might just be a dusty closet in the Edge. So we're defining fortunes you see on scalable to kind of tackle all those different environments and keep that in mind. Our SKUs range from low to high power, general purpose to segment optimize. We're supporting long life use cases so that all goes into account in delivering value to our customers. A lot of the latency sensitive nature of these Edge deployments also benefit greatly from monolithic architectures. And with our latest CPUs we do maintain quite a bit of that with many of our SKUs and delivering higher frequencies along with those SKUs optimized for those specific workloads in networking. So in the end we're looking to drive scalability. We're looking to drive value in a lot of our end users most important KPIs, whether it's latency throughput or efficiency and 4th Gen Z on scalable is looking to deliver that with 60 cores up to 60 cores, the most builtin accelerators of any CPUs in the market. And really the true technology transitions of the platform with DDR5, PCIE, Gen five and CXL. >> Love the scalability story, love the performance. We're going to take a break. Thanks Cynthia, Dennis. Now we're going to come back on our next segment after a quick break to discuss the performance and the benefits of the fourth Gen Intel Zion Scalable. You're watching theCUBE, the leader in high tech coverage, be right back. Welcome back around. We're continuing theCUBE's coverage of compute engineer for your hybrid world. I'm John Furrier, I'm joined by Alan Chu from Intel and Denis Konikoff and Cynthia Sistia from HPE. Welcome back. Cynthia, let's start with you. Can you tell us the benefits of the fourth Gen Intel Zion scale process for the HP Gen 11 server? >> Yeah, so HP ProLiant Gen 11 servers support DDR five memory which delivers increased bandwidth and lower power consumption. There are 32 DDR five dim slots with up to eight terabyte total on ML350 and 16 DDR five dim slots with up to two terabytes total on DL320. So we deliver more memory at a greater bandwidth. Also PCIE 5.0 delivers an increased bandwidth and greater number of lanes. So when we say increased number of lanes we need to remember that each lane delivers more bandwidth than lanes of the previous generation plus. Also a flexible storage configuration on HPDO 320 Gen 11 makes it an ideal server for establishing software defined compute and storage solution at the Edge. When we consider a server for VDI workloads, we need to keep the right balance between the number of cords and CPU frequency in order to deliver the desire environment density and noncompromised user experience. So the new server generation supports a greater number of single wide and global wide GPU use to deliver more graphic accelerated virtual desktops per server unit than ever before. HPE ProLiant ML 350 Gen 11 server supports up to four double wide GPUs or up to eight single wide GPUs. When the signing GPU accelerated solutions the number of GPUs available in the system and consistently the number of BGPUs that can be provisioned for VMs in the binding factor rather than CPU course or memory. So HPE ProLiant Gen 11 servers with Intel fourth generation science scalable processors enable us to deliver more virtual desktops per server than ever before. And with that I will pass it on to Alan to provide more details on the new Gen CPU performance. >> Thanks Cynthia. So you brought up I think a really great point earlier about the importance of achieving the right balance. So between the both of us, Intel and HPE, I'm sure we've heard countless feedback about how we should be optimizing efficiency for our customers and with four Gen Z and scalable in HP ProLiant Gen 11 servers I think we achieved just that with our built-in accelerator. So built-in acceleration delivers not only the revolutionary performance, but enables significant offload from valuable core execution. That offload unlocks a lot of previously unrealized execution efficiency. So for example, with quick assist technology built in, running engine X, TLS encryption to drive 65,000 connections per second we can offload up to 47% of the course that do other work. Accelerating AI inferences with AMX, that's 10X higher performance and we're now unlocking realtime inferencing. It's becoming an element in every workload from the data center to the Edge. And lastly, so with faster and more efficient database performance with RocksDB, we're executing with Intel in-memory analytics accelerator we're able to deliver 2X the performance per watt than prior gen. So I'll say it's that kind of offload that is really going to enable more and more virtualized desktops or users for any given deployment. >> Thanks everyone. We still got a lot more to discuss with Cynthia, Dennis and Allen, but we're going to take a break. Quick break before wrapping things up. You're watching theCUBE, the leader in tech coverage. We'll be right back. Okay, welcome back everyone to theCUBEs coverage of Compute Engineered for your Hybrid World. I'm John Furrier. We'll be wrapping up our discussion on advanced performance of VDI with the fourth gen Intel Zion scalable processers. Welcome back everyone. Dennis, we'll start with you. Let's continue our conversation and turn our attention to security. Obviously security is baked in from day zero as they say. What are some of the new security features or the key security features for the HP ProLiant Gen 11 server? >> Sure, I would like to start with the balance, right? We were talking about performance, we were talking about density, but Alan mentioned about the balance. So what about the security? The security is really important aspect especially if we're talking about solutions deployed at the H. When the security is not active but other aspects of the environment become non-important. And HP is uniquely positioned to deliver the best in class security solution on the market starting with the trusted supply chain and factories and silicon route of trust implemented from the factory. So the new ISO6 supports added protection leveraging SPDM for component authorization and not only enabled for the embedded server management, but also it is integrated with HP GreenLake compute ops manager that enables environment for secure and optimized configuration deployment and even lifecycle management starting from the single server deployed on the Edge and all the way up to the full scale distributed data center. So it brings uncompromised and trusted solution to customers fully protected at all tiers, hardware, firmware, hypervisor, operational system application and data. And the new intel CPUs play an important role in the securing of the platform. So Alan- >> Yeah, thanks. So Intel, I think our zero trust strategy toward security is a really great and a really strong parallel to all the focus that HPE is also bringing to that segment and market. We have even invested in a lot of hardware enabled security technologies like SGX designed to enhance data protection at rest in motion and in use. SGX'S application isolation is the most deployed, researched and battle tested confidential computing technology for the data center market and with the smallest trust boundary of any solution in market. So as we've talked about a little bit about virtualized use cases a lot of virtualized applications rely also on encryption whether bulk or specific ciphers. And this is again an area where we've seen the opportunity for offload to Intel's quick assist technology to encrypt within a single data flow. I think Intel and HP together, we are really providing security at all facets of execution today. >> I love that Software Guard Extension, SGX, also silicon root of trust. We've heard a lot about great stuff. Congratulations, security's very critical as we see more and more. Got to be embedded, got to be completely zero trust. Final question for you guys. Can you share any messages you'd like to share with the audience each of you, what should they walk away from this? What's in it for them? What does all this mean? >> Yeah, so I'll start. Yes, so to wrap it up, HPR Proliant Gen 11 servers are built on four generation science scalable processors to enable high density and extreme performance with high performance CDR five memory and PCI 5.0 plus HP engine engineered and validated workload solutions provide better ROI in any consumption model and prefer by a customer from Edge to Cloud. >> Dennis? >> And yeah, so you are talking about all of the great features that the new generation servers are bringing to our customers, but at the same time, customer IT organization should be ready to enable, configure, support, and fine tune all of these great features for the new server generation. And this is not an obvious task. It requires investments, skills, knowledge and experience. And HP is ready to step up and help customers at any desired skill with the HP Greenlake H2 cloud platform that enables customers for cloud like experience and convenience and the flexibility with the security of the infrastructure deployed in the private data center or in the Edge. So while consuming all of the HP solutions, customer have flexibility to choose the right level of the service delivered from HP GreenLake, starting from hardwares as a service and scale up or down is required to consume the full stack of the hardwares and software as a service with an option to paper use. >> Awesome. Alan, final word. >> Yeah. What should we walk away with? >> Yeah, thanks. So I'd say that we've talked a lot about the systems here in question with HP ProLiant Gen 11 and they're delivering on a lot of the business outcomes that our customers require in order to optimize for operational efficiency or to optimize for just to, well maybe just to enable what they want to do in, with their customers enabling new features, enabling new capabilities. Underpinning all of that is our fourth Gen Zion scalable platform. Whether it's the technology transitions that we're driving with DDR5 PCIA Gen 5 or the raw performance efficiency and scalability of the platform in CPU, I think we're here for our customers in delivering to it. >> That's great stuff. Alan, Dennis, Cynthia, thank you so much for taking the time to do a deep dive in the advanced performance of VDI with the fourth Gen Intel Zion scalable process. And congratulations on Gen 11 ProLiant. You get some great servers there and again next Gen's here. Thanks for taking the time. >> Thank you so much for having us here. >> Okay, this is theCUBEs keeps coverage of Compute Engineered for your Hybrid World sponsored by HP and Intel. I'm John Furrier for theCUBE. Accelerate VDI at the Edge. Thanks for watching.

(cheerful music) >> Welcome to theCUBE's continuing coverage of AMD's 4th Generation EPYC launch. I'm Dave Nicholson, and I'm here in our Palo Alto studios talking to Greg Gibby, senior product manager, data center products from AMD, and Mohan Rokkam, technical marketing engineer at Dell. Welcome, gentlemen. >> Mohan: Hello, hello. >> Greg: Thank you. Glad to be here. >> Good to see each of you. Just really quickly, I want to start out. Let us know a little bit about yourselves. Mohan, let's start with you. What do you do at Dell exactly? >> So I'm a technical marketing engineer at Dell. I've been with Dell for around 15 years now and my goal is to really look at the Dell powered servers and see how do customers take advantage of some of the features we have, especially with the AMD EPYC processors that have just come out. >> Greg, and what do you do at AMD? >> Yeah, so I manage our software-defined infrastructure solutions team, and really it's a cradle to grave where we work with the ISVs in the market, so VMware, Nutanix, Microsoft, et cetera, to integrate the features that we're putting into our processors and make sure they're ready to go and enabled. And then we work with our valued partners like Dell on putting those into actual solutions that customers can buy and then we work with them to sell those solutions into the market. >> Before we get into the details on the 4th Generation EPYC launch and what that means and why people should care. Mohan, maybe you can tell us a little about the relationship between Dell and AMD, how that works, and then Greg, if you've got commentary on that afterwards, that'd be great. Yeah, Mohan. >> Absolutely. Dell and AMD have a long standing partnership, right? Especially now with EPYC series. We have had products since EPYC first generation. We have been doing solutions across the whole range of Dell ecosystem. We have integrated AMD quite thoroughly and effectively and we really love how performant these systems are. So, yeah. >> Dave: Greg, what are your thoughts? >> Yeah, I would say the other thing too is, is that we need to point out is that we both have really strong relationships across the entire ecosystem. So memory vendors, the software providers, et cetera, we have technical relationships. We're working with them to optimize solutions so that ultimately when the customer buys that, they get a great user experience right out of the box. >> So, Mohan, I know that you and your team do a lot of performance validation testing as time goes by. I suspect that you had early releases of the 4th Gen EPYC processor technology. What have you been seeing so far? What can you tell us? >> AMD has definitely knocked it out of the park. Time and again, in the past four generations, in the past five years alone, we have done some database work where in five years, we have seen five exit performance. And across the board, AMD is the leader in benchmarks. We have done virtualization where we would consolidate from five into one system. We have world records in AI, we have world records in databases, we have world records in virtualization. The AMD EPYC solutions has been absolutely performant. I'll leave you with one number here. When we went from top of Stack Milan to top of Stack Genoa, we saw a performance bump of 120%. And that number just blew my mind. >> So that prompts a question for Greg. Often we, in industry insiders, think in terms of performance gains over the last generation or the current generation. A lot of customers in the real world, however, are N - 2. They're a ways back, so I guess two points on that. First of all, the kinds of increases the average person is going to see when they move to this architecture, correct me if I'm wrong, but it's even more significant than a lot of the headline numbers because they're moving two generations, number one. Correct me if I'm wrong on that, but then the other thing is the question to you, Greg. I like very long complicated questions, as you can tell. The question is, is it okay for people to skip generations or make the case for upgrades, I guess is the problem? >> Well, yeah, so a couple thoughts on that first too. Mohan talked about that five X over the generation improvements that we've seen. The other key point with that too is that we've made significant process improvements along the way moving to seven nanocomputer to now five nanocomputer and that's really reducing the total amount of power or the performance per watt the customers can realize as well. And when we look at why would a customer want to upgrade, right? And I want to rephrase that as to why aren't you? And there is a real cost of not upgrading. And so when you look at infrastructure, the average age of a server in the data center is over five years old. And if you look at the most popular processors that were sold in that timeframe, it's 8, 10, 12 cores. So now you've got a bunch of servers that you need in order to deliver the applications and meet your SLAs to your end users, and all those servers pull power. They require maintenance. They have the opportunity to go down, et cetera. You got to pay licensing and service and support costs and all those. And when you look at all the costs that roll up, even though the hardware is paid for just to keep the lights on, and not even talking about the soft costs of unplanned downtime, and, "I'm not meeting your SLAs," et cetera, it's very expensive to keep those servers running. Now, if you refresh, and now you have processors that have 32, 64, 96 cores, now you can consolidate that infrastructure and reduce your total power bill. You can reduce your CapEx, you reduce your ongoing OpEx, you improve your performance, and you improve your security profile. So it really is more cost effective to refresh than not to refresh. >> So, Mohan, what has your experience been double clicking on this topic of consolidation? I know that we're going to talk about virtualization in some of the results that you've seen. What have you seen in that regard? Does this favor better consolidation and virtualized environments? And are you both assuring us that the ROI and TCO pencil out on these new big, bad machines? >> Greg definitely hit the nail on the head, right? We are seeing tremendous savings really, if you're consolidating from two generations old. We went from, as I said, five is to one. You're going from five full servers, probably paid off down to one single server. That itself is, if you look at licensing costs, which again, with things like VMware does get pretty expensive. If you move to a single system, yes, we are at 32, 64, 96 cores, but if you compare to the licensing costs of 10 cores, two sockets, that's still pretty significant, right? That's one huge thing. Another thing which actually really drives the thing is we are looking at security, and in today's environment, security becomes a major driving factor for upgrades. Dell has its own setups, cyber-resilient architecture, as we call it, and that really is integrated from processor all the way up into the OS. And those are some of the features which customers really can take advantage of and help protect their ecosystems. >> So what kinds of virtualized environments did you test? >> We have done virtualization across primary codes with VMware, but the Azure Stack, we have looked at Nutanix. PowerFlex is another one within Dell. We have vSAN Ready Nodes. All of these, OpenShift, we have a broad variety of solutions from Dell and AMD really fits into almost every one of them very well. >> So where does hyper-converged infrastructure fit into this puzzle? We can think of a server as something that contains not only AMD's latest architecture but also latest PCIe bus technology and all of the faster memory, faster storage cards, faster nicks, all of that comes together. But how does that play out in Dell's hyper-converged infrastructure or HCI strategy? >> Dell is a leader in hyper-converged infrastructure. We have the very popular VxRail line, we have the PowerFlex, which is now going into the AWS ecosystem as well, Nutanix, and of course, Azure Stack. With all these, when you look at AMD, we have up to 96 cores coming in. We have PCIe Gen 5 which means you can now connect dual port, 100 and 200 gig nicks and get line rate on those so you can connect to your ecosystem. And I don't know if you've seen the news, 200, 400 gig routers and switchers are selling out. That's not slowing down. The network infrastructure is booming. If you want to look at the AI/ML side of things, the VDI side of things, accelerator cards are becoming more and more powerful, more and more popular. And of course they need that higher end data path that PCIe Gen 5 brings to the table. GDDR5 is another huge improvement in terms of performance and latencies. So when we take all this together, you talk about hyper-converged, all of them add into making sure that A, with hyper-converged, you get ease of management, but B, just 'cause you have ease of management doesn't mean you need to compromise on anything. And the AMD servers effectively are a no compromise offering that we at Dell are able to offer to our customers. >> So Greg, I've got a question a little bit from left field for you. We covered Supercompute Conference 2022. We were in Dallas a couple of weeks ago, and there was a lot of discussion of the current processor manufacturer battles, and a lot of buzz around 4th Gen EPYC being launched and what's coming over the next year. Do you have any thoughts on what this architecture can deliver for us in terms of things like AI? We talk about virtualization, but if you look out over the next year, do you see this kind of architecture driving significant change in the world? >> Yeah, yeah, yeah, yeah. It has the real potential to do that from just the building blocks. So we have our chiplet architecture we call it. So you have an IO die and then you have your core complexes that go around that. And we integrate it all with our infinity fabric. That architecture allows you, if we wanted to, replace some of those CCDs with specific accelerators. And so when we look two, three, four years down the road, that architecture and that capability already built into what we're delivering and can easily be moved in. We just need to make sure that when you look at doing that, that the power that's required to do that and the software, et cetera, and those accelerators actually deliver better performance as a dedicated engine versus just using standard CPUs. The other things that I would say too is if you look at emerging workloads. So data center modernization is one of the buzzwords in cloud native, right? And these container environments, well, AMD'S architecture really just screams support for those type of environments, right? Where when you get into these larger core accounts and the consolidation that Mohan talked about. Now when I'm in a container environment, that blast radius so a lot of customers have concerns around, "Hey, having a single point of failure and having more than X number of cores concerns me." If I'm in containers, that becomes less of a concern. And so when you look at cloud native, containerized applications, data center modernization, AMD's extremely well positioned to take advantage of those use cases as well. >> Yeah, Mohan, and when we talk about virtualization, I think sometimes we have to remind everyone that yeah, we're talking about not only virtualization that has a full-blown operating system in the bucket, but also virtualization where the containers have microservices and things like that. I think you had something to add, Mohan. >> I did, and I think going back to the accelerator side of business, right? When we are looking at the current technology and looking at accelerators, AMD has done a fantastic job of adding in features like AVX-512, we have the bfloat16 and eight features. And some of what these do is they're effectively built-in accelerators for certain workloads especially in the AI and media spaces. And in some of these use cases we look at, for example, are inference. Traditionally we have used external accelerator cards, but for some of the entry level and mid-level use cases, CPU is going to work just fine especially with the newer CPUs that we are seeing this fantastic performance from. The accelerators just help get us to the point where if I'm at the edge, if I'm in certain use cases, I don't need to have an accelerator in there. I can run most of my inference workloads right on the CPU. >> Yeah, yeah. You know the game. It's an endless chase to find the bottleneck. And once we've solved the puzzle, we've created a bottleneck somewhere else. Back to the supercompute conversations we had, specifically about some of the AMD EPYC processor technology and the way that Dell is packaging it up and leveraging things like connectivity. That was one of the things that was also highlighted. This idea that increasingly connectivity is critically important, not just for supercomputing, but for high-performance computing that's finding its way out of the realms of Los Alamos and down to the enterprise level. Gentlemen, any more thoughts about the partnership or maybe a hint at what's coming in the future? I know that the original AMD announcement was announcing and previewing some things that are rolling out over the next several months. So let me just toss it to Greg. What are we going to see in 2023 in terms of rollouts that you can share with us? >> That I can share with you? Yeah, so I think look forward to see more advancements in the technology at the core level. I think we've already announced our product code name Bergamo, where we'll have up to 128 cores per socket. And then as we look in, how do we continually address this demand for data, this demand for, I need actionable insights immediately, look for us to continue to drive performance leadership in our products that are coming out and address specific workloads and accelerators where appropriate and where we see a growing market. >> Mohan, final thoughts. >> On the Dell side, of course, we have four very rich and configurable options with AMD EPYC servers. But beyond that, you'll see a lot more solutions. Some of what Greg has been talking about around the next generation of processors or the next updated processors, you'll start seeing some of those. and you'll definitely see more use cases from us and how customers can implement them and take advantage of the features that. It's just exciting stuff. >> Exciting stuff indeed. Gentlemen, we have a great year ahead of us. As we approach possibly the holiday seasons, I wish both of you well. Thank you for joining us. From here in the Palo Alto studios, again, Dave Nicholson here. Stay tuned for our continuing coverage of AMD's 4th Generation EPYC launch. Thanks for joining us. (cheerful music)

>>Welcome to the Cube's Continuing coverage of AMD's fourth generation Epic launch. I'm Dave Nicholson and I'm joining you here in our Palo Alto Studios. We have two very interesting guests to dive into some of the announcements that have been made and maybe take a look at this from an AI and ML perspective. Our first guest is Milland Doley. He's a senior director for software and solutions at amd, and we're also joined by Shamus Jones, who's a director of server engineering at Dell Technologies. Welcome gentlemen. How are you? >>Very good, thank >>You. Welcome to the Cube. So let's start out really quickly, Shamus, what, give us a thumbnail sketch of what you do at Dell. >>Yeah, so I'm the director of technical marketing engineering here at Dell, and our team really takes a look at the technical server portfolio and solutions and ensures that we can look at, you know, the performance metrics, benchmarks, and performance characteristics, so that way we can give customers a good idea of what they can expect from the server portfolio when they're looking to buy Power Edge from Dell. >>Milland, how about you? What's, what's new at a M D? What do you do there? >>Great to be here. Thank you for having me at amd, I'm the senior director of performance engineering and ISV ecosystem enablement, which is a long winter way of saying we do a lot of benchmarks, improved performance and demonstrate with wonderful partners such as Shamus and Dell, the combined leverage that AMD four generation processes and Dell systems can bring to bear on a multitude of applications across the industry spectrum. >>Shamus, talk about that relationship a little bit more. The relationship between a M D and Dell. How far back does it go? What does it look like in practical terms? >>Absolutely. So, you know, ever since AM MD reentered the server space, we've had a very close relationship. You know, it's one of those things where we are offering solutions that are out there to our customers no matter what generation A portfolio, if they're, if they're demanding either from their competitor or a m d, we offer a portfolio solutions that are out there. What we're finding is that within their generational improvements, they're just getting better and better and better. Really exciting things happening from a m D at the moment, and we're seeing that as we engineer those CPU stacks into our, our server portfolio, you know, we're really seeing unprecedented performance across the board. So excited about the, the history, you know, my team and Lin's team work very closely together, so much so that we were communicating almost on a daily basis around portfolio platforms and updates around the, the, the benchmarks testing and, and validation efforts. >>So Melind, are you happy with these PowerEdge boxes that Seamus is building to, to house, to house your baby? >>We are delighted, you know, it's hard to find stronger partners than Shamus and Dell with AMD's, second generation epic service CPUs. We already had undisputable industry performance leadership, and then with the third and now the fourth generation CPUs, we've just increased our lead with competition. We've got so many outstanding features at the platform, at the CPU level, everybody focuses on the high core counts, but there's also the DDR five, the memory, the io, and the storage subsystem. So we believe we have a fantastic performance and performance per dollar performance per what edge over competition, and we look to partners such as Dell to help us showcase that leadership. >>Well. So Shay Yeah, through Yeah, go ahead >>Dave. What, what I'd add, Dave, is that through the, the partnership that we've had, you know, we've been able to develop subsystems and platform features that historically we couldn't have really things around thermals power efficiency and, and efficiency within the platform. That means that customers can get the most out of their compute infrastructure. >>So this is gonna be a big question moving forward as next generation platforms are rolled out, there's the potential for people to have sticker shock. You talk about something that has eight or 12 cores in a, in a physical enclosure versus 96 cores, and, and I guess the, the question is, do the ROI and TCO numbers look good for someone to make that upgrade? Shamus, you wanna, you wanna hit that first or you guys are integrated? >>Absolutely, yeah, sorry. Absolutely. So we, I'll tell you what, at the moment, customers really can't afford not to upgrade at the moment, right? We've taken a look at the cost basis of keeping older infrastructure in place, let's say five or seven year old infrastructure servers that are, that are drawing more power maybe are, are poorly utilized within the infrastructure and take more and more effort and time to manage, maintain and, and really keep in production. So as customers look to upgrade or refresh their platforms, what we're finding right is that they can take a dynamic consolidation sometimes 5, 7, 8 to one consolidation depending on which platform they have as a historical and which one they're looking to upgrade to. Within AI specifically and machine learning frameworks, we're seeing really unprecedented performance. Lin's team partnered with us to deliver multiple benchmarks for the launch, some of which we're still continuing to see the goodness from things like TP C X AI as a framework, and I'm talking about here specifically the CPU U based performance. >>Even though in a lot of those AI frameworks, you would also expect to have GPUs, which all of the four platforms that we're offering on the AM MD portfolio today offer multiple G P U offerings. So we're seeing a balance between a huge amount of C P U gain and performance, as well as more and more GPU offerings within the platform. That was real, that was a real challenge for us because of the thermal challenges. I mean, you think GPUs are going up 300, 400 watt, these CPUs at 96 core are, are quite demanding thermally, but what we're able to do is through some, some unique smart cooling engineering within the, the PowerEdge portfolio, we can take a look at those platforms and make the most efficient use case by having things like telemetry within the platform so that way we can dynamically change fan speeds to get customers the best performance without throttling based on their need. >>Melin the cube was at the Supercomputing conference in Dallas this year, supercomputing conference 2022, and a lot of the discussion was around not only advances in microprocessor technology, but also advances in interconnect technology. How do you manage that sort of research partnership with Dell when you aren't strictly just focusing on the piece that you are bringing to the party? It's kind of a potluck, you know, we, we, we, we mentioned P C I E Gen five or 5.0, whatever you want to call it, new DDR storage cards, Nicks, accelerators, all of those, all of those things. How do you keep that straight when those aren't things that you actually build? >>Well, excellent question, Dave. And you know, as we are developing the next platform, obviously the, the ongoing relationship is there with Dell, but we start way before launch, right? Sometimes it's multiple years before launch. So we are not just focusing on the super high core counts at the CPU level and the platform configurations, whether it's single socket or dual socket, we are looking at it from the memory subsystem from the IO subsystem, P c i lanes for storage is a big deal, for example, in this generation. So it's really a holistic approach. And look, core counts are, you know, more important at the higher end for some customers h HPC space, some of the AI applications. But on the lower end you have database applications or some other is s v applications that care a lot about those. So it's, I guess different things matter to different folks across verticals. >>So we partnered with Dell very early in the cycle, and it's really a joint co-engineering. Shamus talked about the focus on AI with TP C X xci, I, so we set five world records in that space just on that one benchmark with AD and Dell. So fantastic kick kick off to that across a multitude of scale factors. But PPP c Xci is not just the only thing we are focusing on. We are also collaborating with Dell and des e i on some of the transformer based natural language processing models that we worked on, for example. So it's not just a steep CPU story, it's CPU platform, es subsystem software and the whole thing delivering goodness across the board to solve end user problems in AI and and other verticals. >>Yeah, the two of you are at the tip of the spear from a performance perspective. So I know it's easy to get excited about world records and, and they're, they're fantastic. I know Shamus, you know, that, you know, end user customers might, might immediately have the reaction, well, I don't need a Ferrari in my data center, or, you know, what I need is to be able to do more with less. Well, aren't we delivering that also? And you know, you imagine you milland you mentioned natural, natural language processing. Shamus, are you thinking in 2023 that a lot more enterprises are gonna be able to afford to do things like that? I mean, what are you hearing from customers on this front? >>I mean, while the adoption of the top bin CPU stack is, is definitely the exception, not the rule today we are seeing marked performance, even when we look at the mid bin CPU offerings from from a m d, those are, you know, the most common sold SKUs. And when we look at customers implementations, really what we're seeing is the fact that they're trying to make the most, not just of dollar spend, but also the whole subsystem that Melin was talking about. You know, the fact that balanced memory configs can give you marked performance improvements, not just at the CPU level, but as actually all the way through to the, to the application performance. So it's, it's trying to find the correct balance between the application needs, your budget, power draw and infrastructure within the, the data center, right? Because not only could you, you could be purchasing and, and look to deploy the most powerful systems, but if you don't have an infrastructure that's, that's got the right power, right, that's a large challenge that's happening right now and the right cooling to deal with the thermal differences of the systems, might you wanna ensure that, that you can accommodate those for not just today but in the future, right? >>So it's, it's planning that balance. >>If I may just add onto that, right? So when we launched, not just the fourth generation, but any generation in the past, there's a natural tendency to zero in on the top bin and say, wow, we've got so many cores. But as Shamus correctly said, it's not just that one core count opn, it's, it's the whole stack. And we believe with our four gen CPU processor stack, we've simplified things so much. We don't have, you know, dozens and dozens of offerings. We have a fairly simple skew stack, but we also have a very efficient skew stack. So even, even though at the top end we've got 96 scores, the thermal budget that we require is fairly reasonable. And look, with all the energy crisis going around, especially in Europe, this is a big deal. Not only do customers want performance, but they're also super focused on performance per want. And so we believe with this generation, we really delivered not just on raw performance, but also on performance per dollar and performance per one. >>Yeah. And it's not just Europe, I'm, we're, we are here in Palo Alto right now, which is in California where we all know the cost of an individual kilowatt hour of electricity because it's quite, because it's quite high. So, so thermals, power cooling, all of that, all of that goes together and that, and that drives cost. So it's a question of how much can you get done per dollar shame as you made the point that you, you're not, you don't just have a one size fits all solution that it's, that it's fit for function. I, I'm, I'm curious to hear from you from the two of you what your thoughts are from a, from a general AI and ML perspective. We're starting to see right now, if you hang out on any kind of social media, the rise of these experimental AI programs that are being presented to the public, some will write stories for you based on prom, some will create images for you. One of the more popular ones will create sort of a, your superhero alter ego for, I, I can't wait to do it, I just got the app on my phone. So those are all fun and they're trivial, but they sort of get us used to this idea that, wow, these systems can do things. They can think on their own in a certain way. W what do, what do you see the future of that looking like over the next year in terms of enterprises, what they're going to do for it with it >>Melan? Yeah, I can go first. Yeah, yeah, yeah, yeah, >>Sure. Yeah. Good. >>So the couple of examples, Dave, that you mentioned are, I, I guess it's a blend of novelty and curiosity. You know, people using AI to write stories or poems or, you know, even carve out little jokes, check grammar and spelling very useful, but still, you know, kind of in the realm of novelty in the mainstream, in the enterprise. Look, in my opinion, AI is not just gonna be a vertical, it's gonna be a horizontal capability. We are seeing AI deployed across the board once the models have been suitably trained for disparate functions ranging from fraud detection or anomaly detection, both in the financial markets in manufacturing to things like image classification or object detection that you talked about in, in the sort of a core AI space itself, right? So we don't think of AI necessarily as a vertical, although we are showcasing it with a specific benchmark for launch, but we really look at AI emerging as a horizontal capability and frankly, companies that don't adopt AI on a massive scale run the risk of being left behind. >>Yeah, absolutely. There's an, an AI as an outcome is really something that companies, I, I think of it in the fact that they're adopting that and the frameworks that you're now seeing as the novelty pieces that Melin was talking about is, is really indicative of the under the covers activity that's been happening within infrastructures and within enterprises for the past, let's say 5, 6, 7 years, right? The fact that you have object detection within manufacturing to be able to, to be able to do defect detection within manufacturing lines. Now that can be done on edge platforms all the way at the device. So you're no longer only having to have things be done, you know, in the data center, you can bring it right out to the edge and have that high performance, you know, inferencing training models. Now, not necessarily training at the edge, but the inferencing models especially, so that way you can, you know, have more and, and better use cases for some of these, these instances things like, you know, smart cities with, with video detection. >>So that way they can see, especially during covid, we saw a lot of hospitals and a lot of customers that were using using image and, and spatial detection within their, their video feeds to be able to determine who and what employees were at risk during covid. So there's a lot of different use cases that have been coming around. I think the novelty aspect of it is really interesting and I, I know my kids, my daughters love that, that portion of it, but really what's been happening has been exciting for quite a, quite a period of time in the enterprise space. We're just now starting to actually see those come to light in more of a, a consumer relevant kind of use case. So the technology that's been developed in the data center around all of these different use cases is now starting to feed in because we do have more powerful compute at our fingertips. We do have the ability to talk more about the framework and infrastructure that's that's right out at the edge. You know, I know Dave in the past you've said things like the data center of, you know, 20 years ago is now in my hand as, as my cell phone. That's right. And, and that's, that's a fact and I'm, it's exciting to think where it's gonna be in the next 10 or 20 years. >>One terabyte baby. Yeah. One terabyte. Yeah. It's mind bo. Exactly. It's mind boggling. Yeah. And it makes me feel old. >>Yeah, >>Me too. And, and that and, and Shamus, that all sounded great. A all I want is a picture of me as a superhero though, so you guys are already way ahead of the curve, you know, with, with, with that on that note, Seamus wrap us up with, with a, with kind of a summary of the, the highlights of what we just went through in terms of the performance you're seeing out of this latest gen architecture from a md. >>Absolutely. So within the TPC xai frameworks that Melin and my team have worked together to do, you know, we're seeing unprecedented price performance. So the fact that you can get 220% uplift gen on gen for some of these benchmarks and, you know, you can have a five to one consolidation means that if you're looking to refresh platforms that are historically legacy, you can get a, a huge amount of benefit, both in reduction in the number of units that you need to deploy and the, the amount of performance that you can get per unit. You know, Melinda had mentioned earlier around CPU performance and performance per wat, specifically on the Tu socket two U platform using the fourth generation a m d Epic, you know, we're seeing a 55% higher C P U performance per wat that is that, you know, when for people who aren't necessarily looking at these statistics, every generation of servers, that that's, that is a huge jump leap forward. >>That combined with 121% higher spec scores, you know, as a benchmark, those are huge. Normally we see, let's say a 40 to 60% performance improvement on the spec benchmarks, we're seeing 121%. So while that's really impressive at the top bin, we're actually seeing, you know, large percentile improvements across the mid bins as well, you know, things in the range of like 70 to 90% performance improvements in those standard bins. So it, it's a, it's a huge performance improvement, a power efficiency, which means customers are able to save energy, space and time based on, on their deployment size. >>Thanks for that Shamus, sadly, gentlemen, our time has expired. With that, I want to thank both of you. It's a very interesting conversation. Thanks for, thanks for being with us, both of you. Thanks for joining us here on the Cube for our coverage of AMD's fourth generation Epic launch. Additional information, including white papers and benchmarks plus editorial coverage can be found on does hardware matter.com.

(bright upbeat music) >> Welcome to theCUBE's continuing coverage of AMD's fourth generation EPYC launch, along with the way that Dell has integrated this technology into its PowerEdge server lines. We're in for an interesting conversation today. Today, I'm joined by Dilip Ramachandran, Senior Director of Marketing at AMD, and Juergen Zimmermann. Juergen is Principal SAP Solutions Performance Benchmarking Engineer at Dell. Welcome, gentlemen. >> Welcome. >> Thank you David, nice to be here. >> Nice to meet you too, welcome to theCUBE. You will officially be CUBE alumni after this. Dilip, let's start with you. What's this all about? Tell us about AMD's recent launch and the importance of it. >> Thanks, David. I'm excited to actually talk to you today, AMD, at our fourth generation EPYC launch last month in November. And as part of that fourth generation EPYC launch, we announced industry-leading performance based on 96 cores, based on Zen 4 architecture. And new interfaces, PCIe Gen 5, as well as DDR5. Incredible amount of memory bandwidth, memory capacity supported, and a whole lot of other features as well. So we announced this product, we launched it in November last month. And we've been closely working with Dell on a number of benchmarks that we'd love to talk to you more about today. >> So just for some context, when was the last release of this scale? So when was the third generation released? How long ago? >> The third generation EPYC was launched in Q1 of 2021. So it was almost 18 to 24 months ago. And since then we've made a tremendous jump, the fourth generation EPYC, in terms of number of cores. So third generation EPYC supported 64 cores, fourth generation EPYC supports 96 cores. And these are new cores, the Zen 4 cores, the fourth generation of Zen cores. So very high performance, new interfaces, and really world-class performance. >> Excellent. Well, we'll go into greater detail in a moment, but let's go to Juergen. Tell us about the testing that you've been involved with to kind of prove out the benefits of this new AMD architecture. >> Yeah, well, the testing is SAP Standard Performance benchmark, the SAP SD two tier. And this is more or less a industry standard benchmark that is used to size your service for the needs of SAP. Actually, SAP customers always ask the vendors about the SAP benchmark and the SAPS values of their service. >> And I should have asked you before, but give us a little bit of your background working with SAP. Have you been doing this for longer than a week? >> Yeah, yeah, definitely, I do this for about 20 years now. Started with Sun Microsystems, and interestingly in the year 2003, 2004, I started working with AMD service on SAP with Linux, and afterwards parted the SAP application to Solaris AMD, also with AMD. So I have a lot of tradition with SAP and AMD benchmarks, and doing this ever since then. >> So give us some more detail on the results of the recent testing, and if you can, tell us why we should care? >> (laughs) Okay, the recent results actually also surprised myself, they were so good. So I initially installed the benchmark kit, and couldn't believe that the server is just getting, or hitting idle by the numbers I saw. So I cranked up the numbers and reached results that are most likely double the last generation, so Zen 3 generation, and that even passed almost all 8-socket systems out there. So if you want to have the same SAP performance, you can just use 2-socket AMD server instead of any four or 8-socket servers out there. And this is a tremendous saving in energy. >> So you just mentioned savings in terms of power consumption, which is a huge consideration. What are the sort of end user results that this delivers in terms of real world performance? How is a human being at the end of a computer going to notice something like this? >> So actually the results are like that you get almost 150,000 users concurrently accessing the system, and get their results back from SAP within one second response time. >> 150,000 users, you said? >> 150,000 users in parallel. >> (laughs) Okay, that's amazing. And I think it's interesting to note that, and I'll probably say this a a couple of times. You just referenced third generation EPYC architecture, and there are a lot of folks out there who are two generations back. Not everyone is religiously updating every 18 months, and so for a fair number of SAP environments, this is an even more dramatic increase. Is that a fair thing to say? >> Yeah, I just looked up yesterday the numbers from generation one of EPYC, and this was at about 28,000 users. So we are five times the performance now, within four years. Yeah, great. >> So Dilip, let's dig a little more into the EPYC architecture, and I'm specifically also curious about... You mentioned PCIe Gen five, or 5.0 and all of the components that plug into that. You mentioned I think faster DDR. Talk about that. Talk about how all of the components work together to make when Dell comes out with a PowerEdge server, to make it so much more powerful. >> Absolutely. So just to spend a little bit more time on this particular benchmark, the SAP Sales and Distribution benchmark. It's a widely used benchmark in the industry to basically look at how do I get the most performance out of my system for a variety of SAP business suite applications. And we touched upon it earlier, right, we are able to beat a performance of 4-socket and 8-socket servers out there. And you know, it saves energy, it saves cost, better TCO for the data center. So we're really excited to be able to support more users in a single server and meeting all the other dual socket and 4-socket combinations out there. Now, how did we get there, right, is more the important question. So as part of our fourth generation EPYC, we obviously upgraded our CPU core to provide much better single third performance per core. And at the socket level, you know, when you're packing 96 cores, you need to be able to feed these cores, you know, from a memory standpoint. So what we did was we went to 12 channels of memory, and these are DDR5 memory channels. So obviously you get much better bandwidth, higher speed of the memory with DDR5, you know, starting at 4,800 megahertz. And you're also now able to have more channels to be able to send the data from the memory into the CPU subsystem, which is very critical to keep the CPUs busy and active, and get the performance out. So that's on the memory side. On the data side, you know, we do have PCIe Gen five, and any data oriented applications that take data either from the PCIe drives or the network cards that utilize Gen five that are available in the industry today, you can actually really get data into the system through the PCIe I/O, either again, through the disk, or through the net card as well. So those are other ways to actually also feed the CPU subsystem with data to be processed by the CPU complex. So we are, again, very excited to see all of this coming together, and as they say, proof's in the pudding. You know, Juergen talked about it. How over generation after generation we've increased the performance, and now with our fourth generation EPYC, we are absolutely leading world-class performance on the SAP Sales and Distribution benchmark. >> Dilip, I have another question for you, and this may be, it may be a bit of a PowerEdge and beyond question. What are you seeing, or what are you anticipating in terms of end user perception when they go to buy a new server? Obviously server is a very loose term, and they can be configured in a bunch of different ways. But is there a discussion about ROI and TCO that's particularly critical? Because people are going to ask, "Well, wait a minute. If it's more expensive than the last one that I bought, am I getting enough bang for my buck?" Is that going to be part of the conversation, especially around power and cooling and things like that? >> Yeah, absolutely. You know, every data center decision maker has to ask the question, "Why should I upgrade? Should I stay with legacy hardware, or should I go into the latest and greatest that AMD offers?" And the advantages that the new generation products bring is much better performance at much better energy consumption levels, as well as much better performance per dollar levels. So when you do the upgrade, you are actually getting, you know, savings in terms of performance per dollar, as well as saving in space because you can consolidate your work into fewer servers 'cause you have more cores. As we talked about, you have eight, you know. Typically you might do it on a four or 8-socket server which is really expensive. You can consolidate down to a 2-socket server which is much cheaper. As also for maintenance costs, it's much lower maintenance costs as well. All of this, performance, power, maintenance costs, all of that translate into better TCO, right. So lower all of these, high performance, lower power, and then lower maintenance costs, translate to much better TCO for the end user. And that's an important equation that all customers pay attention to. and you know, we love to work with them and demonstrate those TCO benefits to them. >> Juergen, talk to us more in general about what Dell does from a PowerEdge perspective to make sure that Dell is delivering the best infrastructure possible for SAP. In general, I mean, I assume that this is a big responsibility of yours, is making sure that the stuff runs properly and if not, fixing it. So tell us about that relationship between Dell and a SAP. >> Yeah, for Dell and SAP actually, we're more or less partners with SAP. We have people sitting in SAP's Linux lab, and working in cooperative with SAP, also with Linux partners like SUSE and Red Hat. And we are in constant exchange about what's new in Linux, what's new on our side. And we're all a big family here. >> So when the new architecture comes out and they send it to Juergen, the boys back at the plant as they say, or the factory to use Formula One terms, are are waiting with baited breath to hear what Juergen says about the results. So just kind of kind of recap again, you know, the specific benchmarks that you were running. Tell us about that again. >> Yeah, the specific benchmark is the SAP Sales and Distribution benchmark. And for SAP, this is the benchmark that needs to be tested, and it shows the performance of the whole system. So in contrast to benchmarks that only check if the CPU is running, very good, this test the whole system up from the network stack, from the storage stack, the memory, subsystem, and the OS running on the CPUs. >> Okay, which makes perfect sense, since Dell is delivering an integrated system and not just CPU technology. You know, on that subject, Dilip, do you have any insights into performance numbers that you're hearing about with Gen four EPYC for other database environments? >> Yeah, we have actually worked together with Dell on a variety of benchmarks, both on the latest fourth generation EPYC processors as well as the preceding one, the third generation EPYC processors. And published a bunch of world records on database, particularly I would say TPC-H, TPCx-V, as well as TPCx-HS and TPCx-IoT. So a number of TPC related benchmarks that really showcase performance for database and related applications. And we've collaborated very closely with Dell on these benchmarks and published a number of them already, and you know, a number of them are world records as well. So again, we're very excited to collaborate with Dell on the SAP Sales and Distribution benchmark, as well as other benchmarks that are related to database. >> Well, speaking of other benchmarks, here at theCUBE we're going to be talking to actually quite a few people, looking at this fourth generation EPYC launch from a whole bunch of different angles. You two gentlemen have shed light on some really good pieces of that puzzle. I want to thank you for being on theCUBE today. With that, I'd like to thank all of you for joining us here on theCUBE. Stay tuned for continuing CUBE coverage of AMD's fourth generation EPYC launch, and Dell PowerEdge strategy to leverage it.

(Intro music) >> Welcome back. We're LIVE here from SuperComputing 22 in Dallas Paul Gillin, for Silicon Angle in theCUBE with my guest host Dave... excuse me. And our, our guest today, this segment is Kim Leyenaar who is a storage performance architect at Broadcom. And the topic of this conversation is, is is networking, it's connectivity. I guess, how does that relate to the work of a storage performance architect? >> Well, that's a really good question. So yeah, I have been focused on storage performance for about 22 years. But even, even if we're talking about just storage the entire, all the components have a really big impact on ultimately how quickly you can access your data. So, you know, the, the switches the memory bandwidth, the, the expanders the just the different protocols that you're using. And so, and the big part of is actually ethernet because as you know, data's not siloed anymore. You have to be able to access it from anywhere in the world. >> Dave: So wait, so you're telling me that we're just not living in a CPU centric world now? >> Ha ha ha >> Because it is it is sort of interesting. When we talk about supercomputing and high performance computing we're always talking about clustering systems. So how do you connect those systems? Isn't that, isn't that kind of your, your wheelhouse? >> Kim: It really is. >> Dave: At Broadcom. >> It's, it is, it is Broadcom's wheelhouse. We are all about interconnectivity and we own the interconnectivity. You know, you know, years ago it was, 'Hey, you know buy this new server because, you know, we we've added more cores or we've got better memory.' But now you've got all this siloed data and we've got you know, we've got this, this stuff or defined kind of environment now this composable environments where, hey if you need more networking, just plug this in or just go here and just allocate yourself more. So what we're seeing is these silos really of, 'hey here's our compute, here's your networking, here's your storage.' And so, how do you put those all together? The thing is interconnectivity. So, that's really what we specialize in. I'm really, you know, I'm really happy to be here to talk about some of the things that that we do to enable high performance computing. >> Paul: Now we're seeing, you know, new breed of AI computers being built with multiple GPUs very large amounts of data being transferred between them. And the internet really has become a, a bottleneck. The interconnect has become a bottle, a bottleneck. Is that something that Broadcom is working on alleviating? >> Kim: Absolutely. So we work with a lot of different, there's there's a lot of different standards that we work with to define so that we can make sure that we work everywhere. So even if you're just a dentist's office that's deploying one server, or we're talking about these hyperscalers that are, you know that have thousands or, you know tens of thousands of servers, you know, we're working on making sure that the next generation is able to outperform the previous generation. Not only that, but we found that, you know with these siloed things, if, if you add more storage but that means we're going to eat up six cores using that it's not really as useful. So Broadcom's really been focused on trying to offload the CPU. So we're offloading it from, you know data security, data protection, you know, we're we do packet sniffing ourselves and things like that. So no longer do we rely on the CPU to do that kind of processing for us but we become very smart devices all on our own so that they work very well in these kind of environments. >> Dave: So how about, give, give us an example. I know a lot of the discussion here has been around using ethernet as the connectivity layer. >> Yes. >> You know, in in, in the past, people would think about supercomputing as exclusively being InfiniBand based. >> Ha ha ha. >> But give, give us an idea of what Broadcom is doing in the ethernet space. What, you know, what's what are the advantages of using ethernet? >> Kim: So we've made two really big announcements. The first one is our Tomahawk five ethernet switch. So it's a 400 gigi ethernet switch. And the other thing we announced too was our Thor. So we have, these are our network controllers that also support up to 400 gigi each as well. So, those two alone, it just, it's amazing to me how much data we're able to transfer with those. But not only that, but they're super super intelligent controllers too. And then we realized, you know, hey, we're we're managing all this data, let's go ahead and offload the CPU. So we actually adopted the Rocky Standards. So that's one of the things that puts us above InfiniBand is that ethernet is ubiquitous, it's everywhere. And InfiniBand is primarily just owned by one or two companies. And, and so, and it's also a lot more expensive. So ethernet is just, it's everywhere. And now with the, with the Rocky standards, we're working along with, it's, it's, it does what you're talking about much better than, you know predecessors. >> Tell us about the Rocky Standards. I'm not familiar with it. I'm sure some of our listeners are not. What is the Rocky standard? >> Kim: Ha ha ha. So it's our DNA over converged to ethernet. I'm not a Rocky expert myself but I am an expert on how to offload the CPU. And so one of the things it does is instead of using the CPU to transfer the data from, you know the user space over to the next, you know server when you're transferring it we actually will do it ourselves. So we'll handle it ourselves. We will take it, we will move it across the wire and we will put it in that remote computer. And we don't have to ask the CPU to do anything to get involved in that. So big, you know, it's a big savings. >> Yeah, I mean in, in a nutshell, because there are parts of the InfiniBand protocol that are essentially embedded in RDMA over converged ethernet. So... >> Right. >> So if you can, if you can leverage kind of the best of both worlds, but have it in an ethernet environment which is already ubiquitous, it seems like it's, kind of democratizing supercomputing and, and HPC and I know you guys are big partners with Dell as an example, you guys work with all sorts of other people. >> Kim: Yeah. >> But let's say, let's say somebody is going to be doing ethernet for connectivity, you also offer switches? >> Kim: We do, actually. >> So is that, I mean that's another piece of the puzzle. >> That's a big piece of the puzzle. So we just released our, our Atlas 2 switch. It is a PCIE Gen Five switch. And... >> Dave: What does that mean? What does Gen five, what does that mean? >> Oh, Gen Five PCIE, it's it's a magic connectivity right now. So, you know, we talk about the Sapphire Rapids release as well as the GENUWA release. I know that those, you know those have been talked about a lot here. I've been walking around and everybody's talking about it. Well, those enable the Gen Five PCIE interfaces. So we've been able to double the bandwidth from the Gen Four up to the Gen Five. So, in order to, to support that we do now have our Atlas two PCIE Gen Five switch. And it allows you to connect especially around here we're talking about, you know artificial intelligence and machine learning. A lot of these are relying on the GPU and the DPU that you see, you know a lot of people talking about enabling. So by in, you know, putting these switches in the servers you can connect multitudes of not only NVME devices but also these GPUs and these, these CPUs. So besides that we also have the storage component of it too. So to support that, we we just recently have released our 9,500 series HBAs which support 24 gig SAS. And you know, this is kind of a, this is kind of a big deal for some of our hyperscalers that say, Hey, look our next generation, we're putting a hundred hard drives in. So we're like, you know, so a lot of it is maybe for cold storage, but by giving them that 24 gig bandwidth and by having these mass 24 gig SAS expanders that allows these hyperscalers to build up their systems. >> Paul: And how are you supporting the HPC community at large? And what are you doing that's exclusively for supercomputing? >> Kim: Exclusively for? So we're doing the interconnectivity really for them. You know, you can have as, as much compute power as you want, but these are very data hungry applications and a lot of that data is not sitting right in the box. A lot of that data is sitting in some other country or in some other city, or just the box next door. So to be able to move that data around, you know there's a new concept where they say, you know do the compute where the data is and then there's another kind of, you know the other way is move the data around which is a lot easier kind of sometimes, but so we're allowing us to move that data around. So for that, you know, we do have our our tomahawk switches, we've got our Thor NICS and of course we got, you know, the really wide pipe. So our, our new 9,500 series HBA and RAID controllers not only allow us to do, so we're doing 28 gigabytes a second that we can trans through the one controller, and that's on protected data. So we can actually have the high availability protected data of RAID 5 or RAID 6, or RAID 10 in the box giving in 27 gigabytes a second. So it's, it's unheard of the latency that we're seeing even off of this too, we have a right cash latency that is sub 8 microseconds that is lower than most of the NVME drives that you see, you know that are available today. So, so you know we're able to support these applications that require really low latency as well as data protection. >> Dave: So, so often when we talk about the underlying hardware, it's a it's a game of, you know, whack-a-mole chase the bottleneck. And so you've mentioned PCIE five, a lot of folks who will be implementing five, gen five PCIE five are coming off of three, not even four. >> Kim: I know. >> So make, so, so they're not just getting a last generation to this generation bump but they're getting a two generations, bump. >> Kim: They are. >> How does that, is it the case that it would never make sense to use a next gen or a current gen card in an older generation bus because of the mismatch and performance? Are these things all designed to work together? >> Uh... That's a really tough question. I want to say, no, it doesn't make sense. It, it really makes sense just to kind of move things forward and buy a card that's made for the bus it's in. However, that's not always the case. So for instance, our 9,500 controller is a Gen four PCIE but what we did, we doubled the PCIE so it's a by 16, even though it's a gen four, it's a by 16. So we're getting really, really good bandwidth out of it. As I said before, you know, we're getting 28, 27.8 or almost 28 gigabytes a second bandwidth out of that by doubling the PCIE bus. >> Dave: But they worked together, it all works together? >> All works together. You can put, you can put our Gen four and a Gen five all day long and they work beautifully. Yeah. We, we do work to validate that. >> We're almost out our time. But I, I want to ask you a more, nuts and bolts question, about storage. And we've heard for, you know, for years of the aerial density of hard disk has been reached and there's really no, no way to excel. There's no way to make the, the dish any denser. What is the future of the hard disk look like as a storage medium? >> Kim: Multi actuator actually, we're seeing a lot of multi-actuator. I was surprised to see it come across my desk, you know because our 9,500 actually does support multi-actuator. And, and, and so it was really neat after I've been working with hard drives for 22 years and I remember when they could do 30 megabytes a second, and that was amazing. That was like, wow, 30 megabytes a second. And then, about 15 years ago, they hit around 200 to 250 megabytes a second, and they stayed there. They haven't gone anywhere. What they have done is they've increased the density so that you can have more storage. So you can easily go out and buy 15 to 30 terabyte drive, but you're not going to get any more performance. So what they've done is they've added multiple actuators. So each one of these can do its own streaming and each one of these can actually do their own seeking. So you can get two and four. And I've even seen a talk about, you know eight actuator per disc. I, I don't think that, I think that's still theory, but but they could implement those. So that's one of the things that we're seeing. >> Paul: Old technology somehow finds a way to, to remain current. >> It does. >> Even it does even in the face of new alternatives. Kim Leyenaar, Storage Architect, Storage Performance Architect at Broadcom Thanks so much for being here with us today. Thank you so much for having me. >> This is Paul Gillin with Dave Nicholson here at SuperComputing 22. We'll be right back. (Outro music)

(upbeat music) >> We're back at SC22 SuperComputing Conference in Dallas. My name's Paul Gillan, my co-host, John Furrier, SiliconANGLE founder. And huge exhibit floor here. So much activity, so much going on in HPC, and much of it around the chips from AMD, which has been on a roll lately. And in partnership with Dell, our guests are Brian Payne, Dell Technologies, VP of Product Management for ISG mid-range technical solutions, and Raghu Nambiar, corporate vice president of data system, data center ecosystem, and application engineering, that's quite a mouthful, at AMD, And gentlemen, welcome. Thank you. >> Thanks for having us. >> This has been an evolving relationship between you two companies, obviously a growing one, and something Dell was part of the big general rollout, AMD's new chip set last week. Talk about how that relationship has evolved over the last five years. >> Yeah, sure. Well, so it goes back to the advent of the EPIC architecture. So we were there from the beginning, partnering well before the launch five years ago, thinking about, "Hey how can we come up with a way to solve customer problems? address workloads in unique ways?" And that was kind of the origin of the relationship. We came out with some really disruptive and capable platforms. And then it continues, it's continued till then, all the way to the launch of last week, where we've introduced four of the most capable platforms we've ever had in the PowerEdge portfolio. >> Yeah, I'm really excited about the partnership with the Dell. As Brian said, we have been partnering very closely for last five years since we introduced the first generation of EPIC. So we collaborate on, you know, system design, validation, performance benchmarks, and more importantly on software optimizations and solutions to offer out of the box experience to our customers. Whether it is HPC or databases, big data analytics or AI. >> You know, you guys have been on theCUBE, you guys are veterans 2012, 2014 back in the day. So much has changed over the years. Raghu, you were on the founding chair of the TPC for AI. We've talked about the different iterations of power service. So much has changed. Why the focus on these workloads now? What's the inflection point that we're seeing here at SuperComputing? It feels like we've been in this, you know run the ball, get, gain a yard, move the chains, you know, but we feel, I feel like there's a moment where the there's going to be an unleashing of innovation around new use cases. Where's the workloads? Why the performance? What are some of those use cases right now that are front and center? >> Yeah, I mean if you look at today, the enterprise ecosystem has become extremely complex, okay? People are running traditional workloads like Relational Database Management Systems, also new generation of workloads with the AI and HPC and actually like AI actually HPC augmented with some of the AI technologies. So what customers are looking for is, as I said, out of the box experience, or time to value is extremely critical. Unlike in the past, you know, people, the customers don't have the time and resources to run months long of POCs, okay? So that's one idea that we are focusing, you know, working closely with Dell to give out of the box experience. Again, you know, the enterprise applicate ecosystem is, you know, really becoming complex and the, you know, as you mentioned, some of the industry standard benchmark is designed to give the fair comparison of performance, and price performance for the, our end customers. And you know, Brian and my team has been working closely to demonstrate our joint capabilities in the AI space with, in a set of TPCx-AI benchmark cards last week it was the major highlight of our launch last week. >> Brian, you got showing the demo in the booth at Dell here. Not demo, the product, it's available. What are you seeing for your use cases that customers are kind of rallying around now, and what are they doubling down on. >> Yeah, you know, I, so Raghu I think teed it up well. The really data is the currency of business and all organizations today. And that's what's pushing people to figure out, hey, both traditional workloads as well as new workloads. So we've got in the traditional workload space, you still have ERP systems like SAP, et cetera, and we've announced world records there, a hundred plus percent improvements in our single socket system, 70% and dual. We actually posted a 40% advantage over the best Genoa result just this week. So, I mean, we're excited about that in the traditional space. But what's exciting, like why are we here? Why, why are people thinking about HPC and AI? It's about how do we make use of that data, that data being the currency and how do we push in that space? So Raghu mentioned the TPC AI benchmark. We launched, or we announced in collaboration you talk about how do we work together, nine world records in that space. In one case it's a 3x improvement over prior generations. So the workloads that people care about is like how can I process this data more effectively? How can I store it and secure it more effectively? And ultimately, how do I make decisions about where we're going, whether it's a scientific breakthrough, or a commercial application. That's what's really driving the use cases and the demand from our customers today. >> I think one of the interesting trends we've seen over the last couple of years is a resurgence in interest in task specific hardware around AI. In fact venture capital companies invested a $1.8 billion last year in AI hardware startups. I wonder, and these companies are not doing CPUs necessarily, or GPUs, they're doing accelerators, FPGAs, ASICs. But you have to be looking at that activity and what these companies are doing. What are you taking away from that? How does that affect your own product development plans? Both on the chip side and on the system side? >> I think the future of computing is going to be heterogeneous. Okay. I mean a CPU solving certain type of problems like general purpose computing databases big data analytics, GPU solving, you know, problems in AI and visualization and DPUs and FPGA's accelerators solving you know, offloading, you know, some of the tasks from the CPU and providing realtime performance. And of course, you know, the, the software optimizes are going to be critical to stitch everything together, whether it is HPC or AI or other workloads. You know, again, as I said, heterogeneous computing is going to be the future. >> And, and for us as a platform provider, the heterogeneous, you know, solutions mean we have to design systems that are capable of supporting that. So if as you think about the compute power whether it's a GPU or a CPU, continuing to push the envelope in terms of, you know, to do the computations, power consumption, things like that. How do we design a system that can be, you know, incredibly efficient, and also be able to support the scaling, you know, to solve those complex problems. So that gets into challenges around, you know, both liquid cooling, but also making the most out of air cooling. And so we're seeing not only are we we driving up you know, the capability of these systems, we're actually improving the energy efficiency. And those, the most recent systems that we launched around the CPU, which is still kind of at the heart of everything today, you know, are seeing 50% improvement, you know, gen to gen in terms of performance per watt capabilities. So it's, it's about like how do we package these systems in effective ways and make sure that our customers can get, you know, the advertised benefits, so to speak, of the new chip technologies. >> Yeah. To add to that, you know, performance, scalability total cost of ownership, these are the key considerations, but now energy efficiency has become more important than ever, you know, our commitment to sustainability. This is one of the thing that we have demonstrated last week was with our new generation of EPIC Genoa based systems, we can do a one five to one consolidation, significantly reducing the energy requirement. >> Power's huge costs are going up. It's a global issue. >> Raghu: Yeah, it is. >> How do you squeeze more performance too out of it at the same time, I mean, smaller, faster, cheaper. Paul, you wrote a story about, you know, this weekend about hardware and AI making hardware so much more important. You got more power requirements, you got the sustainability, but you need more horsepower, more compute. What's different in the architecture if you guys could share like today versus years ago, what's different in as these generations step function value increases? >> So one of the major drivers from the processor perspective is if you look at the latest generation of processors, the five nanometer technology, bringing efficiency and density. So we are able to pack 96 processor cores, you know, in a two socket system, we are talking about 196 processor cores. And of course, you know, other enhancements like IPC uplift, bringing DDR5 to the market PC (indistinct) for the market, offering overall, you know, performance uplift of more than 2.5x for certain workloads. And of course, you know, significantly reducing the power footprint. >> Also, I was just going to cut, I mean, architecturally speaking, you know, then how do we take the 96 cores and surround it, deliver a balanced ecosystem to make sure that we can get the, the IO out of the system, and make sure we've got the right data storage. So I mean, you'll see 60% improvements and total storage in the system. I think in 2012 we're talking about 10 gig ethernet. Well, you know, now we're on to 100 and 400 on the forefront. So it's like how do we keep up with this increased power, by having, or computing capabilities both offload and core computing and make sure we've got a system that can deliver the desired (indistinct). >> So the little things like the bus, the PCI cards, the NICs, the connectors have to be rethought through. Is that what you're getting at? >> Yeah, absolutely. >> Paul: And the GPUs, which are huge power consumers. >> Yeah, absolutely. So I mean, cooling, we introduce, and we call it smart cooling is a part of our latest generation of servers. I mean, the thermal design inside of a server is a is a complex, you know, complex system, right? And doing that efficiently because of course fans consume power. So I mean, yeah, those are the kind of considerations that we have to put through to make sure that you're not either throttling performance because you don't have you know, keeping the chips at the right temperature. And, and you know, ultimately when you do that, you're hurting the productivity of the investment. So I mean, it's, it's our responsibility to put our thoughts and deliver those systems that are (indistinct) >> You mention data too, if you bring in the data, one of the big discussions going into the big Amazon show coming up, re:Invent is egress costs. Right, So now you've got compute and how you design data latency you know, processing. It's not just contained in a machine. You got to think about outside that machine talking to other machines. Is there an intelligent (chuckles) network developing? I mean, what's the future look like? >> Well, I mean, this is a, is an area that, that's, you know, it's fun and, you know, Dell's in a unique position to work on this problem, right? We have 70% of the mission housed, 70% of the mission critical data that exists in the world. How do we bring that closer to compute? How do we deliver system level solutions? So server compute, so recently we announced innovations around NVMe over Fabrics. So now you've got the NVMe technology and the SAN. How do we connect that more efficiently across the servers? Those are the kinds, and then guide our customers to make use of that. Those are the kinds of challenges that we're trying to unlock the value of the data by making sure we're (indistinct). >> There are a lot of lessons learned from, you know, classic HPC and some of the, you know big data analytics. Like, you know, Hadoops of the world, you know, you know distributor processing for crunching a large amount of amount of data. >> With the growth of the cloud, you see, you know, some pundits saying that data centers will become obsolete in five years, and everything's going to move to the cloud. Obviously data center market that's still growing, and is projected to continue to grow. But what's the argument for captive hardware, for owning a data center these days when the cloud offers such convenience and allegedly cost benefit? >> I would say the reality is that we're, and I think the industry at large has acknowledged this, that we're living in a multicloud world and multicloud methods are going to be necessary to you know, to solve problems and compete. And so, I mean, you know, in some cases, whether it's security or latency, you know, there's a push to have things in your own data center. And then of course growth at the edge, right? I mean, that's, that's really turning, you know, things on their head, if you will, getting data closer to where it's being generated. And so I would say we're going to live in this edge cloud, you know, and core data center environment with multi, you know, different cloud providers providing solutions and services where it makes sense, and it's incumbent on us to figure out how do we stitch together that data platform, that data layer, and help customers, you know, synthesize this data to, to generate, you know, the results they need. >> You know, one of the things I want to get into on the cloud you mentioned that Paul, is that we see the rise of graph databases. And so is that on the radar for the AI? Because a lot of more graph data is being brought in, the database market's incredibly robust. It's one of the key areas that people want performance out of. And as cloud native becomes the modern application development, a lot more infrastructure as code's happening, which means that the internet and the networks and the process should be programmable. So graph database has been one of those things. Have you guys done any work there? What's some data there you can share on that? >> Yeah, actually, you know, we have worked closely with a company called TigerGraph, there in the graph database space. And we have done a couple of case studies, one on the healthcare side, and the other one on the financial side for fraud detection. Yeah, I think they have a, this is an emerging area, and we are able to demonstrate industry leading performance for graph databases. Very excited about it. >> Yeah, it's interesting. It brings up the vertical versus horizontal applications. Where is the AI HPC kind of shining? Is it like horizontal and vertical solutions or what's, what's your vision there. >> Yeah, well, I mean, so this is a case where I'm also a user. So I own our analytics platform internally. We actually, we have a chat box for our product development organization to figure out, hey, what trends are going on with the systems that we sell, whether it's how they're being consumed or what we've sold. And we actually use graph database technology in order to power that chat box. So I'm actually in a position where I'm like, I want to get these new systems into our environment so we can deliver. >> Paul: Graphs under underlie most machine learning models. >> Yeah, Yeah. >> So we could talk about, so much to talk about in this space, so little time. And unfortunately we're out of that. So fascinating discussion. Brian Payne, Dell Technologies, Raghu Nambiar, AMD. Congratulations on the successful launch of your new chip set and the growth of, in your relationship over these past years. Thanks so much for being with us here on theCUBE. >> Super. >> Thank you much. >> It's great to be back. >> We'll be right back from SuperComputing 22 in Dallas. (upbeat music)

(upbeat music) (logo swooshing) >> Good morning and welcome back to Dallas, ladies and gentlemen, we are here with theCUBE Live from Supercomputing 2022. David, my cohost, how are you doing? Exciting, day two, feeling good? >> Very exciting. Ready to start off the day. >> Very excited. We have two fascinating guests joining us to kick us off. Please welcome Pete and Armando. Gentlemen, thank you for being here with us. >> Thank you for having us. >> Thank you for having us. >> I'm excited that you're starting off the day because we've been hearing a lot of rumors about Ethernet as the fabric for HPC, but we really haven't done a deep dive yet during the show. You all seem all in on Ethernet. Tell us about that. Armando, why don't you start? >> Yeah, I mean, when you look at Ethernet, customers are asking for flexibility and choice. So when you look at HPC, InfiniBand's always been around, right? But when you look at where Ethernet's coming in, it's really our commercial in their enterprise customers. And not everybody wants to be in the top 500, what they want to do is improve their job time and improve their latency over the network. And when you look at Ethernet, you kind of look at the sweet spot between 8, 12, 16, 32 nodes, that's a perfect fit for Ethernet in that space and those types of jobs. >> I love that. Pete, you want to elaborate? >> Yeah, sure. I mean, I think one of the biggest things you find with Ethernet for HPC is that, if you look at where the different technologies have gone over time, you've had old technologies like, ATM, Sonic, Fifty, and pretty much everything is now kind of converged toward Ethernet. I mean, there's still some technologies such as InfiniBand, Omni-Path, that are out there. But basically, they're single source at this point. So what you see is that there is a huge ecosystem behind Ethernet. And you see that also the fact that Ethernet is used in the rest of the enterprise, is used in the cloud data centers, that is very easy to integrate HPC based systems into those systems. So as you move HPC out of academia into enterprise, into cloud service providers, it's much easier to integrate it with the same technology you're already using in those data centers, in those networks. >> So what's the state of the art for Ethernet right now? What's the leading edge? what's shipping now and what's in the near future? You're with Broadcom, you guys designed this stuff. >> Pete: Yeah. >> Savannah: Right. >> Yeah, so leading edge right now, got a couple things-- >> Savannah: We love good stage prop here on the theCUBE. >> Yeah, so this is Tomahawk 4. So this is what is in production, it's shipping in large data centers worldwide. We started sampling this in 2019, started going into data centers in 2020. And this is 25.6 terabytes per second. >> David: Okay. >> Which matches any other technology out there. Like if you look at say, InfinBand, highest they have right now that's just starting to get into production is 25.6 T. So state of the art right now is what we introduced, We announced this in August, This is Tomahawk 5, so this is 51.2 terabytes per second. So double the bandwidth, out of any other technology that's out there. And the important thing about networking technology is when you double the bandwidth, you don't just double the efficiency, actually, winds up being a factor of six efficiency. >> Savannah: Wow. >> 'Cause if you want, I can go into that, but... >> Why not? >> Well, what I want to know, please tell me that in your labs, you have a poster on the wall that says T five, with some like Terminator kind of character. (all laughs) 'Cause that would be cool. If it's not true, just don't say anything. I'll just... >> Pete: This can actually shift into a terminator. >> Well, so this is from a switching perspective. >> Yeah. >> When we talk about the end nodes, when we talk about creating a fabric, what's the latest in terms of, well, the nicks that are going in there, what speed are we talking about today? >> So as far as 30 speeds, it tends to be 50 gigabits per second. >> David: Okay. >> Moving to a hundred gig PAM-4. >> David: Okay. >> And we do see a lot of nicks in the 200 gig Ethernet port speed. So that would be four lanes, 50 gig. But we do see that advancing to 400 gig fairly soon, 800 gig in the future. But say state of the art right now, we're seeing for the end node tends to be 200 gig E based on 50 gig PAM-4. >> Wow. >> Yeah, that's crazy. >> Yeah, that is great. My mind is act actively blown. I want to circle back to something that you brought up a second ago, which I think is really astute. When you talked about HPC moving from academia into enterprise, you're both seeing this happen, where do you think we are on the adoption curve and sort of in that cycle? Armando, do you want to go? >> Yeah, well, if you look at the market research, they're actually telling you it's 50/50 now. So Ethernet is at the level of 50%, InfinBand's at 50%, right? >> Savannah: Interesting. >> Yeah, and so what's interesting to us, customers are coming to us and say, hey, we want to see flexibility and choice and, hey, let's look at Ethernet and let's look at InfiniBand. But what is interesting about this is that we're working with Broadcom, we have their chips in our lab, we their have switches in our lab. And really what we're trying to do is make it easy to simple and configure the network for essentially MPI. And so the goal here with our validated designs is really to simplify this. So if you have a customer that, hey, I've been InfiniBand but now I want to go Ethernet, there's going to be some learning curves there. And so what we want to do is really simplify that so that we can make it easy to install, get the cluster up and running and they can actually get some value out the cluster. >> Yeah, Pete, talk about that partnership. what does that look like? I mean, are you working with Dell before the T six comes out? Or you just say what would be cool is we'll put this in the T six? >> No, we've had a very long partnership both on the hardware and the software side. Dell's been an early adopter of our silicon. We've worked very closely on SI and Sonic on the operating system, and they provide very valuable feedback for us on our roadmap. So before we put out a new chip, and we have actually three different product lines within the switching group, within Broadcom, we've then gotten very valuable feedback on the hardware and on the APIs, on the operating system that goes on top of those chips. So that way when it comes to market, Dell can take it and deliver the exact features that they have in the current generation to their customers to have that continuity. And also they give us feedback on the next gen features they'd like to see again, in both the hardware and the software. >> So I'm fascinated by... I always like to know like what, yeah, exactly. Look, you start talking about the largest supercomputers, most powerful supercomputers that exist today, and you start looking at the specs and there might be two million CPUs, 2 million CPU cores. Exoflap of performance. What are the outward limits of T five in switches, building out a fabric, what does that look like? What are the increments in terms of how many... And I know it's a depends answer, but how many nodes can you support in a scale out cluster before you need another switch? Or what does that increment of scale look like today? >> Yeah, so this is 51.2 terabytes per second. Where we see the most common implementation based on this would be with 400 gig Ethernet ports. >> David: Okay. >> So that would be 128, 400 gig E ports connected to one chip. Now, if you went to 200 gig, which is kind of the state of the art for the nicks, you can have double that. So in a single hop, you can have 256 end nodes connected through one switch. >> Okay, so this T five, that thing right there, (all laughing) inside a sheet metal box, obviously you've got a bunch of ports coming out of that. So what's the form factor look like for where that T five sits? Is there just one in a chassis or you have.. What does that look like? >> It tends to be pizza boxes these days. What you've seen overall is that the industry's moved away from chassis for these high end systems more towardS pizza boxes. And you can have composable systems where, in the past you would have line cards, either the fabric cards that the line cards are plug into or interfaced to. These days what tends to happen is you'd have a pizza box and if you wanted to build up like a virtual chassis, what you would do is use one of those pizza boxes as the fabric card, one of them as the line card. >> David: Okay. >> So what we see, the most common form factor for this is they tend to be two, I'd say for North America, most common would be a 2RU, with 64 OSFP ports. And often each of those OSFP, which is an 800 gig E or 800 gig port, we've broken out into two 400 gig ports. >> So yeah, in 2RU, and this is all air cooled, in 2RU, you've got 51.2 T. We do see some cases where customers would like to have different optics and they'll actually deploy 4RU, just so that way they have the phase-space density. So they can plug in 128, say QSFP 112. But yeah, it really depends on which optics, if you want to have DAK connectivity combined with optics. But those are the two most common form factors. >> And Armando, Ethernet isn't necessarily Ethernet in the sense that many protocols can be run over it. >> Right. >> I think I have a projector at home that's actually using Ethernet physical connections. But, so what are we talking about here in terms of the actual protocol that's running over this? Is this exactly the same as what you think of as data center Ethernet, or is this RDMA over converged Ethernet? What Are we talking about? >> Yeah, so RDMA, right? So when you look at running, essentially HPC workloads, you have the NPI protocol, so message passing interface, right? And so what you need to do is you may need to make sure that that NPI message passing interface runs efficiently on Ethernet. And so this is why we want to test and validate all these different things to make sure that that protocol runs really, really fast on Ethernet. If you look at NPIs officially, built to, hey, it was designed to run on InfiniBand but now what you see with Broadcom, with the great work they're doing, now we can make that work on Ethernet and get same performance, so that's huge for customers. >> Both of you get to see a lot of different types of customers. I kind of feel like you're a little bit of a looking into the crystal ball type because you essentially get to see the future knowing what people are trying to achieve moving forward. Talk to us about the future of Ethernet in HPC in terms of AI and ML, where do you think we're going to be next year or 10 years from now? >> You want to go first or you want me to go first? >> I can start, yeah. >> Savannah: Pete feels ready. >> So I mean, what I see, I mean, Ethernet, what we've seen is that as far as on, starting off of the switch side, is that we've consistently doubled the bandwidth every 18 to 24 months. >> That's impressive. >> Pete: Yeah. >> Nicely done, casual, humble brag there. That was great, I love that. I'm here for you. >> I mean, I think that's one of the benefits of Ethernet, is the ecosystem, is the trajectory the roadmap we've had, I mean, you don't see that in any of the networking technology. >> David: More who? (all laughing) >> So I see that, that trajectory is going to continue as far as the switches doubling in bandwidth, I think that they're evolving protocols, especially again, as you're moving away from academia into the enterprise, into cloud data centers, you need to have a combination of protocols. So you'll probably focus still on RDMA, for the supercomputing, the AI/ML workloads. But we do see that as you have a mix of the applications running on these end nodes, maybe they're interfacing to the CPUs for some processing, you might use a different mix of protocols. So I'd say it's going to be doubling a bandwidth over time, evolution of the protocols. I mean, I expect that Rocky is probably going to evolve over time depending on the AI/ML and the HPC workloads. I think also there's a big change coming as far as the physical connectivity within the data center. Like one thing we've been focusing on is co-packed optics. So right now, this chip is, all the balls in the back here, there's electrical connections. >> How many are there, by the way? 9,000 plus on the back of that-- >> 9,352. >> I love how specific it is. It's brilliant. >> Yeah, so right now, all the SERDES, all the signals are coming out electrically based, but we've actually shown, we actually we have a version of Tomahawk 4 at 25.6 T that has co-packed optics. So instead of having electrical output, you actually have optics directly out of the package. And if you look at, we'll have a version of Tomahawk 5. >> Nice. >> Where it's actually even a smaller form factor than this, where instead of having the electrical output from the bottom, you actually have fibers that plug directly into the sides. >> Wow. Cool. >> So I see there's the bandwidth, there's radix's increasing, protocols, different physical connectivity. So I think there's a lot of things throughout, and the protocol stack's also evolving. So a lot of excitement, a lot of new technology coming to bear. >> Okay, You just threw a carrot down the rabbit hole. I'm only going to chase this one, okay? >> Peter: All right. >> So I think of individual discreet physical connections to the back of those balls. >> Yeah. >> So if there's 9,000, fill in the blank, that's how many connections there are. How do you do that many optical connections? What's the mapping there? What does that look like? >> So what we've announced for Tomahawk 5 is it would have FR4 optics coming out. So you'd actually have 512 fiber pairs coming out. So basically on all four sides, you'd have these fiber ribbons that come in and connect. There's actually fibers coming out of the sides there. We wind up having, actually, I think in this case, we would actually have 512 channels and it would wind up being on 128 actual fiber pairs because-- >> It's miraculous, essentially. >> Savannah: I know. >> Yeah. So a lot of people are going to be looking at this and thinking in terms of InfiniBand versus Ethernet, I think you've highlighted some of the benefits of specifically running Ethernet moving forward as HPC which sort of just trails slightly behind super computing as we define it, becomes more pervasive AI/ML. What are some of the other things that maybe people might not immediately think about when they think about the advantages of running Ethernet in that environment? Is it about connecting the HPC part of their business into the rest of it? What are the advantages? >> Yeah, I mean, that's a big thing. I think, and one of the biggest things that Ethernet has again, is that the data centers, the networks within enterprises, within clouds right now are run on Ethernet. So now, if you want to add services for your customers, the easiest thing for you to do is the drop in clusters that are connected with the same networking technology. So I think one of the biggest things there is that if you look at what's happening with some of the other proprietary technologies, I mean, in some cases they'll have two different types of networking technologies before they interface to Ethernet. So now you've got to train your technicians, you train your assist admins on two different network technologies. You need to have all the debug technology, all the interconnect for that. So here, the easiest thing is you can use Ethernet, it's going to give you the same performance and actually, in some cases, we've seen better performance than we've seen with Omni-Path, better than in InfiniBand. >> That's awesome. Armando, we didn't get to you, so I want to make sure we get your future hot take. Where do you see the future of Ethernet here in HPC? >> Well, Pete hit on a big thing is bandwidth, right? So when you look at, train a model, okay? So when you go and train a model in AI, you need to have a lot of data in order to train that model, right? So what you do is essentially, you build a model, you choose whatever neural network you want to utilize. But if you don't have a good data set that's trained over that model, you can't essentially train the model. So if you have bandwidth, you want big pipes because you have to move that data set from the storage to the CPU. And essentially, if you're going to do it maybe on CPU only, but if you do it on accelerators, well, guess what? You need a big pipe in order to get all that data through. And here's the deal, the bigger the pipe you have, the more data, the faster you can train that model. So the faster you can train that model, guess what? The faster you get to some new insight, maybe it's a new competitive advantage, maybe it's some new way you design a product, but that's a benefit of speed, you want faster, faster, faster. >> It's all about making it faster and easier-- for the users. >> Armando: It is. >> I love that. Last question for you, Pete, just because you've said Tomahawk seven times, and I'm thinking we're in Texas, stakes, there's a lot going on with that. >> Making me hungry. >> I know, exactly. I'm sitting out here thinking, man, I did not have big enough breakfast. How did you come up with the name Tomahawk? >> So Tomahawk, I think it just came from a list. So we have a tried end product line. >> Savannah: Ah, yes. >> Which is a missile product line. And Tomahawk is being kind of like the bigger and batter missile, so. >> Savannah: Love this. Yeah, I mean-- >> So do you like your engineers? You get to name it. >> Had to ask. >> It's collaborative. >> Okay. >> We want to make sure everyone's in sync with it. >> So just it's not the Aquaman tried. >> Right. >> It's the steak Tomahawk. I think we're good now. >> Now that we've cleared that-- >> Now we've cleared that up. >> Armando, Pete, it was really nice to have both you. Thank you for teaching us about the future of Ethernet and HCP. David Nicholson, always a pleasure to share the stage with you. And thank you all for tuning in to theCUBE live from Dallas. We're here talking all things HPC and supercomputing all day long. We hope you'll continue to tune in. My name's Savannah Peterson, thanks for joining us. (soft music)

>>Hello everyone. Welcome to the Cubes Live here in Dallas, Texas. I'm John Ferer, host of the Cube, Three days of wall to wall coverage. Of course, we've got the three fabulous guests here, myself, Savannah, Peterson. S look wonderful. >>Thank you. Jong on. I, I feel lucky to play the part here with my 10 gallon hat. >>Dave Nicholson, who's the analyst uncovering all the Dell Supercomputing, hpe all the technology is changing the game. Dave, you look great. Thanks for coming on. >>Thanks, John. I appreciate >>It. All right, so, so, so you look good. So we're in Dallas, Texas is a trade show conference. I don't know what you'd call this these days, but thousands of booths are here. What's the take here? Why supercomputing 22? What's the big deal? >>Well, the big deal is dramatic incremental progress in terms of supercomputing capability. So what this conference represents is the leading edge in what it can deliver to the world. We're talking about scale that is impossible to comprehend with the human brain, but you can toss out facts and figures like performance measured in ex flops, millions of CPU cores working together, thousands of kilowatts of power required to power these systems. And I think what makes this, what makes this show unique is that it's not just a bunch of vendors, but it's academia. It's PhD candidates coming and looking for companies that they might work with. So it's a very, very different vibe here. >>Savannah, we were talking last night before we were setting up our agenda for it to drill down on this week. And you know, you were, by the way, that looks great. I mean, I wish I had one. >>We'll get you one by the end of the show, >>John. Don't worry. You know, Texas is always big in Texas and that's the, the thing here, but Supercomputing seems like that had a lull for a while. Yeah, it seems like it's gonna explode and you get a chance to review the papers, take a look at it. You, you're a, I won't say closet hardware nerd, but that's your roots. >>Yeah, yeah. Very openly hardware nerd. And, and I'm excited because I, we saw a lot of hype around quantum and around AI five, 10 years ago, but we weren't seeing the application at scale and we also weren't seeing, quite frankly, the hardware wasn't ready to power these types of endeavors at scale. Whereas now, you know, we've got, we've got air cooling, we've got liquid cooling, we've got multiple GPU's. Dell was just showing me all eight of theirs that they put in their beautiful million dollar piece of equipment, which is extremely impressive for folks to run complex calculations. And, but what I'm excited about with all the, I love when we fuse business and academia together, I think that that doesn't happen very often. I've been impressed. I mean, when I walked in today, right away, I'm sure y'all can't see this at home just yet, but we'll try and give you a feel over the course of the next few days. This conference is huge. This >>Is, yeah, it is >>Way bigger than I was expecting, You know, a lot larger than where we just were in Detroit. And, and I love it because we've got the people that are literally inventing the calculations that will determine a lot of our future from sequencing our genome to powering our weather forecasting, as well as all of the companies that create the hardware and the software that's gonna actually support that. Those algorithms and >>Those, and, and the science and the engineering involved has just been going on since 1988. This conference, this trade show going on since 1988, which is, it, it passes the test of time and now the future with all the new use cases emerging from the compute and supercomputing architectures out there, it's from cradle to grave. If you're, if you're in this business, you, you're in school all the way through the industry, it doesn't seem to stop that, that university student side of it. I mean that whole student section here. So you don't see that very often in some of these tech shows, like from students to boardroom. >>Yeah. I actually brought the super computer from 1988 with me in my pocket. And I'm not sure that I'm even joking. I this may have as much processing power, certainly as much storage with one terabyte on board. I sprung for the one terabyte folks. But it is mind boggling the amount of compute power we're, we're talking about. When you dig below the surface, which we'll be doing in the coming days, you see things like leaping from P C I E, you know, gen four to gen five, and the increase that that gives us in, in terms of capabilities for plugging into the motherboard and accessing the CPU complex and on and on and on. But, but you know, something Savannah alluded to, we're talking about the leading edge of what is possible from a humanity perspective. 1%. And, and so I'd like to get into, you know, as we're we're talking to some of the experts that we'll get a chance to talk to, I'd like to get their view on what the future holds and whether we can simply grow through quantitative increases in compute power, or if the real promise is out there in the land of quantum computing, are we all sort of hanging our hats, our large 10 gallon hats? >>If that's yes. Our hats, if we're hanging our hats on that, that that's when truly we'll be able to tease insight out of chaos. I'd like to hear from some of the real experts on that subject. >>I'm glad you brought that up, cuz I'm personally pretty pumped about quantum computing, but I've seen it sit in this hype stage for quite a while and I'm ready for the application. So I'm curious to hear >>What our experts, That's an awesome, that would be, I think that would be an awesome bumper sticker. Frankly. Savannah, I'm pumped, I'm pumped about quantum computing. Who is this person? Who is this person? >>I wanna see it first. Did someone show me it? >>Yeah, yeah. 400 qubits I think was the latest IBM announcement, which, which means something. I'll pretend like I completely understand what it means. >>Tell us what that means, David. >>Well, well, so, so Savannah, let me man explain it to you. Yeah, >>Let's >>Hear it. So, so it's basically, it's, you know, in conventional computing you can either, you can either be on or off zero or one in quantum computing, you can be both, neither or all of the above. That's, that's, that's, that's the depth to which I can go. I >>Like that. That was actually a succinct, as humanly possible >>Really sounds like a Ponzi scheme to me. I, I'm not sure if I, >>Well, let's get into some of the thoughts that you guys have on some of the papers. We saw Savannah and Dave, your perspective on this whole next level kind of expansion with supercomputing and super cloud and super apps will do for this next gen. What use cases are kind of shining out of this, because, you know, it used to be you were limited by how much gear you had stacked up, how big the server could be, the supercomputer. Now you've got large scale cloud computing, you got the ability to have different subsystems like advances in networking. So you're seeing a new architectural, almost bigger. Super computing isn't just a machine, it's a collection of machines, It's a collection of Yeah. Of other stuff. What's your thoughts on these, this architecture and then the use cases that are gonna emerge that were not getable before? >>So in the past, you, you talk about, you know, 1988 and, and you know, let's say a decade ago, the race was to assemble enough compute power to be able to do things quickly enough to be practical. So we knew that if we applied software to hardware, we could get an answer to a problem because we were asking very, very specific questions. And how quickly we got the answer would determine whether it was practical to pursue it or not. So if something took a day instead of a month, okay, fantastic. But now we've reached this critical mass. You could argue when that happened, but definitely I think we're there where things like artificial intelligence and machine learning are the core of what we're doing. We're not just simply asking systems to deliver defined answers. We're asking them to learn from their experiences, starts getting a little spooky, and we're asking them to tease insights out in a way that we haven't figured out. >>So we're saying give us the insight. We're not telling the system specifically how to give us that insight. So I think that's, that's the fundamental difference that's the frontier, is, you know, you're gonna hear a lot about AI and ml and then if you retreat back a bit from Supercomputing, you're in the realm of high performance computing, which is sort of junior version of supercomputing. It's instead of the billion dollar system, it's the system that, you know, schlubs like, like, like, like Facebook or AWS might be able to afford, you know, maybe a hundred million dollars for a system casual, just, just sort of casual kind of thing next to the coffee table in the living room. But I think that's really gonna be the talk. So that's a huge tent when you talk about AI and ml. Yeah, >>I I, I totally agree. We're having some of the conversations that we've had for a long time about AI and bias. I saw a lot of the papers were looking at that. I think that's what's gonna be really interesting to me, what's most exciting about this is how are we pulling together all of this on a global scale. So I'm excited to see how supercomputing impacts climate change, our ability to monitor environmental conditions around the globe and different governments and bodies can all combine. And all of this information can be going into a central brain and learning from it and figuring out how we can make the world a better place. We're learning about the body. There's a lot of people doing molecular biology and sequencing of the genome here. We've got, there's, there's, It's just, it's very, I I don't think a lot of people realize that supercomputing pretty much touches every aspect of our >>Lives. I mean, we've had it, we've had it for a while. I think cloud computing took a lot of the attention, given that that brought in massive capabilities, a lot of agility. And I think what's interesting here at this show, if you look at, you know, what's going on from the guess, like I said, from the dorm room to the boardroom, everyone's here, but you look at what's actually going on above the hardware, CNCF is here. They have a booth, the whole cloud native software business. It's gonna be interesting to see how the software business takes advantage of totally. How these architectures, because let's face it, I've never heard a developer pointer say, I wanna run on slower hardware. So no one wants that. So now if you abstract away the hardware, as we know with, with cloud computing and DevOps cloud on premises and Edge, David, this is like, this is again, nirvana for the industry because you want, it's an exciting thing, the fastest possible compute system for the software. >>Yeah, yeah. >>I I, at the end of the day, that's what we're talking >>About. So I asked, I asked the, the gift question to my Wharton students this morning on a call, and I, you know, I asked specifically if, if I could give you something that was the result of super computing's amazing nature, what would it be? Would it be personalized therapeutics in healthcare? Would it be something related to climate? Being able to figure out exactly what we can do. There's a whole range of possibilities. And what's interesting is >>What were some of the answers? >>So, so, so a lot of the answers, a lot of the answers came down to, to two categories and it was really, it was healthcare and climate. Yeah. A lot of, a lot of understanding and of course, and of course a lot of jokes about how eventually supercomputers will determine that. The problem is people, >>It's people. Yeah, no. So I knew you were headed there, >>But >>Don't people just want custom jeans? Yeah. >>Or, well, so one of the, one of the good ones though was, >>Was also that >>While we're >>Here, a person from a company who shall not be named said, oh, advertising, it was the, it was the what if you could predict with a high degree of certainty that when you sent someone an email saying, Hey, do you wanna buy this? They would say, Well, yeah, I do. Dramatically lowering the cost of acquisition for an individual customer as an example. Those are the kinds of breakthroughs that will transform how we live. Because all of a sudden, industries are completely disrupted, disrupted, not necessarily directly related to supercomputing, but you think about automating the entire fleet of, of, of trucks in, in North America. What does that do to people who currently drive those trucks? Yeah, so there are, there are societal questions at hand that I don't necessarily know the academics are, are, are considering when they're thinking what's possible. >>Well, I think, I think the point about the ad thing brings up the whole cultural shift that's going on from the old generation of, Hey, let's use our best minds in the industry to figure out how to place an ad at the right place in the right pixel, at the right time. Versus solving real problems like climate change our, you know, culture and society and get us getting along as a country and world water sustainability fires in California. Yeah, I mean, come on. >>There's a lot. So I, I gotta say, I was curious when you were playing with your pocket computer there and talking about the terabyte that you have inside. So back in 1988 when Supercomputing started, the first show was in Orlando. It was actually the same four days that we're here right now. I was born in 1988 if we're just talking about how great 1988 is. And so I guess I, >>I was born, So were we Savannah? So were we >>The era of, I think I was in third grade at that time. >>We won't tell, we won't say what you told me earlier about 1988 for you. But that said, so 1988 was when Steve Jobs released the next computer. He was out of Apple at that time. Yeah, that's right. >>Eight >>Megabytes of Ram. >>It's called the Cube. I think >>It's respectable. That's all it was called. It was, it was, it was, it was the cube, which is pretty, pretty exciting. But when we were looking at, yeah, on the supercomputing side, your phone would've been about, is a capable, >>So where will we be in 20 years? It's amazing >>What we gonna, >>Will our holograms be here instead of us physically sitting, sitting at the table? I don't know. >>Well, it's gonna be very interesting to see how the global ecosystem evolves. It used to be very nationalistic culture with computing. I think, I think we're gonna see global, you know, flattening of culture relative to computing. I think space will be a, a massive hopeful, massive discussion. I think software and automation will be at levels we don't even see. So I think software, to me, I'm looking at, that's the enablement of this supercomputing show. In terms of the next five years, what are they gonna do to enable more faster intelligent horsepower? And, and what does that look like? Is it, it used to be simple processor, more processors, more threads, multicores, and then stuff around it. I think this is where I think it's gonna shift to more network computing, network processing, edge latency, physics is involved. I mean, every, everything you can squeeze out of the physics will be Yeah. Interesting to watch. Well, when >>We, when we, when we peel back the cover on the actual pieces of hardware that are driving this revolution, parallelizing, you know, of workloads is critical to this. It's what super computing consists of. There's no such thing as a supercomputer sitting by itself on a table. Even the million dollar system from Dell, which is crazy when you hear Dell and million dollar system. >>And it's still there too, >>Right? Just, just hanging out. Yeah. But, but it's all about the interconnect. When you want to take advantage of parallel processing, you have to have software that can leverage all of the resources and connectivity becomes increasingly important. I think that's gonna be a thread that we're gonna see throughout the next few days with the, with the, you know, the motherboards, for lack of a lack of a better term, allowing faster access to memory, faster access to cpu, gpu, dpu, networking, storage devices, plugging in those all work together. But increasingly it's that connectivity layer that's critically important. Questions of InfiniBand versus ethernet. Our DMA over converged ethernet as an example, a lot of these architectural decisions are gonna be based on power cooling, dead city. So lot of details behind the scenes to make the magic happen. I >>Think the power is gonna be, you know, thinking 20 years out, hopefully everything here is powered sustainably 20 years from now because power pull, I mean these, the more exciting things going on in your supercomputer. The power suck is massive. That when we were talking to Dell, they were saying that's one of the biggest problems, >>Concerns, that's gonna their customers and that's gonna play into sustainability. So a lot of great guests, we got folks from Dell and the industry, a lot of the manufacturers, a lot of the hardware software experts gonna come on and share what's going on. You know, we did a, we did a post why hardware matters a few months ago, Dave. Everyone's like, well it does now more than ever. So we're gonna get into it here at Supercomputing 22, where the hardware matters. Faster power, as we say for the applications. Mr. Cube, moving back with more live coverage. Stay with us back.

(upbeat music) >> The market for enterprise servers is large and it generates well north of $100 billion in annual revenue, and it's growing consistently in the mid to high single digit range. Right now, like many segments, the market for servers is, it's like slingshotting, right? Organizations, they've been replenishing their install bases and upgrading, especially at HQs coming out of the isolation economy. But the macro headwinds, as we've reported, are impacting all segments of the market. CIOs, you know, they're tapping the brakes a little bit, sometimes quite a bit and being cautious with both capital expenditures and discretionary opex, particularly in the cloud. They're dialing it down and just being a little bit more, you know, cautious. The market for enterprise servers, it's dominated as you know, by x86 based systems with an increasingly large contribution coming from alternatives like ARM and NVIDIA. Intel, of course, is the largest supplier, but AMD has been incredibly successful competing with Intel because of its focus, it's got an outsourced manufacturing model and its innovation and very solid execution. Intel's frequent delays with its next generation Sapphire Rapid CPUs, now slated for January 2023 have created an opportunity for AMD, specifically AMD's next generation EPYC CPUs codenamed Genoa will offer as many as 96 Zen 4 cores per CPU when it launches later on this month. Observers can expect really three classes of Genoa. There's a standard Zen 4 compute platform for general purpose workloads, there's a compute density optimized Zen 4 package and then a cache optimized version for data intensive workloads. Indeed, the makers of enterprise servers are responding to customer requirements for more diversity and server platforms to handle different workloads, especially those high performance data-oriented workloads that are being driven by AI and machine learning and high performance computing, HPC needs. OEMs like Dell, they're going to be tapping these innovations and try to get to the market early. Dell, in particular, will be using these systems as the basis for its next generation Gen 16 servers, which are going to bring new capabilities to the market. Now, of course, Dell is not alone, there's got other OEM, you've got HPE, Lenovo, you've got ODMs, you've got the cloud players, they're all going to be looking to keep pace with the market. Now, the other big trend that we've seen in the market is the way customers are thinking about or should be thinking about performance. No longer is the clock speed of the CPU the soul and most indicative performance metric. There's much more emphasis in innovation around all those supporting components in a system, specifically the parts of the system that take advantage, for example, of faster bus speeds. We're talking about things like network interface cards and RAID controllers and memories and other peripheral devices that in combination with microprocessors, determine how well systems can perform and those kind of things around compute operations, IO and other critical tasks. Now, the combinatorial factors ultimately determine the overall performance of the system and how well suited a particular server is to handling different workloads. So we're seeing OEMs like Dell, they're building flexibility into their offerings and putting out products in their portfolios that can meet the changing needs of their customers. Welcome to our ongoing series where we investigate the critical question, does hardware matter? My name is Dave Vellante, and with me today to discuss these trends and the things that you should know about for the next generation of server architectures is former CTO from Oracle and EMC and adjunct faculty and Wharton CTO Academy, David Nicholson. Dave, always great to have you on "theCUBE." Thanks for making some time with me. >> Yeah, of course, Dave, great to be here. >> All right, so you heard my little spiel in the intro, that summary, >> Yeah. >> Was it accurate? What would you add? What do people need to know? >> Yeah, no, no, no, 100% accurate, but you know, I'm a resident nerd, so just, you know, some kind of clarification. If we think of things like microprocessor release cycles, it's always going to be characterized as rolling thunder. I think 2023 in particular is going to be this constant release cycle that we're going to see. You mentioned the, (clears throat) excuse me, general processors with 96 cores, shortly after the 96 core release, we'll see that 128 core release that you referenced in terms of compute density. And then, we can talk about what it means in terms of, you know, nanometers and performance per core and everything else. But yeah, no, that's the main thing I would say, is just people shouldn't look at this like a new car's being released on Saturday. This is going to happen over the next 18 months, really. >> All right, so to that point, you think about Dell's next generation systems, they're going to be featuring these new AMD processes, but to your point, when you think about performance claims, in this industry, it's a moving target. It's that, you call it a rolling thunder. So what does that game of hopscotch, if you will, look like? How do you see it unfolding over the next 12 to 18 months? >> So out of the gate, you know, slated as of right now for a November 10th release, AMD's going to be first to market with, you know, everyone will argue, but first to market with five nanometer technology in production systems, 96 cores. What's important though is, those microprocessors are going to be resident on motherboards from Dell that feature things like PCIe 5.0 technology. So everything surrounding the microprocessor complex is faster. Again, going back to this idea of rolling thunder, we expect the Gen 16 PowerEdge servers from Dell to similarly be rolled out in stages with initial releases that will address certain specific kinds of workloads and follow on releases with a variety of systems configured in a variety of ways. >> So I appreciate you painting a picture. Let's kind of stay inside under the hood, if we can, >> Sure. >> And share with us what we should know about these kind of next generation CPUs. How are companies like Dell going to be configuring them? How important are clock speeds and core counts in these new systems? And what about, you mentioned motherboards, what about next gen motherboards? You mentioned PCIe Gen 5, where does that fit in? So take us inside deeper into the system, please. >> Yeah, so if you will, you know, if you will join me for a moment, let's crack open the box and look inside. It's not just microprocessors. Like I said, they're plugged into a bus architecture that interconnect. How quickly that interconnect performs is critical. Now, I'm going to give you a statistic that doesn't require a PhD to understand. When we go from PCIe Gen 4 to Gen 5, which is going to be featured in all of these systems, we double the performance. So just, you can write that down, two, 2X. The performance is doubled, but the numbers are pretty staggering in terms of giga transactions per second, 128 gigabytes per second of aggregate bandwidth on the motherboard. Again, doubling when going from 4th Gen to 5th Gen. But the reality is, most users of these systems are still on PCIe Gen 3 based systems. So for them, just from a bus architecture perspective, you're doing a 4X or 8X leap in performance, and then all of the peripherals that plug into that faster bus are faster, whether it's RAID control cards from RAID controllers or storage controllers or network interface cards. Companies like Broadcom come to mind. All of their components are leapfrogging their prior generation to fit into this ecosystem. >> So I wonder if we could stay with PCIe for a moment and, you know, just understand what Gen 5 brings. You said, you know, 2X, I think we're talking bandwidth here. Is there a latency impact? You know, why does this matter? And just, you know, this premise that these other components increasingly matter more, Which components of the system are we talking about that can actually take advantage of PCIe Gen 5? >> Pretty much all of them, Dave. So whether it's memory plugged in or network interface cards, so communication to the outside world, which computer servers tend to want to do in 2022, controllers that are attached to internal and external storage devices. All of them benefit from this enhancement and performance. And it's, you know, PCI express performance is measured in essentially bandwidth and throughput in the sense of the numbers of transactions per second that you can do. It's mind numbing, I want to say it's 32 giga transfers per second. And then in terms of bandwidth, again, across the lanes that are available, 128 gigabytes per second. I'm going to have to check if it's gigabits or gigabytes. It's a massive number. And again, it's double what PCIe 4 is before. So what does that mean? Just like the advances in microprocessor technology, you can consolidate massive amounts of work into a much smaller footprint. That's critical because everything in that server is consuming power. So when you look at next generation hardware that's driven by things like AMD Genoa or you know, the EPYC processors, the Zen with the Z4 microprocessors, for every dollar that you're spending on power and equipment and everything else, you're getting far greater return on your investment. Now, I need to say that we anticipate that these individual servers, if you're out shopping for a server, and that's a very nebulous term because they come in all sorts of shapes and sizes, I think there's going to be a little bit of sticker shock at first until you run the numbers. People will look at an individual server and they'll say, wow, this is expensive and the peripherals, the things that are going into those slots are more expensive, but you're getting more bang for your buck. You're getting much more consolidation, lower power usage and for every dollar, you're getting a greater amount of performance and transactions, which translates up the stack through the application layer and, you know, out to the end user's desire to get work done. >> So I want to come back to that, but let me stay on performance for a minute. You know, we all used to be, when you'd go buy a new PC, you'd be like, what's the clock speed of that? And so, when you think about performance of a system today and how measurements are changing, how should customers think about performance in these next gen systems? And where does that, again, where does that supporting ecosystem play? >> So if you are really into the speeds and feeds and what's under the covers, from an academic perspective, you can go in and you can look at the die size that was used to create the microprocessors, the clock speeds, how many cores there are, but really, the answer is look at the benchmarks that are created through testing, especially from third party organizations that test these things for workloads that you intend to use these servers for. So if you are looking to support something like a high performance environment for artificial intelligence or machine learning, look at the benchmarks as they're recorded, as they're delivered by the entire system. So it's not just about the core. So yeah, it's interesting to look at clock speeds to kind of compare where we are with regards to Moore's Law. Have we been able to continue to track along that path? We know there are physical limitations to Moore's Law from an individual microprocessor perspective, but none of that really matters. What really matters is what can this system that I'm buying deliver in terms of application performance and user requirement performance? So that's what I'd say you want to look for. >> So I presume we're going to see these benchmarks at some point, I'm hoping we can, I'm hoping we can have you back on to talk about them. Is that something that we can expect in the future? >> Yeah, 100%, 100%. Dell, and I'm sure other companies, are furiously working away to demonstrate the advantages of this next gen architecture. If I had to guess, I would say that we are going to see quite a few world records set because of the combination of things, like faster network interface cards, faster storage cards, faster memory, more memory, faster cache, more cache, along with the enhanced microprocessors that are going to be delivered. And you mentioned this is, you know, AMD is sort of starting off this season of rolling thunder and in a few months, we'll start getting the initial entries from Intel also, and we'll be able to compare where they fit in with what AMD is offering. I'd expect OEMs like Dell to have, you know, a portfolio of products that highlight the advantages of each processor's set. >> Yeah, I talked in my open Dave about the diversity of workloads. What are some of those emerging workloads and how will companies like Dell address them in your view? >> So a lot of the applications that are going to be supported are what we think of as legacy application environments. A lot of Oracle databases, workloads associated with ERP, all of those things are just going to get better bang for their buck from a compute perspective. But what we're going to be hearing a lot about and what the future really holds for us that's exciting is this arena of artificial intelligence and machine learning. These next gen platforms offer performance that allows us to do things in areas like natural language processing that we just couldn't do before cost effectively. So I think the next few years are going to see a lot of advances in AI and ML that will be debated in the larger culture and that will excite a lot of computer scientists. So that's it, AI/ML are going to be the big buzzwords moving forward. >> So Dave, you talked earlier about this, some people might have sticker shocks. So some of the infrastructure pros that are watching this might be, oh, okay, I'm going to have to pitch this, especially in this, you know, tough macro environment. I'm going to have to sell this to my CIO, my CFO. So what does this all mean? You know, if they're going to have to pay more, how is it going to affect TCO? How would you pitch that to your management? >> As long as you stay away from per unit cost, you're fine. And again, we don't have necessarily, or I don't have necessarily insider access to street pricing on next gen servers yet, but what I do know from examining what the component suppliers tell us is that, these systems are going to be significantly more expensive on a per unit basis. But what does that mean? If the server that you're used to buying for five bucks is now 10 bucks, but it's doing five times as much work, it's a great deal, and anyone who looks at it and says, 10 bucks? It used to only be five bucks, well, the ROI and the TCO, that's where all of this really needs to be measured and a huge part of that is going to be power consumption. And along with the performance tests that we expect to see coming out imminently, we should also be expecting to see some of those ROI metrics, especially around power consumption. So I don't think it's going to be a problem moving forward, but there will be some sticker shock. I imagine you're going to be able to go in and configure a very, very expensive, fully loaded system on some of these configurators online over the next year. >> So it's consolidation, which means you could do more with less. It's going to be, or more with the same, it's going to be lower power, less cooling, less floor space and lower management overhead, which is kind of now you get into staff, so you're going to have to sort of identify how the staff can be productive in other areas. You're probably not going to fire people hopefully. But yeah, it sounds like it's going to be a really consolidation play. I talked at the open about Intel and AMD and Intel coming out with Sapphire Rapids, you know, of course it's been well documented, it's late but they're now scheduled for January. Pat Gelsinger's talked about this, and of course they're going to try to leapfrog AMD and then AMD is going to respond, you talked about this earlier, so that game is going to continue. How long do you think this cycle will last? >> Forever. (laughs) It's just that, there will be periods of excitement like we're going to experience over at least the next year and then there will be a lull and then there will be a period of excitement. But along the way, we've got lurkers who are trying to disrupt this market completely. You know, specifically you think about ARM where the original design point was, okay, you're powered by a battery, you have to fit in someone's pocket. You can't catch on fire and burn their leg. That's sort of the requirement, as opposed to the, you know, the x86 model, which is okay, you have a data center with a raised floor and you have a nuclear power plant down the street. So don't worry about it. As long as an 18-wheeler can get it to where it needs to be, we'll be okay. And so, you would think that over time, ARM is going to creep up as all destructive technologies do, and we've seen that, we've definitely seen that. But I would argue that we haven't seen it happen as quickly as maybe some of us expected. And then you've got NVIDIA kind of off to the side starting out, you know, heavy in the GPU space saying, hey, you know what, you can use the stuff we build for a whole lot of really cool new stuff. So they're running in a different direction, sort of gnawing at the traditional x86 vendors certainly. >> Yes, so I'm glad- >> That's going to be forever. >> I'm glad you brought up ARM and NVIDIA, I think, but you know, maybe it hasn't happened as quickly as many thought, although there's clearly pockets and examples where it is taking shape. But this to me, Dave, talks to the supporting cast. It's not just about the microprocessor unit anymore, specifically, you know, generally, but specifically the x86. It's the supporting, it's the CPU, the NPU, the XPU, if you will, but also all those surrounding components that, to your earlier point, are taking advantage of the faster bus speeds. >> Yeah, no, 100%. You know, look at it this way. A server used to be measured, well, they still are, you know, how many U of rack space does it take up? You had pizza box servers with a physical enclosure. Increasingly, you have the concept of a server in quotes being the aggregation of components that are all plugged together that share maybe a bus architecture. But those things are all connected internally and externally, especially externally, whether it's external storage, certainly networks. You talk about HPC, it's just not one server. It's hundreds or thousands of servers. So you could argue that we are in the era of connectivity and the real critical changes that we're going to see with these next generation server platforms are really centered on the bus architecture, PCIe 5, and the things that get plugged into those slots. So if you're looking at 25 gig or 100 gig NICs and what that means from a performance and/or consolidation perspective, or things like RDMA over Converged Ethernet, what that means for connecting systems, those factors will be at least as important as the microprocessor complexes. I imagine IT professionals going out and making the decision, okay, we're going to buy these systems with these microprocessors, with this number of cores in memory. Okay, great. But the real work starts when you start talking about connecting all of them together. What does that look like? So yeah, the definition of what constitutes a server and what's critically important I think has definitely changed. >> Dave, let's wrap. What can our audience expect in the future? You talked earlier about you're going to be able to get benchmarks, so that we can quantify these innovations that we've been talking about, bring us home. >> Yeah, I'm looking forward to taking a solid look at some of the performance benchmarking that's going to come out, these legitimate attempts to set world records and those questions about ROI and TCO. I want solid information about what my dollar is getting me. I think it helps the server vendors to be able to express that in a concrete way because our understanding is these things on a per unit basis are going to be more expensive and you're going to have to justify them. So that's really what, it's the details that are going to come the day of the launch and in subsequent weeks. So I think we're going to be busy for the next year focusing on a lot of hardware that, yes, does matter. So, you know, hang on, it's going to be a fun ride. >> All right, Dave, we're going to leave it there. Thanks you so much, my friend. Appreciate you coming on. >> Thanks, Dave. >> Okay, and don't forget to check out the special website that we've set up for this ongoing series. Go to doeshardwarematter.com and you'll see commentary from industry leaders, we got analysts on there, technical experts from all over the world. Thanks for watching, and we'll see you next time. (upbeat music)

(upbeat music) >> Hello everyone, welcome to this CUBE Showcase, accelerating business transformation with VMware Cloud on AWS. It's a solution innovation conversation with two great guests, Fred Wurden, VP of Commercial Services at AWS and Narayan Bharadwaj, who's the VP and General Manager of Cloud Solutions at VMware. Gentlemen, thanks for joining me on the showcase. >> Great to be here. >> Great. Thanks for having us on. It's a great topic. >> We've been covering this VMware cloud on AWS since the launch going back and it's been amazing to watch the evolution from people saying, Oh, it's the worst thing I've ever seen. What's this mean? And the press were not really on board with the vision, but as it played out as you guys had announced together, it did work out great for VMware. It did work out great for AWS and it continues two years later and I want to just get an update from you guys on where you guys see this has been going. I'll see multiple years. Where is the evolution of the solution as we are right now coming off VMware explorer just recently and going in to re:Invent, which is only a couple weeks away Feels like tomorrow. But as we prepare, a lot going on. Where are we with the evolution of the solution? >> I mean, first thing I want to say is October 2016 was a seminal moment in the history of IT. When Pat Gelsinger and Andy Jassy came together to announce this. And I think John, you were there at the time I was there. It was a great, great moment. We launched the solution in 2017 year after that at VMworld, back when we called it VMworld. I think we have gone from strength to strength. One of the things that has really mattered to us is we've learned from AWS also in the processes, this notion of working backwards. So we really, really focused on customer feedback as we built a service offering now five years old. Pretty remarkable journey. In the first years we tried to get across all the regions, that was a big focus because there was so much demand for it. In the second year, we started going really on enterprise great features. We invented this pretty awesome feature called Stretched Clusters, where you could stretch a vSphere cluster using vSAN and NSX-T across to AZs in the same region. Pretty phenomenal four nines of availability that applications started to get with that particular feature. And we kept moving forward, all kinds of integration with AWS Direct Connect, Transit Gateways with our own advanced networking capabilities. Along the way, Disaster Recovery, we punched out two new services just focused on that. And then more recently we launched our Outposts partnership. We were up on stage at re:Invent, again, with Pat and Andy announcing AWS Outposts and the VMware flavor of that, VMware Cloud and AWS Outposts. I think it's been significant growth in our federal sector as well with our federal and high certification more recently. So all in all, we are super excited. We're five years old. The customer momentum is really, really strong and we are scaling the service massively across all geos and industries. >> That's great, great update. And I think one of the things that you mentioned was how the advantages you guys got from that relationship. And this has been the theme for AWS, man, since I can remember from day one, Fred. You guys do the heavy lifting as you always say for the customers. Here, VMware comes on board. Takes advantage of the AWS and just doesn't miss a beat. Continues to move their workloads that everyone's using, vSphere, and these are big workloads on AWS. What's the AWS perspective on this? How do you see it? >> Yeah, it's pretty fascinating to watch how fast customers can actually transform and move when you take the skill set that they're familiar with and the advanced capabilities that they've been using on-prem and then overlay it on top of the AWS infrastructure that's evolving quickly and building out new hardware and new instances we'll talk about. But that combined experience between both of us on a jointly engineered solution to bring the best security and the best features that really matter for those workloads drive a lot of efficiency and speed for the customers. So it's been well received and the partnership is stronger than ever from an engineering standpoint, from a business standpoint. And obviously it's been very interesting to look at just how we stay day one in terms of looking at new features and work and responding to what customers want. So pretty excited about just seeing the transformation and the speed that which customers can move to while at VMC. >> That's a great value proposition. We've been talking about that in context to anyone building on top of the cloud. They can have their own supercloud, as we call it, if you take advantage of all the CapEx and investment Amazon's made and AWS has made and continues to make in performance IaaS and PaaS, all great stuff. I have to ask you guys both as you guys see this going to the next level, what are some of the differentiations you see around the service compared to other options in the market? What makes it different? What's the combination? You mentioned jointly engineered. What are some of the key differentiators of the service compared to others? >> Yeah. I think one of the key things Fred talked about is this jointly engineered notion. Right from day one we were the early adopters of the AWS Nitro platform. The reinvention of EC2 back five years ago. And so we have been having a very, very strong engineering partnership at that level. I think from a VMware customer standpoint, you get the full software-defined data center, compute storage networking on EC2, bare metal across all regions. You can scale that elastically up and down. It's pretty phenomenal just having that consistency globally on AWS EC2 global regions. Now the other thing that's a real differentiator for us, what customers tell us about is this whole notion of a managed service. And this was somewhat new to VMware. But we took away the pain of this undifferentiated heavy lifting where customers had to provision rack stack hardware, configure the software on top, and then upgrade the software and the security patches on top. So we took away all of that pain as customers transitioned to VMware cloud in AWS. In fact, my favorite story from last year when we were all going through the Log4j debacle. Industry was just going through that. Favorite proof point from customers was before they could even race this issue to us, we sent them a notification saying, we already patched all of your systems, no action from you. The customers were super thrilled. I mean, these are large banks. Many other customers around the world were super thrilled they had to take no action, but a pretty incredible industry challenge that we were all facing. >> Narayan, that's a great point. The whole managed service piece brings up the security. You kind of teasing at it, but there's always vulnerabilities that emerge when you are doing complex logic. And as you grow your solutions, there's more bits. Fred, we were commenting before we came on camera more bits than ever before and at the physics layer too, as well as the software. So you never know when there's going to be a zero-day vulnerability out there. It happens. We saw one with Fortinet this week. This came out of the woodwork. But moving fast on those patches, it's huge. This brings up the whole support angle. I wanted to ask you about how you guys are doing that as well, because to me, we see the value when we talk to customers on theCUBE about this. It was a real easy understanding of what the cloud means to them with VMware now with the AWS. But the question that comes up that we want to get more clarity on is how do you guys handle support together? >> Well, what's interesting about this is that it's done mutually. We have dedicated support teams on both sides that work together pretty seamlessly to make sure that whether there's a issue at any layer, including all the way up into the app layer, as you think about some of the other workloads like SAP, we'll go end-to-end and make sure that we support the customer regardless of where the particular issue might be for them. And on top of that, we look at where we're improving reliability in as a first order of principle between both companies. So from availability and reliability standpoint, it's top of mind and no matter where the particular item might land, we're going to go help the customer resolve that. It works really well. >> On the VMware side, what's been the feedback there? What are some of the updates? >> Yeah, I think, look, I mean, VMware owns and operates the service, but we work phenomenal backend relationship with AWS. Customers call VMware for the service or any issues. And then we have a awesome relationship with AWS on the backend for support issues or any hardware issues. The key management that we jointly do. All of the hard problems that customers don't have to worry about. I think on the front end, we also have a really good group of solution architects across the companies that help to really explain the solution, do complex things like cloud migration, which is much, much easier with the VMware Cloud in AWS. We're presenting that easy button to the public cloud in many ways. And so we have a whole technical audience across the two companies that are working with customers every single day. >> You had mentioned, I've got list here of some of the innovations. You mentioned the stretch clustering, getting the geos working, advanced network, Disaster Recovery, FedRAMP, public sector certifications, Outposts. All good, you guys are checking the boxes every year. You got a good accomplishments list there on the VMware AWS side here in this relationship. The question that I'm interested in is what's next? What recent innovations are you doing? Are you making investments in? What's on the list this year? What items will be next year? How do you see the new things, the list of accomplishments? People want to know what's next. They don't want to see stagnant growth here. They want to see more action as cloud continues to scale and modern applications cloud native. You're seeing more and more containers, more and more CI/CD pipelining with modern apps, put more pressure on the system. What's new? What's the new innovations? >> Absolutely. And I think as a five year old service offering, innovation is top of mind for us every single day. So just to call out a few recent innovations that we announced in San Francisco at VMware Explore. First of all, our new platform i4i.metal. It's isolate based. It's pretty awesome. It's the latest and greatest, all the speeds and feeds that we would expect from VMware and AWS at this point in our relationship. We announced two different storage options. This notion of working from customer feedback, allowing customers even more price reductions, really take off that storage and park it externally and separate that from compute. So two different storage offerings there. One is with AWS FSx with NetApp ONTAP, which brings in our NetApp partnership as well into the equation and really get that NetApp based really excited about this offering as well. And the second storage offering called VMware Cloud Flex Storage. VMware's own managed storage offering. Beyond that, we have done a lot of other innovations as well. I really wanted to talk about VMware Cloud Flex Compute where previously customers could only scale by hosts and a host is 36 to 48 cores, give or take. But with VMware Cloud Flex Compute, we are now allowing this notion of a resource defined compute model where customers can just get exactly the vCPU memory and storage that maps to the applications, however small they might be. So this notion of granularity is really a big innovation that we are launching in the market this year. And then last but not least, top of ransomware. Of course it's a hot topic in the industry. We are seeing many, many customers ask for this. We are happy to announce a new ransomware recovery with our VMware Cloud DR solution. A lot of innovation there and the way we are able to do machine learning and make sure the workloads that are covered from snapshots and backups are actually safe to use. So there's a lot of differentiation on that front as well. A lot of networking innovations with Project Northstar. Our ability to have layer four through layer seven, new SaaS services in that area as well. Keep in mind that the service already supports managed Kubernetes for containers. It's built in to the same clusters that have virtual machines. And so this notion of a single service with a great TCO for VMs and containers is sort at the heart of our (faintly speaking). >> The networking side certainly is a hot area to keep innovating on. Every year it's the same, same conversation, get better faster, networking more options there. The Flex Compute is interesting. If you don't mind me getting a quick clarification, could you explain the resource-defined versus hardware-defined? Because this is what we had saw at Explore coming out, that notion of resource-defined versus hardware-defined. What does that mean? >> Yeah, I mean I think we have been super successful in this hardware-defined notion. We we're scaling by the hardware unit that we present as software-defined data centers. And so that's been super successful. But customers wanted more, especially customers in different parts of the world wanted to start even smaller and grow even more incrementally. Lower the cost even more. And so this is the part where resource-defined starts to be very, very interesting as a way to think about, here's my bag of resources exactly based on what the customers request before fiber machines, five containers. It's size exactly for that. And then as utilization grows, we elastically behind the scenes, we're able to grow it through policies. So that's a whole different dimension. That's a whole different service offering that adds value and customers are comfortable. They can go from one to the other. They can go back to that host based model if they so choose to. And there's a jump off point across these two different economic models. >> It's cloud flexibility right there. I like the name. Fred, let's get into some of the examples of customers, if you don't mind, let's get into some of the, we have some time. I want to unpack a little bit of what's going on with the customer deployments. One of the things we've heard again on theCUBE is from customers is they like the clarity of the relationship, they love the cloud positioning of it. And then what happens is they lift and shift the workloads and it's like feels great. It's just like we're running VMware on AWS and then they start consuming higher level services. That adoption next level happens and because it's in the cloud. So can you guys take us through some recent examples of customer wins or deployments where they're using VMware cloud on AWS on getting started and then how do they progress once they're there? How does it evolve? Can you just walk us through a couple use cases? >> Sure. Well, there's a couple. One, it's pretty interesting that like you said, as there's more and more bits, you need better and better hardware and networking. And we're super excited about the i4 and the capabilities there in terms of doubling and or tripling what we're doing around lower variability on latency and just improving all the speeds. But what customers are doing with it, like the college in New Jersey, they're accelerating their deployment on onboarding over like 7,400 students over a six to eight month period. And they've really realized a ton of savings. But what's interesting is where and how they can actually grow onto additional native services too. So connectivity to any other services is available as they start to move and migrate into this. The options there obviously are tied to all the innovation that we have across any services, whether it's containerized and with what they're doing with Tanzu or with any other container and or services within AWS. So there's some pretty interesting scenarios where that data and or the processing, which is moved quickly with full compliance, whether it's in like healthcare or regulatory business is allowed to then consume and use things, for example, with Textract or any other really cool service that has monthly and quarterly innovations. So there's things that you just could not do before that are coming out and saving customers money and building innovative applications on top of their current app base in a rapid fashion. So pretty excited about it. There's a lot of examples. I think I probably don't have time to go into too many here. But that's actually the best part is listening to customers and seeing how many net new services and new applications are they actually building on top of this platform. >> Narayan, what's your perspective from the VMware side? 'Cause you guys have now a lot of headroom to offer customers with Amazon's higher level services and or whatever's homegrown where it's being rolled out 'cause you now have a lot of hybrid too. So what's your take on what's happening in with customers? >> I mean, it's been phenomenal. The customer adoption of this and banks and many other highly sensitive verticals are running production-grade applications, tier one applications on the service over the last five years. And so I have a couple of really good examples. S&P Global is one of my favorite examples. Large bank, they merge with IHS Markit, big conglomeration now. Both customers were using VMware Cloud and AWS in different ways. And with the use case, one of their use cases was how do I just respond to these global opportunities without having to invest in physical data centers? And then how do I migrate and consolidate all my data centers across the global, which there were many. And so one specific example for this company was how they migrated 1000 workloads to VMware Cloud and AWS in just six weeks. Pretty phenomenal if you think about everything that goes into a cloud migration process, people process technology. And the beauty of the technology going from VMware point A to VMware point B. The lowest cost, lowest risk approach to adopting VMware Cloud and AWS. So that's one of my favorite examples. There are many other examples across other verticals that we continue to see. The good thing is we are seeing rapid expansion across the globe, but constantly entering new markets with a limited number of regions and progressing our roadmap. >> It's great to see. I mean, the data center migrations go from months, many, many months to weeks. It's interesting to see some of those success stories. Congratulations. >> One of the other interesting fascinating benefits is the sustainability improvement in terms of being green. So the efficiency gains that we have both in current generation and new generation processors and everything that we're doing to make sure that when a customer can be elastic, they're also saving power, which is really critical in a lot of regions worldwide at this point in time. They're seeing those benefits. If you're running really inefficiently in your own data center, that is not a great use of power. So the actual calculators and the benefits to these workloads are pretty phenomenal just in being more green, which I like. We just all need to do our part there and this is a big part of it here. >> It's a huge point about the sustainability. Fred, I'm glad you called that out. The other one I would say is supply chain issue is another one. You see that constraints. I can't buy hardware. And the third one is really obvious, but no one really talks about it. It's security. I mean, I remember interviewing Steven Schmidt with that AWS and many years ago, this is like 2013 and at that time people were saying, the cloud's not secure. And he's like, listen, it's more secure in the cloud on-premise. And if you look at the security breaches, it's all about the on-premise data center vulnerabilities, not so much hardware. So there's a lot, the stay current on the isolation there is hard. So I think the security and supply chain, Fred, is another one. Do you agree? >> I absolutely agree. It's hard to manage supply chain nowadays. We put a lot of effort into that and I think we have a great ability to forecast and make sure that we can lean in and have the resources that are available and run them more efficiently. And then like you said on the security point, security is job one. It is the only P1. And if you think of how we build our infrastructure from Nitro all the way up and how we respond and work with our partners and our customers, there's nothing more important. >> And Narayan, your point earlier about the managed service patching and being on top of things is really going to get better. All right, final question. I really want to thank you for your time on this showcase. It's really been a great conversation. Fred, you had made a comment earlier. I want to end with a curve ball and put you eyes on the spot. We're talking about a new modern shift. We're seeing another inflection point. We've been documenting it. It's almost like cloud hitting another inflection point with application and open source growth significantly at the app layer. Continue to put a lot of pressure and innovation in the infrastructure side. So the question is for you guys each to answer is, what's the same and what's different in today's market? So it's like we want more of the same here, but also things have changed radically and better here. What's changed for the better and what's still the same thing hanging around that people are focused on? Can you share your perspective? >> I'll tackle it. Businesses are complex and they're often unique, that's the same. What's changed is how fast you can innovate. The ability to combine managed services and new innovative services and build new applications is so much faster today. Leveraging world class hardware that you don't have to worry about, that's elastic. You could not do that even five, 10 years ago to the degree you can today, especially with innovation. So innovation is accelerating at a rate that most people can't even comprehend and understand the set of services that are available to them. It's really fascinating to see what a one pizza team of engineers can go actually develop in a week. It is phenomenal. So super excited about this space and it's only going to continue to accelerate that. That's my take, Narayan. >> You got a lot of platform to compete on. With Amazon, you got a lot to build on. Narayan, your side. What's your answer to that question? >> I think we are seeing a lot of innovation with new applications that customers are constantly (faintly speaking). I think what we see is this whole notion of how do you go from desktop to production to the secure supply chain and how can we truly build on the agility that developers desire and build all the security and the pipelines to energize that production quickly and efficiently. I think we are seeing, we are at the very start of that sort of journey. Of course, we have invested in Kubernetes, the means to an end, but we're so much more beyond that's happening in industry and I think we're at the very, very beginning of this transformations, enterprise transformation that many of our customers are going through and we are inherently part of it. >> Well, gentlemen, I really appreciate that we're seeing the same thing. It's more the same here on solving these complexities with distractions, whether it's higher level services with large scale infrastructure. At your fingertips, infrastructure as code, infrastructure to be provisioned, serverless, all the good stuff happen and Fred with AWS on your side. And we're seeing customers resonate with this idea of being an operator again, being a cloud operator and developer. So the developer ops is kind of, DevOps is changing too. So all for the better. Thank you for spending the time and we're seeing again that traction with the VMware customer base and AWS getting along great together. So thanks for sharing your perspectives. >> We appreciate it. Thank you so much. >> Thank you John. >> This is theCUBE and AWS VMware showcase accelerating business transformation, VMware Cloud on AWS. Jointly engineered solution bringing innovation to the VMware customer base, going to the cloud and beyond. I'm John Furrier, your host. Thanks for watching. (gentle music)

>>Hi everyone. Welcome to the Cube special presentation here in Palo Alto, California. I'm John Foer, host of the Cube. We've got two great guests, one for calling in from Germany, our videoing in from Germany, one from Maryland. We've got VMware and aws. This is the customer successes with VMware cloud on AWS showcase, accelerating business transformation here in the showcase with Samir Candu Worldwide. VMware strategic alliance solution, architect leader with AWS Samir. Great to have you and Daniel Re Myer, principal architect global AWS synergy at VMware. Guys, you guys are, are working together. You're the key players in the re relationship as it rolls out and continues to grow. So welcome to the cube. >>Thank you. Greatly appreciate it. >>Great to have you guys both on, As you know, we've been covering this since 2016 when Pat Geling, then CEO and then then CEO AWS at Andy Chasy did this. It kind of got people by surprise, but it really kind of cleaned out the positioning in the enterprise for the success. OFM workloads in the cloud. VMware's had great success with it since, and you guys have the great partnerships. So this has been like a really strategic, successful partnership. Where are we right now? You know, years later we got this whole inflection point coming. You're starting to see, you know, this idea of higher level services, more performance are coming in at the infrastructure side. More automation, more serverless, I mean, and a, I mean it's just getting better and better every year in the cloud. Kinda a whole nother level. Where are we, Samir? Let's start with you on, on the relationship. >>Yeah, totally. So I mean, there's several things to keep in mind, right? So in 2016, right, that's when the partnership between AWS and VMware was announced, and then less than a year later, that's when we officially launched VMware cloud on aws. Years later, we've been driving innovation, working with our customers, jointly engineering this between AWS and VMware day in, day out. As far as advancing VMware cloud on aws. You know, even if you look at the innovation that takes place with a solution, things have modernized, things have changed, there's been advancements, you know, whether it's security focus, whether it's platform focus, whether it's networking focus, there's been modifications along the way, even storage, right? More recently, one of the things to keep in mind is we're looking to deliver value to our customers together. These are our joint customers. So there's hundreds of VMware and AWS engineers working together on this solution. >>And then factor in even our sales teams, right? We have VMware and AWS sales teams interacting with each other on a constant daily basis. We're working together with our customers at the end of the day too. Then we're looking to even offer and develop jointly engineered solutions specific to VMware cloud on aws, and even with VMware's, other platforms as well. Then the other thing comes down to is where we have dedicated teams around this at both AWS and VMware. So even from solutions architects, even to our sales specialists, even to our account teams, even to specific engineering teams within the organizations, they all come together to drive this innovation forward with VMware cloud on AWS and the jointly engineered solution partnership as well. And then I think one of the key things to keep in mind comes down to we have nearly 600 channel partners that have achieved VMware cloud on AWS service competency. So think about it from the standpoint there's 300 certified or validated technology solutions, they're now available to our customers. So that's even innovation right off the top as well. >>Great stuff. Daniel, I wanna get to you in a second. Upon this principal architect position you have in your title, you're the global a synergy person. Synergy means bringing things together, making it work. Take us through the architecture, because we heard a lot of folks at VMware explore this year, formerly world, talking about how the, the workloads on it has been completely transforming into cloud and hybrid, right? This is where the action is. Where are you? Is your customers taking advantage of that new shift? You got AI ops, you got it. Ops changing a lot, you got a lot more automation edges right around the corner. This is like a complete transformation from where we were just five years ago. What's your thoughts on the >>Relationship? So at at, at first, I would like to emphasize that our collaboration is not just that we have dedicated teams to help our customers get the most and the best benefits out of VMware cloud on aws. We are also enabling US mutually. So AWS learns from us about the VMware technology, where VMware people learn about the AWS technology. We are also enabling our channel partners and we are working together on customer projects. So we have regular assembled globally and also virtually on Slack and the usual suspect tools working together and listening to customers, that's, that's very important. Asking our customers where are their needs? And we are driving the solution into the direction that our customers get the, the best benefits out of VMware cloud on aws. And over the time we, we really have involved the solution. As Samia mentioned, we just added additional storage solutions to VMware cloud on aws. We now have three different instance types that cover a broad range of, of workload. So for example, we just added the I four I host, which is ideally for workloads that require a lot of CPU power, such as you mentioned it, AI workloads. >>Yeah. So I wanna guess just specifically on the customer journey and their transformation. You know, we've been reporting on Silicon angle in the queue in the past couple weeks in a big way that the OPS teams are now the new devs, right? I mean that sounds OP a little bit weird, but operation IT operations is now part of the, a lot more data ops, security writing code composing, you know, with open source, a lot of great things are changing. Can you share specifically what customers are looking for when you say, as you guys come in and assess their needs, what are they doing? What are some of the things that they're doing with VMware on AWS specifically that's a little bit different? Can you share some of and highlights there? >>That, that's a great point because originally VMware and AWS came from very different directions when it comes to speaking people at customers. So for example, aws very developer focused, whereas VMware has a very great footprint in the IT ops area. And usually these are very different, very different teams, groups, different cultures, but it's, it's getting together. However, we always try to address the customers, right? There are customers that want to build up a new application from the scratch and build resiliency, availability, recoverability, scalability into the application. But there are still a lot of customers that say, well we don't have all of the skills to redevelop everything to refactor an application to make it highly available. So we want to have all of that as a service, recoverability as a service, scalability as a service. We want to have this from the infrastructure. That was one of the unique selling points for VMware on premise and now we are bringing this into the cloud. >>Samir, talk about your perspective. I wanna get your thoughts, and not to take a tangent, but we had covered the AWS remar of, actually it was Amazon res machine learning automation, robotics and space. It was really kinda the confluence of industrial IOT software physical. And so when you look at like the IT operations piece becoming more software, you're seeing things about automation, but the skill gap is huge. So you're seeing low code, no code automation, you know, Hey Alexa, deploy a Kubernetes cluster. Yeah, I mean, I mean that's coming, right? So we're seeing this kind of operating automation meets higher level services meets workloads. Can you unpack that and share your opinion on, on what you see there from an Amazon perspective and how it relates to this? >>Yeah, totally. Right. And you know, look at it from the point of view where we said this is a jointly engineered solution, but it's not migrating to one option or the other option, right? It's more or less together. So even with VMware cloud on aws, yes it is utilizing AWS infrastructure, but your environment is connected to that AWS VPC in your AWS account. So if you wanna leverage any of the native AWS services, so any of the 200 plus AWS services, you have that option to do so. So that's gonna give you that power to do certain things, such as, for example, like how you mentioned with iot, even with utilizing Alexa or if there's any other service that you wanna utilize, that's the joining point between both of the offerings. Right off the top though, with digital transformation, right? You, you have to think about where it's not just about the technology, right? There's also where you want to drive growth in the underlying technology. Even in your business leaders are looking to reinvent their business. They're looking to take different steps as far as pursuing a new strategy. Maybe it's a process, maybe it's with the people, the culture, like how you said before, where people are coming in from a different background, right? They may not be used to the cloud, they may not be used to AWS services, but now you have that capability to mesh them together. Okay. Then also, Oh, >>Go ahead, finish >>Your thought. No, no, I was gonna say, what it also comes down to is you need to think about the operating model too, where it is a shift, right? Especially for that VS four admin that's used to their on-premises at environment. Now with VMware cloud on aws, you have that ability to leverage a cloud, but the investment that you made and certain things as far as automation, even with monitoring, even with logging, yeah. You still have that methodology where you can utilize that in VMware cloud on AWS two. >>Danielle, I wanna get your thoughts on this because at at explore and, and, and after the event, now as we prep for Cuban and reinvent coming up the big AWS show, I had a couple conversations with a lot of the VMware customers and operators and it's like hundreds of thousands of, of, of, of users and millions of people talking about and and peaked on VM we're interested in v VMware. The common thread was one's one, one person said, I'm trying to figure out where I'm gonna put my career in the next 10 to 15 years. And they've been very comfortable with VMware in the past, very loyal, and they're kind of talking about, I'm gonna be the next cloud, but there's no like role yet architects, is it Solution architect sre. So you're starting to see the psychology of the operators who now are gonna try to make these career decisions, like how, what am I gonna work on? And it's, and that was kind of fuzzy, but I wanna get your thoughts. How would you talk to that persona about the future of VMware on, say, cloud for instance? What should they be thinking about? What's the opportunity and what's gonna happen? >>So digital transformation definitely is a huge change for many organizations and leaders are perfectly aware of what that means. And that also means in, in to to some extent, concerns with your existing employees. Concerns about do I have to relearn everything? Do I have to acquire new skills? And, and trainings is everything worthless I learned over the last 15 years of my career? And the, the answer is to make digital transformation a success. We need not just to talk about technology, but also about process people and culture. And this is where VMware really can help because if you are applying VMware cloud on a, on AWS to your infrastructure, to your existing on-premise infrastructure, you do not need to change many things. You can use the same tools and skills, you can manage your virtual machines as you did in your on-premise environment. You can use the same managing and monitoring tools. If you have written, and many customers did this, if you have developed hundreds of, of scripts that automate tasks and if you know how to troubleshoot things, then you can use all of that in VMware cloud on aws. And that gives not just leaders, but but also the architects at customers, the operators at customers, the confidence in, in such a complex project, >>The consistency, very key point, gives them the confidence to go and, and then now that once they're confident they can start committing themselves to new things. Samir, you're reacting to this because you know, on your side you've got higher level services, you got more performance at the hardware level. I mean, lot improvement. So, okay, nothing's changed. I can still run my job now I got goodness on the other side. What's the upside? What's in it for the, for the, for the customer there? >>Yeah, so I think what it comes down to is they've already been so used to or entrenched with that VMware admin mentality, right? But now extending that to the cloud, that's where now you have that bridge between VMware cloud on AWS to bridge that VMware knowledge with that AWS knowledge. So I will look at it from the point of view where now one has that capability and that ability to just learn about the cloud, but if they're comfortable with certain aspects, no one's saying you have to change anything. You can still leverage that, right? But now if you wanna utilize any other AWS service in conjunction with that VM that resides maybe on premises or even in VMware cloud on aws, you have that option to do so. So think about it where you have that ability to be someone who's curious and wants to learn. And then if you wanna expand on the skills, you certainly have that capability to do so. >>Great stuff. I love, love that. Now that we're peeking behind the curtain here, I'd love to have you guys explain, cuz people wanna know what's goes on in behind the scenes. How does innovation get happen? How does it happen with the relationship? Can you take us through a day in the life of kind of what goes on to make innovation happen with the joint partnership? You guys just have a zoom meeting, Do you guys fly out, you write go do you ship thing? I mean I'm making it up, but you get the idea, what's the, what's, how does it work? What's going on behind the scenes? >>So we hope to get more frequently together in person, but of course we had some difficulties over the last two to three years. So we are very used to zoom conferences and and Slack meetings. You always have to have the time difference in mind if we are working globally together. But what we try, for example, we have reg regular assembled now also in person geo based. So for emia, for the Americas, for aj. And we are bringing up interesting customer situations, architectural bits and pieces together. We are discussing it always to share and to contribute to our community. >>What's interesting, you know, as, as events are coming back to here, before you get, you weigh in, I'll comment, as the cube's been going back out to events, we are hearing comments like what, what pandemic we were more productive in the pandemic. I mean, developers know how to work remotely and they've been on all the tools there, but then they get in person, they're happy to see people, but there's no one's, no one's really missed the beat. I mean it seems to be very productive, you know, workflow, not a lot of disruption. More if anything, productivity gains. >>Agreed, right? I think one of the key things to keep in mind is, you know, even if you look at AWS's and even Amazon's leadership principles, right? Customer obsession, that's key. VMware is carrying that forward as well. Where we are working with our customers, like how Daniel said met earlier, right? We might have meetings at different time zones, maybe it's in person, maybe it's virtual, but together we're working to listen to our customers. You know, we're taking and capturing that feedback to drive innovation and VMware cloud on AWS as well. But one of the key things to keep in mind is yes, there have been, there has been the pandemic, we might have been disconnected to a certain extent, but together through technology we've been able to still communicate work with our customers. Even with VMware in between, with AWS and whatnot. We had that flexibility to innovate and continue that innovation. So even if you look at it from the point of view, right? VMware cloud on AWS outposts, that was something that customers have been asking for. We've been been able to leverage the feedback and then continue to drive innovation even around VMware cloud on AWS outposts. So even with the on premises environment, if you're looking to handle maybe data sovereignty or compliance needs, maybe you have low latency requirements, that's where certain advancements come into play, right? So the key thing is always to maintain that communication track. >>And our last segment we did here on the, on this showcase, we listed the accomplishments and they were pretty significant. I mean go, you got the global rollouts of the relationship. It's just really been interesting and, and people can reference that. We won't get into it here, but I will ask you guys to comment on, as you guys continue to evolve the relationship, what's in it for the customer? What can they expect next? Cuz again, I think right now we're in at a, an inflection point more than ever. What can people expect from the relationship and what's coming up with reinvent? Can you share a little bit of kind of what's coming down the pike? >>So one of the most important things we have announced this year, and we will continue to evolve into that direction, is independent scale of storage. That absolutely was one of the most important items customer asked us for over the last years. Whenever, whenever you are requiring additional storage to host your virtual machines, you usually in VMware cloud on aws, you have to add additional notes. Now we have three different note types with different ratios of compute, storage and memory. But if you only require additional storage, you always have to get also additional compute and memory and you have to pay. And now with two solutions which offer choice for the customers, like FS six one, NetApp onap, and VMware cloud Flex Storage, you now have two cost effective opportunities to add storage to your virtual machines. And that offers opportunities for other instance types maybe that don't have local storage. We are also very, very keen looking forward to announcements, exciting announcements at the upcoming events. >>Samir, what's your, what's your reaction take on the, on what's coming down on your side? >>Yeah, I think one of the key things to keep in mind is, you know, we're looking to help our customers be agile and even scale with their needs, right? So with VMware cloud on aws, that's one of the key things that comes to mind, right? There are gonna be announcements, innovations and whatnot with outcoming events. But together we're able to leverage that to advance VMware cloud on AWS to Daniel's point storage, for example, even with host offerings. And then even with decoupling storage from compute and memory, right now you have the flexibility where you can do all of that. So to look at it from the standpoint where now with 21 regions where we have VMware cloud on AWS available as well, where customers can utilize that as needed when needed, right? So it comes down to, you know, transformation will be there. Yes, there's gonna be maybe where workloads have to be adapted where they're utilizing certain AWS services, but you have that flexibility and option to do so. And I think with the continuing events that's gonna give us the options to even advance our own services together. >>Well you guys are in the middle of it, you're in the trenches, you're making things happen, you've got a team of people working together. My final question is really more of a kind of a current situation, kind of future evolutionary thing that you haven't seen this before. I wanna get both of your reaction to it. And we've been bringing this up in, in the open conversations on the cube is in the old days it was going back this generation, you had ecosystems, you had VMware had an ecosystem they did best, had an ecosystem. You know, we have a product, you have a product, biz dev deals happen, people sign relationships and they do business together and they, they sell to each other's products or do some stuff. Now it's more about architecture cuz we're now in a distributed large scale environment where the role of ecosystems are intertwining. >>And this, you guys are in the middle of two big ecosystems. You mentioned channel partners, you both have a lot of partners on both sides. They come together. So you have this now almost a three dimensional or multidimensional ecosystem, you know, interplay. What's your thoughts on this? And, and, and because it's about the architecture, integration is a value, not so much. Innovation is only, you gotta do innovation, but when you do innovation, you gotta integrate it, you gotta connect it. So what is, how do you guys see this as a, as an architectural thing, start to see more technical business deals? >>So we are, we are removing dependencies from individual ecosystems and from individual vendors. So a customer no longer has to decide for one vendor and then it is a very expensive and high effort project to move away from that vendor, which ties customers even, even closer to specific vendors. We are removing these obstacles. So with VMware cloud on aws moving to the cloud, firstly it's, it's not a dead end. If you decide at one point in time because of latency requirements or maybe it's some compliance requirements, you need to move back into on-premise. You can do this if you decide you want to stay with some of your services on premise and just run a couple of dedicated services in the cloud, you can do this and you can mana manage it through a single pane of glass. That's quite important. So cloud is no longer a dead and it's no longer a binary decision, whether it's on premise or the cloud. It it is the cloud. And the second thing is you can choose the best of both works, right? If you are migrating virtual machines that have been running in your on-premise environment to VMware cloud on aws, by the way, in a very, very fast cost effective and safe way, then you can enrich later on enrich these virtual machines with services that are offered by aws. More than 200 different services ranging from object based storage, load balancing and so on. So it's an endless, endless possibility. >>We, we call that super cloud in, in a, in a way that we be generically defining it where everyone's innovating, but yet there's some common services. But the differentiation comes from innovation where the lock in is the value, not some spec, right? Samir, this is gonna where cloud is right now, you guys are, are not commodity. Amazon's completely differentiating, but there's some commodity things. Having got storage, you got compute, but then you got now advances in all areas. But partners innovate with you on their terms. Absolutely. And everybody wins. >>Yeah. And a hundred percent agree with you. I think one of the key things, you know, as Daniel mentioned before, is where it it, it's a cross education where there might be someone who's more proficient on the cloud side with aws, maybe more proficient with the viewers technology, but then for partners, right? They bridge that gap as well where they come in and they might have a specific niche or expertise where their background, where they can help our customers go through that transformation. So then that comes down to, hey, maybe I don't know how to connect to the cloud. Maybe I don't know what the networking constructs are. Maybe I can leverage that partner. That's one aspect to go about it. Now maybe you migrated that workload to VMware cloud on aws. Maybe you wanna leverage any of the native AWS services or even just off the top 200 plus AWS services, right? But it comes down to that skill, right? So again, solutions architecture at the back of, back of the day, end of the day, what it comes down to is being able to utilize the best of both worlds. That's what we're giving our customers at the end of the >>Day. I mean, I just think it's, it's a, it's a refactoring and innovation opportunity at all levels. I think now more than ever, you can take advantage of each other's ecosystems and partners and technologies and change how things get done with keeping the consistency. I mean, Daniel, you nailed that, right? I mean, you don't have to do anything. You still run the fear, the way you working on it and now do new things. This is kind of a cultural shift. >>Yeah, absolutely. And if, if you look, not every, not every customer, not every organization has the resources to refactor and re-platform everything. And we gave, we give them a very simple and easy way to move workloads to the cloud. Simply run them and at the same time they can free up resources to develop new innovations and, and grow their business. >>Awesome. Samir, thank you for coming on. Danielle, thank you for coming to Germany, Octoberfest, I know it's evening over there, your weekend's here. And thank you for spending the time. Samir final give you the final word, AWS reinvents coming up. Preparing. We're gonna have an exclusive with Adam, but Fry, we do a curtain raise, a dual preview. What's coming down on your side with the relationship and what can we expect to hear about what you got going on at reinvent this year? The big show? >>Yeah, so I think, you know, Daniel hit upon some of the key points, but what I will say is we do have, for example, specific sessions, both that VMware's driving and then also that AWS is driving. We do have even where we have what I call a chalk talks. So I would say, and then even with workshops, right? So even with the customers, the attendees who are there, whatnot, if they're looking for to sit and listen to a session, yes that's there. But if they wanna be hands on, that is also there too. So personally for me as an IT background, you know, been in CIS admin world and whatnot, being hands on, that's one of the key things that I personally am looking forward. But I think that's one of the key ways just to learn and get familiar with the technology. Yeah, >>Reinvents an amazing show for the in person. You guys nail it every year. We'll have three sets this year at the cube. It's becoming popular. We more and more content. You guys got live streams going on, a lot of content, a lot of media, so thanks, thanks for sharing that. Samir Daniel, thank you for coming on on this part of the showcase episode of really the customer successes with VMware Cloud Ons, really accelerating business transformation withs and VMware. I'm John Fur with the cube, thanks for watching. Hello everyone. Welcome to this cube showcase, accelerating business transformation with VMware cloud on it's a solution innovation conversation with two great guests, Fred and VP of commercial services at aws and NA Ryan Bard, who's the VP and general manager of cloud solutions at VMware. Gentlemen, thanks for joining me on this showcase. >>Great to be here. >>Hey, thanks for having us on. It's a great topic. You know, we, we've been covering this VMware cloud on abus since, since the launch going back and it's been amazing to watch the evolution from people saying, Oh, it's the worst thing I've ever seen. It's what's this mean? And depress work were, we're kind of not really on board with kind of the vision, but as it played out as you guys had announced together, it did work out great for VMware. It did work out great for a D and it continues two years later and I want just get an update from you guys on where you guys see this has been going. I'll see multiple years. Where is the evolution of the solution as we are right now coming off VMware explorer just recently and going in to reinvent, which is only a couple weeks away, feels like tomorrow. But you know, as we prepare a lot going on, where are we with the evolution of the solution? >>I mean, first thing I wanna say is, you know, PBO 2016 was a someon moment and the history of it, right? When Pat Gelsinger and Andy Jessey came together to announce this and I think John, you were there at the time I was there, it was a great, great moment. We launched the solution in 2017, the year after that at VM Word back when we called it Word, I think we have gone from strength to strength. One of the things that has really mattered to us is we have learned froms also in the processes, this notion of working backwards. So we really, really focused on customer feedback as we build a service offering now five years old, pretty remarkable journey. You know, in the first years we tried to get across all the regions, you know, that was a big focus because there was so much demand for it. >>In the second year we started going really on enterprise grade features. We invented this pretty awesome feature called Stretch clusters, where you could stretch a vSphere cluster using VSA and NSX across two AZs in the same region. Pretty phenomenal four nine s availability that applications start started to get with that particular feature. And we kept moving forward all kinds of integration with AWS direct connect transit gateways with our own advanced networking capabilities. You know, along the way, disaster recovery, we punched out two, two new services just focused on that. And then more recently we launched our outposts partnership. We were up on stage at Reinvent, again with Pat Andy announcing AWS outposts and the VMware flavor of that VMware cloud and AWS outposts. I think it's been significant growth in our federal sector as well with our federal and high certification more recently. So all in all, we are super excited. We're five years old. The customer momentum is really, really strong and we are scaling the service massively across all geos and industries. >>That's great, great update. And I think one of the things that you mentioned was how the advantages you guys got from that relationship. And, and this has kind of been the theme for AWS since I can remember from day one. Fred, you guys do the heavy lifting as as, as you always say for the customers here, VMware comes on board, takes advantage of the AWS and kind of just doesn't miss a beat, continues to move their workloads that everyone's using, you know, vSphere and these are, these are big workloads on aws. What's the AWS perspective on this? How do you see it? >>Yeah, it's pretty fascinating to watch how fast customers can actually transform and move when you take the, the skill set that they're familiar with and the advanced capabilities that they've been using on Preem and then overlay it on top of the AWS infrastructure that's, that's evolving quickly and, and building out new hardware and new instances we'll talk about. But that combined experience between both of us on a jointly engineered solution to bring the best security and the best features that really matter for those workloads drive a lot of efficiency and speed for the, for the customer. So it's been well received and the partnership is stronger than ever from an engineering standpoint, from a business standpoint. And obviously it's been very interesting to look at just how we stay day one in terms of looking at new features and work and, and responding to what customers want. So pretty, pretty excited about just seeing the transformation and the speed that which customers can move to bmc. Yeah, >>That's what great value publish. We've been talking about that in context too. Anyone building on top of the cloud, they can have their own supercloud as we call it. If you take advantage of all the CapEx and and investment Amazon's made and AWS has made and, and and continues to make in performance IAS and pass all great stuff. I have to ask you guys both as you guys see this going to the next level, what are some of the differentiations you see around the service compared to other options on the market? What makes it different? What's the combination? You mentioned jointly engineered, what are some of the key differentiators of the service compared to others? >>Yeah, I think one of the key things Fred talked about is this jointly engineered notion right from day one. We were the earlier doctors of AWS Nitro platform, right? The reinvention of E two back five years ago. And so we have been, you know, having a very, very strong engineering partnership at that level. I think from a VMware customer standpoint, you get the full software defined data center or compute storage networking on EC two, bare metal across all regions. You can scale that elastically up and down. It's pretty phenomenal just having that consistency globally, right on aws EC two global regions. Now the other thing that's a real differentiator for us that customers tell us about is this whole notion of a managed service, right? And this was somewhat new to VMware, but we took away the pain of this undifferentiated heavy lifting where customers had to provision rack, stack hardware, configure the software on top, and then upgrade the software and the security batches on top. >>So we took, took away all of that pain as customers transitioned to VMware cloud and aws. In fact, my favorite story from last year when we were all going through the lock for j debacle industry was just going through that, right? Favorite proof point from customers was before they put even race this issue to us, we sent them a notification saying we already patched all of your systems, no action from you. The customers were super thrilled. I mean these are large banks, many other customers around the world, super thrilled they had to take no action, but a pretty incredible industry challenge that we were all facing. >>Nora, that's a great, so that's a great point. You know, the whole managed service piece brings up the security, you kind of teasing at it, but you know, there's always vulnerabilities that emerge when you are doing complex logic. And as you grow your solutions, there's more bits. You know, Fred, we were commenting before we came on camera, there's more bits than ever before and, and at at the physics layer too, as well as the software. So you never know when there's gonna be a zero day vulnerability out there. Just, it happens. We saw one with fornet this week, this came outta the woodwork. But moving fast on those patches, it's huge. This brings up the whole support angle. I wanted to ask you about how you guys are doing that as well, because to me we see the value when we, when we talk to customers on the cube about this, you know, it was a real, real easy understanding of how, what the cloud means to them with VMware now with the aws. But the question that comes up that we wanna get more clarity on is how do you guys handle support together? >>Well, what's interesting about this is that it's, it's done mutually. We have dedicated support teams on both sides that work together pretty seamlessly to make sure that whether there's a issue at any layer, including all the way up into the app layer, as you think about some of the other workloads like sap, we'll go end to end and make sure that we support the customer regardless of where the particular issue might be for them. And on top of that, we look at where, where we're improving reliability in, in as a first order of, of principle between both companies. So from an availability and reliability standpoint, it's, it's top of mind and no matter where the particular item might land, we're gonna go help the customer resolve. That works really well >>On the VMware side. What's been the feedback there? What's the, what are some of the updates? >>Yeah, I think, look, I mean, VMware owns and operates the service, but we have a phenomenal backend relationship with aws. Customers call VMware for the service for any issues and, and then we have a awesome relationship with AWS on the backend for support issues or any hardware issues. The BASKE management that we jointly do, right? All of the hard problems that customers don't have to worry about. I think on the front end, we also have a really good group of solution architects across the companies that help to really explain the solution. Do complex things like cloud migration, which is much, much easier with VMware cloud aws, you know, we are presenting that easy button to the public cloud in many ways. And so we have a whole technical audience across the two companies that are working with customers every single day. >>You know, you had mentioned, I've got a list here, some of the innovations the, you mentioned the stretch clustering, you know, getting the GOs working, Advanced network, disaster recovery, you know, fed, Fed ramp, public sector certifications, outposts, all good. You guys are checking the boxes every year. You got a good, good accomplishments list there on the VMware AWS side here in this relationship. The question that I'm interested in is what's next? What recent innovations are you doing? Are you making investments in what's on the lists this year? What items will be next year? How do you see the, the new things, the list of accomplishments, people wanna know what's next. They don't wanna see stagnant growth here, they wanna see more action, you know, as as cloud kind of continues to scale and modern applications cloud native, you're seeing more and more containers, more and more, you know, more CF C I C D pipe pipelining with with modern apps, put more pressure on the system. What's new, what's the new innovations? >>Absolutely. And I think as a five yearold service offering innovation is top of mind for us every single day. So just to call out a few recent innovations that we announced in San Francisco at VMware Explorer. First of all, our new platform i four I dot metal, it's isolate based, it's pretty awesome. It's the latest and greatest, all the speeds and feeds that we would expect from VMware and aws. At this point in our relationship. We announced two different storage options. This notion of working from customer feedback, allowing customers even more price reductions, really take off that storage and park it externally, right? And you know, separate that from compute. So two different storage offerings there. One is with AWS Fsx, with NetApp on tap, which brings in our NetApp partnership as well into the equation and really get that NetApp based, really excited about this offering as well. >>And the second storage offering for VMware cloud Flex Storage, VMware's own managed storage offering. Beyond that, we have done a lot of other innovations as well. I really wanted to talk about VMware cloud Flex Compute, where previously customers could only scale by hosts and a host is 36 to 48 cores, give or take. But with VMware cloud Flex Compute, we are now allowing this notion of a resource defined compute model where customers can just get exactly the V C P memory and storage that maps to the applications, however small they might be. So this notion of granularity is really a big innovation that that we are launching in the market this year. And then last but not least, talk about ransomware. Of course it's a hot topic in industry. We are seeing many, many customers ask for this. We are happy to announce a new ransomware recovery with our VMware cloud DR solution. >>A lot of innovation there and the way we are able to do machine learning and make sure the workloads that are covered from snapshots and backups are actually safe to use. So there's a lot of differentiation on that front as well. A lot of networking innovations with Project Knot star for ability to have layer flow through layer seven, you know, new SaaS services in that area as well. Keep in mind that the service already supports managed Kubernetes for containers. It's built in to the same clusters that have virtual machines. And so this notion of a single service with a great TCO for VMs and containers and sort of at the heart of our office, >>The networking side certainly is a hot area to keep innovating on. Every year it's the same, same conversation, get better, faster networking, more, more options there. The flex computes. Interesting. If you don't mind me getting a quick clarification, could you explain the Drew screen resource defined versus hardware defined? Because this is kind of what we had saw at Explore coming out, that notion of resource defined versus hardware defined. What's the, what does that mean? >>Yeah, I mean I think we have been super successful in this hardware defined notion. We we're scaling by the hardware unit that we present as software defined data centers, right? And so that's been super successful. But we, you know, customers wanted more, especially customers in different parts of the world wanted to start even smaller and grow even more incrementally, right? Lower their costs even more. And so this is the part where resource defined starts to be very, very interesting as a way to think about, you know, here's my bag of resources exactly based on what the customers request for fiber machines, five containers, its size exactly for that. And then as utilization grows, we elastically behind the scenes, we're able to grow it through policies. So that's a whole different dimension. It's a whole different service offering that adds value and customers are comfortable. They can go from one to the other, they can go back to that post based model if they so choose to. And there's a jump off point across these two different economic models. >>It's kind of cloud of flexibility right there. I like the name Fred. Let's get into some of the examples of customers, if you don't mind. Let's get into some of the ex, we have some time. I wanna unpack a little bit of what's going on with the customer deployments. One of the things we've heard again on the cube is from customers is they like the clarity of the relationship, they love the cloud positioning of it. And then what happens is they lift and shift the workloads and it's like, feels great. It's just like we're running VMware on AWS and then they would start consuming higher level services, kind of that adoption next level happens and because it it's in the cloud, so, So can you guys take us through some recent examples of customer wins or deployments where they're using VMware cloud on AWS on getting started, and then how do they progress once they're there? How does it evolve? Can you just walk us through a couple of use cases? >>Sure. There's a, well there's a couple. One, it's pretty interesting that, you know, like you said, as there's more and more bits you need better and better hardware and networking. And we're super excited about the I four and the capabilities there in terms of doubling and or tripling what we're doing around a lower variability on latency and just improving all the speeds. But what customers are doing with it, like the college in New Jersey, they're accelerating their deployment on a, on onboarding over like 7,400 students over a six to eight month period. And they've really realized a ton of savings. But what's interesting is where and how they can actually grow onto additional native services too. So connectivity to any other services is available as they start to move and migrate into this. The, the options there obviously are tied to all the innovation that we have across any services, whether it's containerized and with what they're doing with Tanu or with any other container and or services within aws. >>So there's, there's some pretty interesting scenarios where that data and or the processing, which is moved quickly with full compliance, whether it's in like healthcare or regulatory business is, is allowed to then consume and use things, for example, with tech extract or any other really cool service that has, you know, monthly and quarterly innovations. So there's things that you just can't, could not do before that are coming out and saving customers money and building innovative applications on top of their, their current app base in, in a rapid fashion. So pretty excited about it. There's a lot of examples. I think I probably don't have time to go into too, too many here. Yeah. But that's actually the best part is listening to customers and seeing how many net new services and new applications are they actually building on top of this platform. >>Nora, what's your perspective from the VMware sy? So, you know, you guys have now a lot of headroom to offer customers with Amazon's, you know, higher level services and or whatever's homegrown where's being rolled out? Cuz you now have a lot of hybrid too, so, so what's your, what's your take on what, what's happening in with customers? >>I mean, it's been phenomenal, the, the customer adoption of this and you know, banks and many other highly sensitive verticals are running production grade applications, tier one applications on the service over the last five years. And so, you know, I have a couple of really good examples. S and p Global is one of my favorite examples. Large bank, they merge with IHS market, big sort of conglomeration. Now both customers were using VMware cloud and AWS in different ways. And with the, with the use case, one of their use cases was how do I just respond to these global opportunities without having to invest in physical data centers? And then how do I migrate and consolidate all my data centers across the global, which there were many. And so one specific example for this company was how they migrated thousand 1000 workloads to VMware cloud AWS in just six weeks. Pretty phenomenal. If you think about everything that goes into a cloud migration process, people process technology and the beauty of the technology going from VMware point A to VMware point B, the the lowest cost, lowest risk approach to adopting VMware, VMware cloud, and aws. So that's, you know, one of my favorite examples. There are many other examples across other verticals that we continue to see. The good thing is we are seeing rapid expansion across the globe that constantly entering new markets with the limited number of regions and progressing our roadmap there. >>Yeah, it's great to see, I mean the data center migrations go from months, many, many months to weeks. It's interesting to see some of those success stories. So congratulations. One >>Of other, one of the other interesting fascinating benefits is the sustainability improvement in terms of being green. So the efficiency gains that we have both in current generation and new generation processors and everything that we're doing to make sure that when a customer can be elastic, they're also saving power, which is really critical in a lot of regions worldwide at this point in time. They're, they're seeing those benefits. If you're running really inefficiently in your own data center, that is just a, not a great use of power. So the actual calculators and the benefits to these workloads is, are pretty phenomenal just in being more green, which I like. We just all need to do our part there. And, and this is a big part of it here. >>It's a huge, it's a huge point about the sustainability. Fred, I'm glad you called that out. The other one I would say is supply chain issues. Another one you see that constrains, I can't buy hardware. And the third one is really obvious, but no one really talks about it. It's security, right? I mean, I remember interviewing Stephen Schmidt with that AWS and many years ago, this is like 2013, and you know, at that time people were saying the cloud's not secure. And he's like, listen, it's more secure in the cloud on premise. And if you look at the security breaches, it's all about the on-premise data center vulnerabilities, not so much hardware. So there's a lot you gotta to stay current on, on the isolation there is is hard. So I think, I think the security and supply chain, Fred is, is another one. Do you agree? >>I I absolutely agree. It's, it's hard to manage supply chain nowadays. We put a lot of effort into that and I think we have a great ability to forecast and make sure that we can lean in and, and have the resources that are available and run them, run them more efficiently. Yeah, and then like you said on the security point, security is job one. It is, it is the only P one. And if you think of how we build our infrastructure from Nitro all the way up and how we respond and work with our partners and our customers, there's nothing more important. >>And naron your point earlier about the managed service patching and being on top of things, it's really gonna get better. All right, final question. I really wanna thank you for your time on this showcase. It's really been a great conversation. Fred, you had made a comment earlier. I wanna kind of end with kind of a curve ball and put you eyes on the spot. We're talking about a modern, a new modern shift. It's another, we're seeing another inflection point, we've been documenting it, it's almost like cloud hitting another inflection point with application and open source growth significantly at the app layer. Continue to put a lot of pressure and, and innovation in the infrastructure side. So the question is for you guys each to answer is what's the same and what's different in today's market? So it's kind of like we want more of the same here, but also things have changed radically and better here. What are the, what's, what's changed for the better and where, what's still the same kind of thing hanging around that people are focused on? Can you share your perspective? >>I'll, I'll, I'll, I'll tackle it. You know, businesses are complex and they're often unique that that's the same. What's changed is how fast you can innovate. The ability to combine manage services and new innovative services and build new applications is so much faster today. Leveraging world class hardware that you don't have to worry about that's elastic. You, you could not do that even five, 10 years ago to the degree you can today, especially with innovation. So innovation is accelerating at a, at a rate that most people can't even comprehend and understand the, the set of services that are available to them. It's really fascinating to see what a one pizza team of of engineers can go actually develop in a week. It is phenomenal. So super excited about this space and it's only gonna continue to accelerate that. That's my take. All right. >>You got a lot of platform to compete on with, got a lot to build on then you're Ryan, your side, What's your, what's your answer to that question? >>I think we are seeing a lot of innovation with new applications that customers are constant. I think what we see is this whole notion of how do you go from desktop to production to the secure supply chain and how can we truly, you know, build on the agility that developers desire and build all the security and the pipelines to energize that motor production quickly and efficiently. I think we, we are seeing, you know, we are at the very start of that sort of of journey. Of course we have invested in Kubernetes the means to an end, but there's so much more beyond that's happening in industry. And I think we're at the very, very beginning of this transformations, enterprise transformation that many of our customers are going through and we are inherently part of it. >>Yeah. Well gentlemen, I really appreciate that we're seeing the same thing. It's more the same here on, you know, solving these complexities with distractions. Whether it's, you know, higher level services with large scale infrastructure at, at your fingertips. Infrastructures, code, infrastructure to be provisioned, serverless, all the good stuff happen in Fred with AWS on your side. And we're seeing customers resonate with this idea of being an operator, again, being a cloud operator and developer. So the developer ops is kind of, DevOps is kind of changing too. So all for the better. Thank you for spending the time and we're seeing again, that traction with the VMware customer base and of us getting, getting along great together. So thanks for sharing your perspectives, >>I appreciate it. Thank you so >>Much. Okay, thank you John. Okay, this is the Cube and AWS VMware showcase, accelerating business transformation. VMware cloud on aws, jointly engineered solution, bringing innovation to the VMware customer base, going to the cloud and beyond. I'm John Fur, your host. Thanks for watching. Hello everyone. Welcome to the special cube presentation of accelerating business transformation on vmc on aws. I'm John Furrier, host of the Cube. We have dawan director of global sales and go to market for VMware cloud on adb. This is a great showcase and should be a lot of fun. Ashish, thanks for coming on. >>Hi John. Thank you so much. >>So VMware cloud on AWS has been well documented as this big success for VMware and aws. As customers move their workloads into the cloud, IT operations of VMware customers has signaling a lot of change. This is changing the landscape globally is on cloud migration and beyond. What's your take on this? Can you open this up with the most important story around VMC on aws? >>Yes, John. The most important thing for our customers today is the how they can safely and swiftly move their ID infrastructure and applications through cloud. Now, VMware cloud AWS is a service that allows all vSphere based workloads to move to cloud safely, swiftly and reliably. Banks can move their core, core banking platforms, insurance companies move their core insurance platforms, telcos move their goss, bss, PLA platforms, government organizations are moving their citizen engagement platforms using VMC on aws because this is one platform that allows you to move it, move their VMware based platforms very fast. Migrations can happen in a matter of days instead of months. Extremely securely. It's a VMware manage service. It's very secure and highly reliably. It gets the, the reliability of the underlyings infrastructure along with it. So win-win from our customers perspective. >>You know, we reported on this big news in 2016 with Andy Chas, the, and Pat Geling at the time, a lot of people said it was a bad deal. It turned out to be a great deal because not only could VMware customers actually have a cloud migrate to the cloud, do it safely, which was their number one concern. They didn't want to have disruption to their operations, but also position themselves for what's beyond just shifting to the cloud. So I have to ask you, since you got the finger on the pulse here, what are we seeing in the market when it comes to migrating and modern modernizing in the cloud? Because that's the next step. They go to the cloud, you guys have done that, doing it, then they go, I gotta modernize, which means kind of upgrading or refactoring. What's your take on that? >>Yeah, absolutely. Look, the first step is to help our customers assess their infrastructure and licensing and entire ID operations. Once we've done the assessment, we then create their migration plans. A lot of our customers are at that inflection point. They're, they're looking at their real estate, ex data center, real estate. They're looking at their contracts with colocation vendors. They really want to exit their data centers, right? And VMware cloud and AWS is a perfect solution for customers who wanna exit their data centers, migrate these applications onto the AWS platform using VMC on aws, get rid of additional real estate overheads, power overheads, be socially and environmentally conscious by doing that as well, right? So that's the migration story, but to your point, it doesn't end there, right? Modernization is a critical aspect of the entire customer journey as as well customers, once they've migrated their ID applications and infrastructure on cloud get access to all the modernization services that AWS has. They can correct easily to our data lake services, to our AIML services, to custom databases, right? They can decide which applications they want to keep and which applications they want to refactor. They want to take decisions on containerization, make decisions on service computing once they've come to the cloud. But the most important thing is to take that first step. You know, exit data centers, come to AWS using vmc or aws, and then a whole host of modernization options available to them. >>Yeah, I gotta say, we had this right on this, on this story, because you just pointed out a big thing, which was first order of business is to make sure to leverage the on-prem investments that those customers made and then migrate to the cloud where they can maintain their applications, their data, their infrastructure operations that they're used to, and then be in position to start getting modern. So I have to ask you, how are you guys specifically, or how is VMware cloud on s addressing these needs of the customers? Because what happens next is something that needs to happen faster. And sometimes the skills might not be there because if they're running old school, IT ops now they gotta come in and jump in. They're gonna use a data cloud, they're gonna want to use all kinds of machine learning, and there's a lot of great goodness going on above the stack there. So as you move with the higher level services, you know, it's a no brainer, obviously, but they're not, it's not yesterday's higher level services in the cloud. So how are, how is this being addressed? >>Absolutely. I think you hit up on a very important point, and that is skills, right? When our customers are operating, some of the most critical applications I just mentioned, core banking, core insurance, et cetera, they're most of the core applications that our customers have across industries, like even, even large scale ERP systems, they're actually sitting on VMware's vSphere platform right now. When the customer wants to migrate these to cloud, one of the key bottlenecks they face is skill sets. They have the trained manpower for these core applications, but for these high level services, they may not, right? So the first order of business is to help them ease this migration pain as much as possible by not wanting them to, to upscale immediately. And we VMware cloud and AWS exactly does that. I mean, you don't have to do anything. You don't have to create new skill set for doing this, right? Their existing skill sets suffice, but at the same time, it gives them that, that leeway to build that skills roadmap for their team. DNS is invested in that, right? Yes. We want to help them build those skills in the high level services, be it aml, be it, be it i t be it data lake and analytics. We want to invest in them, and we help our customers through that. So that ultimately the ultimate goal of making them drop data is, is, is a front and center. >>I wanna get into some of the use cases and success stories, but I want to just reiterate, hit back your point on the skill thing. Because if you look at what you guys have done at aws, you've essentially, and Andy Chassey used to talk about this all the time when I would interview him, and now last year Adam was saying the same thing. You guys do all the heavy lifting, but if you're a VMware customer user or operator, you are used to things. You don't have to be relearn to be a cloud architect. Now you're already in the game. So this is like almost like a instant path to cloud skills for the VMware. There's hundreds of thousands of, of VMware architects and operators that now instantly become cloud architects, literally overnight. Can you respond to that? Do you agree with that? And then give an example. >>Yes, absolutely. You know, if you have skills on the VMware platform, you know, know, migrating to AWS using via by cloud and AWS is absolutely possible. You don't have to really change the skills. The operations are exactly the same. The management systems are exactly the same. So you don't really have to change anything but the advantages that you get access to all the other AWS services. So you are instantly able to integrate with other AWS services and you become a cloud architect immediately, right? You are able to solve some of the critical problems that your underlying IT infrastructure has immediately using this. And I think that's a great value proposition for our customers to use this service. >>And just one more point, I want just get into something that's really kind of inside baseball or nuanced VMC or VMware cloud on AWS means something. Could you take a minute to explain what on AWS means? Just because you're like hosting and using Amazon as a, as a work workload? Being on AWS means something specific in your world, being VMC on AWS mean? >>Yes. This is a great question, by the way, You know, on AWS means that, you know, VMware's vse platform is, is a, is an iconic enterprise virtualization software, you know, a disproportionately high market share across industries. So when we wanted to create a cloud product along with them, obviously our aim was for them, for the, for this platform to have the goodness of the AWS underlying infrastructure, right? And, and therefore, when we created this VMware cloud solution, it it literally use the AWS platform under the eighth, right? And that's why it's called a VMs VMware cloud on AWS using, using the, the, the wide portfolio of our regions across the world and the strength of the underlying infrastructure, the reliability and, and, and sustainability that it offers. And therefore this product is called VMC on aws. >>It's a distinction I think is worth noting, and it does reflect engineering and some levels of integration that go well beyond just having a SaaS app and, and basically platform as a service or past services. So I just wanna make sure that now super cloud, we'll talk about that a little bit in another interview, but I gotta get one more question in before we get into the use cases and customer success stories is in, in most of the VM world, VMware world, in that IT world, it used to, when you heard migration, people would go, Oh my God, that's gonna take months. And when I hear about moving stuff around and doing cloud native, the first reaction people might have is complexity. So two questions for you before we move on to the next talk. Track complexity. How are you addressing the complexity issue and how long these migrations take? Is it easy? Is it it hard? I mean, you know, the knee jerk reaction is month, You're very used to that. If they're dealing with Oracle or other old school vendors, like, they're, like the old guard would be like, takes a year to move stuff around. So can you comment on complexity and speed? >>Yeah. So the first, first thing is complexity. And you know, what makes what makes anything complex is if you're, if you're required to acquire new skill sets or you've gotta, if you're required to manage something differently, and as far as VMware cloud and AWS on both these aspects, you don't have to do anything, right? You don't have to acquire new skill sets. Your existing idea operation skill sets on, on VMware's platforms are absolutely fine and you don't have to manage it any differently like, than what you're managing your, your ID infrastructure today. So in both these aspects, it's exactly the same and therefore it is absolutely not complex as far as, as far as, as far as we cloud and AWS is concerned. And the other thing is speed. This is where the huge differentiation is. You have seen that, you know, large banks and large telcos have now moved their workloads, you know, literally in days instead of months. >>Because because of VMware cloud and aws, a lot of time customers come to us with specific deadlines because they want to exit their data centers on a particular date. And what happens, VMware cloud and AWS is called upon to do that migration, right? So speed is absolutely critical. The reason is also exactly the same because you are using the exactly the same platform, the same management systems, people are available to you, you're able to migrate quickly, right? I would just reference recently we got an award from President Zelensky of Ukraine for, you know, migrating their entire ID digital infrastructure and, and that that happened because they were using VMware cloud database and happened very swiftly. >>That's been a great example. I mean, that's one political, but the economic advantage of getting outta the data center could be national security. You mentioned Ukraine, I mean Oscar see bombing and death over there. So clearly that's a critical crown jewel for their running their operations, which is, you know, you know, world mission critical. So great stuff. I love the speed thing. I think that's a huge one. Let's get into some of the use cases. One of them is, the first one I wanted to talk about was we just hit on data, data center migration. It could be financial reasons on a downturn or our, or market growth. People can make money by shifting to the cloud, either saving money or making money. You win on both sides. It's a, it's a, it's almost a recession proof, if you will. Cloud is so use case for number one data center migration. Take us through what that looks like. Give an example of a success. Take us through a day, day in the life of a data center migration in, in a couple minutes. >>Yeah. You know, I can give you an example of a, of a, of a large bank who decided to migrate, you know, their, all their data centers outside their existing infrastructure. And they had, they had a set timeline, right? They had a set timeline to migrate the, the, they were coming up on a renewal and they wanted to make sure that this set timeline is met. We did a, a complete assessment of their infrastructure. We did a complete assessment of their IT applications, more than 80% of their IT applications, underlying v vSphere platform. And we, we thought that the right solution for them in the timeline that they wanted, right, is VMware cloud ands. And obviously it was a large bank, it wanted to do it safely and securely. It wanted to have it completely managed, and therefore VMware cloud and aws, you know, ticked all the boxes as far as that is concerned. >>I'll be happy to report that the large bank has moved to most of their applications on AWS exiting three of their data centers, and they'll be exiting 12 more very soon. So that's a great example of, of, of the large bank exiting data centers. There's another Corolla to that. Not only did they manage to manage to exit their data centers and of course use and be more agile, but they also met their sustainability goals. Their board of directors had given them goals to be carbon neutral by 2025. They found out that 35% of all their carbon foot footprint was in their data centers. And if they moved their, their ID infrastructure to cloud, they would severely reduce the, the carbon footprint, which is 35% down to 17 to 18%. Right? And that meant their, their, their, their sustainability targets and their commitment to the go to being carbon neutral as well. >>And that they, and they shift that to you guys. Would you guys take that burden? A heavy lifting there and you guys have a sustainability story, which is a whole nother showcase in and of itself. We >>Can Exactly. And, and cause of the scale of our, of our operations, we are able to, we are able to work on that really well as >>Well. All right. So love the data migration. I think that's got real proof points. You got, I can save money, I can, I can then move and position my applications into the cloud for that reason and other reasons as a lot of other reasons to do that. But now it gets into what you mentioned earlier was, okay, data migration, clearly a use case and you laid out some successes. I'm sure there's a zillion others. But then the next step comes, now you got cloud architects becoming minted every, and you got managed services and higher level services. What happens next? Can you give us an example of the use case of the modernization around the NextGen workloads, NextGen applications? We're starting to see, you know, things like data clouds, not data warehouses. We're not gonna data clouds, it's gonna be all kinds of clouds. These NextGen apps are pure digital transformation in action. Take us through a use case of how you guys make that happen with a success story. >>Yes, absolutely. And this is, this is an amazing success story and the customer here is s and p global ratings. As you know, s and p global ratings is, is the world leader as far as global ratings, global credit ratings is concerned. And for them, you know, the last couple of years have been tough as far as hardware procurement is concerned, right? The pandemic has really upended the, the supply chain. And it was taking a lot of time to procure hardware, you know, configure it in time, make sure that that's reliable and then, you know, distribute it in the wide variety of, of, of offices and locations that they have. And they came to us. We, we did, again, a, a, a alar, a fairly large comprehensive assessment of their ID infrastructure and their licensing contracts. And we also found out that VMware cloud and AWS is the right solution for them. >>So we worked there, migrated all their applications, and as soon as we migrated all their applications, they got, they got access to, you know, our high level services be our analytics services, our machine learning services, our, our, our, our artificial intelligence services that have been critical for them, for their growth. And, and that really is helping them, you know, get towards their next level of modern applications. Right Now, obviously going forward, they will have, they will have the choice to, you know, really think about which applications they want to, you know, refactor or which applications they want to go ahead with. That is really a choice in front of them. And, but you know, the, we VMware cloud and AWS really gave them the opportunity to first migrate and then, you know, move towards modernization with speed. >>You know, the speed of a startup is always the kind of the Silicon Valley story where you're, you know, people can make massive changes in 18 months, whether that's a pivot or a new product. You see that in startup world. Now, in the enterprise, you can see the same thing. I noticed behind you on your whiteboard, you got a slogan that says, are you thinking big? I know Amazon likes to think big, but also you work back from the customers and, and I think this modern application thing's a big deal because I think the mindset has always been constrained because back before they moved to the cloud, most IT, and, and, and on-premise data center shops, it's slow. You gotta get the hardware, you gotta configure it, you gotta, you gotta stand it up, make sure all the software is validated on it, and loading a database and loading oss, I mean, mean, yeah, it got easier and with scripting and whatnot, but when you move to the cloud, you have more scale, which means more speed, which means it opens up their capability to think differently and build product. What are you seeing there? Can you share your opinion on that epiphany of, wow, things are going fast, I got more time to actually think about maybe doing a cloud native app or transforming this or that. What's your, what's your reaction to that? Can you share your opinion? >>Well, ultimately we, we want our customers to utilize, you know, most of our modern services, you know, applications should be microservices based. When desired, they should use serverless applic. So list technology, they should not have monolithic, you know, relational database contracts. They should use custom databases, they should use containers when needed, right? So ultimately, we want our customers to use these modern technologies to make sure that their IT infrastructure, their licensing, their, their entire IT spend is completely native to cloud technologies. They work with the speed of a startup, but it's important for them to, to, to get to the first step, right? So that's why we create this journey for our customers, where you help them migrate, give them time to build the skills, they'll help them mo modernize, take our partners along with their, along with us to, to make sure that they can address the need for our customers. That's, that's what our customers need today, and that's what we are working backwards from. >>Yeah, and I think that opens up some big ideas. I'll just say that the, you know, we're joking, I was joking the other night with someone here in, in Palo Alto around serverless, and I said, you know, soon you're gonna hear words like architectural list. And that's a criticism on one hand, but you might say, Hey, you know, if you don't really need an architecture, you know, storage lists, I mean, at the end of the day, infrastructure is code means developers can do all the it in the coding cycles and then make the operations cloud based. And I think this is kind of where I see the dots connecting. Final thought here, take us through what you're thinking around how this new world is evolving. I mean, architecturals kind of a joke, but the point is, you know, you have to some sort of architecture, but you don't have to overthink it. >>Totally. No, that's a great thought, by the way. I know it's a joke, but it's a great thought because at the end of the day, you know, what do the customers really want? They want outcomes, right? Why did service technology come? It was because there was an outcome that they needed. They didn't want to get stuck with, you know, the, the, the real estate of, of a, of a server. They wanted to use compute when they needed to, right? Similarly, what you're talking about is, you know, outcome based, you know, desire of our customers and, and, and that's exactly where the word is going to, Right? Cloud really enforces that, right? We are actually, you know, working backwards from a customer's outcome and using, using our area the breadth and depth of our services to, to deliver those outcomes, right? And, and most of our services are in that path, right? When we use VMware cloud and aws, the outcome is a, to migrate then to modernize, but doesn't stop there, use our native services, you know, get the business outcomes using this. So I think that's, that's exactly what we are going through >>Actually, should actually, you're the director of global sales and go to market for VMware cloud on Aus. I wanna thank you for coming on, but I'll give you the final minute. Give a plug, explain what is the VMware cloud on Aus, Why is it great? Why should people engage with you and, and the team, and what ultimately is this path look like for them going forward? >>Yeah. At the end of the day, we want our customers to have the best paths to the cloud, right? The, the best path to the cloud is making sure that they migrate safely, reliably, and securely as well as with speed, right? And then, you know, use that cloud platform to, to utilize AWS's native services to make sure that they modernize their IT infrastructure and applications, right? We want, ultimately that our customers, customers, customer get the best out of, you know, utilizing the, that whole application experience is enhanced tremendously by using our services. And I think that's, that's exactly what we are working towards VMware cloud AWS is, is helping our customers in that journey towards migrating, modernizing, whether they wanna exit a data center or whether they wanna modernize their applications. It's a essential first step that we wanna help our customers with >>One director of global sales and go to market with VMware cloud on neighbors. He's with aws sharing his thoughts on accelerating business transformation on aws. This is a showcase. We're talking about the future path. We're talking about use cases with success stories from customers as she's thank you for spending time today on this showcase. >>Thank you, John. I appreciate it. >>Okay. This is the cube, special coverage, special presentation of the AWS Showcase. I'm John Furrier, thanks for watching.

>>Good evening, brilliant humans. My name is Savannah Peterson and very delighted to be streaming to you. Live from the Cube Studios here in Motor City, Michigan. I've got John Furrier on my left. John, this is our last interview of the day. Energy just seems to keep oozing. How >>You doing? Take two, Three days of coverage, the queue love segments. This one's great cuz we have a practitioner who's implementing all the hard core talks to be awesome. Can't wait to get into it. >>Yeah, I'm very excited for this one. If it's not very clear, we are a community focused community is a huge theme here at the show at Cape Con. And our next guests are actually a provider and a customer. Turning it over to you. Lisa and Jake, welcome to the show. >>Thank you so much for having us. >>It's great to be here. It is our pleasure. Lisa, you're with Cockroach. Just in case the audience isn't familiar, give us a quick little sound bite. >>We're a distributed sequel database. Highly scalable, reliable. The database you can't kill, right? We will survive the apocalypse. So very resilient. Our customers, mostly retail, FinTech game meet online gambling. They, they, they need that resiliency, they need that scalability. So the indestructible database is the elevator pitch >>And the success has been very well documented. Valuation obviously is a scorp guard, but huge customers. We were at the Escape 19. Just for the record, the first ever multi-cloud conference hasn't come back baby. Love it. It'll come back soon. >>Yeah, well we did a similar version of it just a month ago and I was, that was before Cockroach. I was a different company there talking a lot about multi-cloud. So, but I'm, I've been a car a couple of years now and I run community, I run developer relations. I'm still also a CNCF ambassador, so I lead community as well. I still run a really large user group in the San Francisco Bay area. So we've just >>Been in >>Community, take through the use case. Jake's story set us up. >>Well I would like Jake to take him through the use case and Cockroach is a part of it, but what they've built is amazing. And also Jake's history is amazing. So you can start Jake, >>Wherever you take >>Your Yeah, sure. I'm Jake, I'm CEO and co-founder of Offset. Oted is the commercial entity behind Spice Dvy and Spice Dvy is a permission service. Cool. So a permission service is something that lets developers and let's platform teams really unlock the full potential of their applications. So a lot of people get stuck on My R back isn't flexible enough. How do I do these fine grain things? How do I do these complex sharing workflows that my product manager thinks is so important? And so our service enables those platform teams and developers to do those kinds of things. >>What's your, what's your infrastructure? What's your setup look like? What, how are you guys looking like on the back end? >>Sure. Yeah. So we're obviously built on top of Kubernetes as well. One of the reasons that we're here. So we use Kubernetes, we use Kubernetes operators to orchestrate everything. And then we use, use Cockroach TV as our production data store, our production backend data store. >>So I'm curious, cause I love when these little matchmakers come together. You said you've now been presenting on a little bit of a road show, which is very exciting. Lisa, how are you and the team surfacing stories like Jakes, >>Well, I mean any, any place we can obviously all the social medias, all the blogs, How >>Are you finding it though? >>How, how did you Oh, like from our customers? Yeah, we have an open source version so people start to use us a long time before we even sometimes know about them. And then they'll come to us and they'll be like, I love Cockroach, and like, tell me about it. Like, tell me what you build and if it's interesting, you know, we'll we'll try to give it some light. And it's always interesting to me what people do with it because it's an interesting technology. I like what they've done with it. I mean the, the fact that it's globally distributed, right? That was like a really important thing to you. Totally. >>Yeah. We're also long term fans of Cockroach, so we actually all work together out of Workbench, which was a co-working space and investor in New York City. So yeah, we go way back. We knew the founders. I, I'm constantly saying like if I could have invested early in cockroach, that would've been the easiest check I could have ever signed. >>Yeah, that's awesome. And then we've been following that too and you guys are now using them, but folks that are out there looking to have the, the same challenges, what are the big challenges on selecting the database? I mean, as you know, the history of Cockroach and you're originating the story, folks out there might not know and they're also gonna choose a database. What's the, what's the big challenge that they can solve that that kind of comes together? What, what would you describe that? >>Sure. So we're, as I said, we're a permission service and per the data that you store in a permission service is incredibly sensitive. You need it to be around, right? You need it to be available. If the permission service goes down, almost everything else goes down because it's all calling into the permission service. Is this user allowed to do this? Are they allowed to do that? And if we can't answer those questions, then our customer is down, right? So when we're looking at a database, we're looking for reliability, we're looking for durability, disaster recovery, and then permission services are one of the only services that you usually don't shard geographically. So if you look at like AWS's iam, that's a global service, even though the individual things that they run are actually sharded by region. So we also needed a globally distributed database with all of those other properties. So that's what led us >>To, this is a huge topic. So man, we've been talking about all week the cloud is essentially distributed database at this point and it's distributed system. So distributed database is a hot topic, totally not really well reported. A lot of people talking about it, but how would you describe this distributed trend that's going on? What are the key reasons that they're driving it? What's making this more important than ever in your mind, in your opinion? >>I mean, for our use case, it was just a hard requirement, right? We had to be able to have this global service. But I think just for general use cases, a distributed database, distributed database has that like shared nothing architecture that allows you to kind of keep it running and horizontally scale it. And as your requirements and as your applications needs change, you can just keep adding on capacity and keep adding on reliability and availability. >>I'd love to get both of your opinion. You've been talking about the, the, the, the phases of customers, the advanced got Kubernetes going crazy distributed, super alpha geek. Then you got the, the people who are building now, then you got the lagers who are coming online. Where do you guys see the market now in terms of, I know the Alphas are all building all the great stuff and you guys had great success with all the top logos and they're all doing hardcore stuff. As the mainstream enterprise comes in, where's their psychology, what's on their mind? What's, you share any insight into your perspective on that? Because we're seeing a lot more of it folks becoming like real cloud players. >>Yeah, I feel like in mainstream enterprise hasn't been lagging as much as people think. You know, certainly there's been pockets in big enterprises that have been looking at this and as distributed sequel, it gives you that scalability that it's absolutely essential for big enterprises. But also it gives you the, the multi-region, you know, the, you have to be globally distributed. And for us, for enterprises, you know, you need your data near where the users are. I know this is hugely important to you as well. So you have to be able to have a multi-region functionality and that's one thing that distributed SQL lets you build and that what we built into our product. And I know that's one of the things you like too. >>Yeah, well we're a brand new product. I mean we only founded the company two years ago, but we're actually getting inbound interest from big enterprises because we solve the kinds of challenges that they have and whether, I mean, most of them already do have a cockroach footprint, but whether they did or didn't, once they need to bring in our product, they're going to be adopting cockroach transitively anyway. >>So, So you're built on top of Cockroach, right? And Spice dv, is that open source or? >>It >>Is, yep. Okay. And explain the role of open source and your business model. Can you take a minute to talk about the relevance of that? >>Yeah, open source is key. My background is, before this I was at Red Hat. Before that we were at CoreOS, so CoreOS acquisition and before that, >>One of the best acquisitions that ever happened for the value. That was a great, great team. Yeah, >>We, we, we had fun and before that we built Qua. So my co-founders and I, we built Quay, which is a, a first private docker registry. So CoreOS and, and all of those things are all open source or deeply open source. So it's just in our dna. We also see it as part of our go-to market motion. So if you are a database, a lot of people won't even consider what you're doing without being open source. Cuz they say, I don't want to take a, I don't want to, I don't want to end up in an Oracle situation >>Again. Yeah, Oracle meaning they go, you get you locked in, get you in a headlock, Increase prices. >>Yeah. Oh yeah, >>Can, can >>I got triggered. >>You need to talk about your PTSD there >>Or what. >>I mean we have 20,000 stars on GitHub because we've been open and transparent from the beginning. >>Yeah. And it >>Well, and both of your projects were started based on Google Papers, >>Right? >>That is true. Yep. And that's actually, so we're based off of the Google Zans of our paper. And as you know, Cockroach is based off of the Google Span paper and in the the Zanzibar paper, they have this globally distributed database that they're built on top of. And so when I said we're gonna go and we're gonna make a company around the Zabar paper, people would go, Well, what are you gonna do for Span? And I was like, Easy cockroach, they've got us covered. >>Yeah, I know the guys and my friends. Yeah. So the question is why didn't you get into the first round of Cockroach? She said don't answer that. >>The question he did answer though was one of those age old arguments in our community about pronunciation. We used to argue about Quay, I always called it Key of course. And the co-founder obviously knows how it's pronounced, you know, it's the et cd argument, it's the co cuddl versus the control versus coo, CTL Quay from the co-founder. That is end of argument. You heard it here first >>And we're keeping it going with Osted. So awesome. A lot of people will say Zeed or, you know, so we, we just like to have a little ambiguity >>In the, you gotta have some semantic arguments, arm wrestling here. I mean, it keeps, it keeps everyone entertained, especially on the over the weekend. What's, what's next? You got obviously Kubernetes in there. Can you explain the relationship between Kubernetes, how you're handling Spice dv? What, what does the Kubernetes piece fit in and where, where is that going to be going? >>Yeah, great question. Our flagship product right now is a dedicated, and in a dedicated, what we're doing is we're spinning up a single tenant Kubernetes cluster. We're installing all of our operator suite, and then we're installing the application and running it in a single tenant fashion for our customers in the same region, in the same data center where they're running their applications to minimize latency. Because of this, as an authorization service, latency gets passed on directly to the end user. So everybody's trying to squeeze the latency down as far as they can. And our strategy is to just run these single tenant stacks for people with the minimal latency that we can and give them a VPC dedicated link very similar to what Cockroach does in their dedicated >>Product. And the distributed architecture makes that possible because it's lighter way, it's not as heavy. Is that one of the reasons? >>Yep. And Kubernetes really gives us sort of like a, a level playing field where we can say, we're going going to take the provider, the cloud providers Kubernetes offering, normalize it, lay down our operators, and then use that as the base for delivering >>Our application. You know, Jake, you made me think of something I wanted to bring up with other guests, but now since you're here, you're an expert, I wanna bring that up, but talk about Super Cloud. We, we coined that term, but it's kind of multi-cloud, is that having workloads on multiple clouds is hard. I mean there are, they are, there are workloads on, on clouds, but the complexity of one clouds, let's take aws, they got availability zones, they got regions, you got now data issues in each one being global, not that easy on one cloud, nevermind all clouds. Can you share your thoughts on how you see that progression? Because when you start getting, as its distributed database, a lot of good things might come up that could fit into solving the complexity of global workloads. Could you share your thoughts on or scoping that problem space of, of geography? Yeah, because you mentioned latency, like that's huge. What are some of the other challenges that other people have with mobile? >>Yeah, absolutely. When you have a service like ours where the data is small, but very critical, you can get a vendor like Cockroach to step in and to fill that gap and to give you that globally distributed database that you can call into and retrieve the data. I think the trickier issues come up when you have larger data, you have huge binary blobs. So back when we were doing Quay, we wanted to be a global service as well, but we had, you know, terabytes, petabytes of data that we were like, how do we get this replicated everywhere and not go broke? Yeah. So I think those are kind of the interesting issues moving forward is what do you do with like those huge data lakes, the huge amount of data, but for the, the smaller bits, like the things that we can keep in a relational database. Yeah, we're, we're happy that that's quickly becoming a solved >>Problem. And by the way, that that data problem also is compounded when the architecture goes to the edge. >>Totally. >>I mean this is a big issue. >>Exactly. Yeah. Edge is something that we're thinking a lot about too. Yeah, we're lucky that right now the applications that are consuming us are in a data center already. But as they start to move to the edge, we're going to have to move to the edge with them. And it's a story that we're gonna have to figure out. >>All right, so you're a customer cockroach, what's the testimonial if I put you on the spot, say, hey, what's it like working with these guys? You know, what, what's the, what's the, you know, the founders, so you know, you give a good description, little biased, but we'll, we'll we'll hold you on it. >>Yeah. Working with Cockroach has been great. We've had a couple things that we've run into along the way and we've gotten great support from our account managers. They've brought in the right technical expertise when we need it. Cuz what we're doing with Cockroach is not you, you couldn't do it on Postgres, right? So it's not just a simple rip and replace for us, we're using all of the features of Cockroach, right? We're doing as of system time queries, we're doing global replication. We're, you know, we're, we're consuming it all. And so we do need help from them sometimes and they've been great. Yeah. >>And that's natural as they grow their service. I mean the world's changing. >>Well I think one of the important points that you mentioned with multi-cloud, we want you to have the choice. You know, you can run it in in clouds, you can run it hybrid, you can run it OnPrem, you can do whatever you want and it's just, it's one application that you can run in these different data centers. And so really it's up to you how do you want to build your infrastructure? >>And one of the things we've been talking about, the super cloud concept that we've been issue getting a lot of contrary, but, but people are leaning into it is that it's the refactoring and taking advantage of the services. Like what you mentioned about cockroach. People are doing that now on cloud going the lift and shift market kind of had it time now it's like hey, I can start taking advantage of these higher level services or capability of someone else's stack and refactoring it. So I think that's a dynamic that I'm seeing a lot more of. And it sounds like it's working out great in this situation. >>I just came from a talk and I asked them, you know, what don't you wanna put in the cloud and what don't you wanna run in Kubernetes or on containers and good Yeah. And the customers that I was on stage with, one of the guys made a joke and he said I would put my dog in a container room. I could, he was like in the category, which is his right, which he is in the category of like, I'll put everything in containers and these are, you know, including like mis critical apps, heritage apps, since they don't wanna see legacy anymore. Heritage apps, these are huge enterprises and they wanna put everything in the cloud. Everything >>You so want your dog that gets stuck on the airplane when it's on the tarmac. >>Oh >>God, that's, she was the, don't take that analogy. Literally don't think about that. Well that's, >>That's let's not containerize. >>There's always supply chain concern. >>It. So I mean going macro and especially given where we are cncf, it's all about open source. Do y'all think that open source builds a better future? >>Yeah and a better past. I mean this is, so much of this software is founded on open source. I, we wouldn't be here really. I've been in open source community for many, many years so I wouldn't say I'm biased. I would say this is how we build software. I came from like in a high school we're all like, oh let's build a really cool application. Oh you know what? I built this cuz I needed it, but maybe somebody else needs it too. And you put it out there and that is the ethos of Silicon Valley, right? That's where we grew up. So I've always had that mindset, you know, and social coding and why I have three people, right? Working on the same thing when one person you could share it's so inefficient. All of that. Yeah. So I think it's great that people work on what they're really good at. You know, we all, now you need some standardization, you need some kind of control around this whole thing. Sometimes some foundations to, you know, herd the cats. Yeah. But it's, it's great. Which is why I'm a c CF ambassador and I spend a lot of time, you know, in my free time talking about open source. Yeah, yeah. >>It's clear how passionate you are about it. Jake, >>This is my second company that we founded now and I don't think either of them could have existed without the base of open source, right? Like when you look at I have this cool idea for an app or a company and I want to go try it out, the last thing I want to do is go and negotiate with a vendor to get like the core data component. Yeah. To even be able to get to the >>Prototypes. NK too, by the way. Yeah. >>Hey >>Nk >>Or hire, you know, a bunch of PhDs to go and build that core component for me. So yeah, I mean nobody can argue that >>It truly is, I gotta say a best time if you're a developer right now, it's awesome to be a developer right now. It's only gonna get better. As we were riff from the last session about productivity, we believe that if you follow the digital transformation to its conclusion, developers and it aren't a department serving the business, they are the business. And that means they're running the show, which means that now their entire workflow is gonna change. It's gonna be have to be leveraging services partnering. So yeah, open source just fills that. So the more code coming up, it's just no doubt in our mind that that's go, that's happening and will accelerate. So yeah, >>You know, no one company is gonna be able to compete with a community. 50,000 users contributing versus you riding it yourself in your garage with >>Your dogs. Well it's people driven too. It's humans not container. It's humans working together. And here you'll see, I won't say horse training, that's a bad term, but like as projects start to get traction, hey, why don't we come together as, as the world starts to settle and the projects have traction, you start to see visibility into use cases, functionality. Some projects might not be, they have to kind of see more kind >>Of, not every feature is gonna be development. Oh. So I mean, you know, this is why you connect with truly brilliant people who can architect and distribute sequel database. Like who thought of that? It's amazing. It's as, as our friend >>You say, Well let me ask you a question before we wrap up, both by time, what is the secret of Kubernetes success? What made Kubernetes specifically successful? Was it timing? Was it the, the unambitious nature of it, the unification of it? Was it, what was the reason why is Kubernetes successful, right? And why nothing else? >>Well, you know what I'm gonna say? So I'm gonna let Dave >>First don't Jake, you go first. >>Oh boy. If we look at what was happening when Kubernetes first came out, it was, Mesosphere was kind of like the, the big player in the space. I think Kubernetes really, it had the backing from the right companies. It had the, you know, it had the credibility, it was sort of loosely based on Borg, but with the story of like, we've fixed everything that was broken in Borg. Yeah. And it's better now. Yeah. So I think it was just kind and, and obviously people were looking for a solution to this problem as they were going through their containerization journey. And I, yeah, I think it was just right >>Place, the timing consensus of hey, if we just let this happen, something good might come together for everybody. That's the way I felt. I >>Think it was right place, right time, right solution. And then it just kind of exploded when we were at Cores. Alex Povi, our ceo, he heard about Kubernetes and he was like, you know, we, we had a thing called Fleet D or we had a tool called Fleet. And he's like, Nope, we're all in on Kubernetes now. And that was an amazing Yeah, >>I remember that interview. >>I, amazing decision. >>Yeah, >>It's clear we can feel the shift. It's something that's come up a lot this week is is the commitment. Everybody's all in. People are ready for their transformation and Kubernetes is definitely gonna be the orchestrator that we're >>Leveraging. Yeah. And it's an amazing community. But it was, we got lucky that the, the foundational technology, I mean, you know, coming out of Google based on Go conferences, based on Go, it's no to coincidence that this sort of nature of, you know, pods horizontally, scalable, it's all fits together. I does make sense. Yeah. I mean, no offense to Python and some of the other technologies that were built in other languages, but Go is an awesome language. It's so, so innovative. Innovative things you could do with it. >>Awesome. Oh definitely. Jake, I'm very curious since we learned on the way and you are a Detroit native? >>I am. Yep. I grew up in the in Warren, which is just a suburb right outside of Detroit. >>So what does it mean to you as a Michigan born bloke to be here, see your entire community invade? >>It is, I grew up coming to the Detroit Auto Show in this very room >>That brought me to Detroit the first time. Love n a I a s. Been there with our friends at Ford just behind us. >>And it's just so interesting to me to see the accumulation, the accumulation of tech coming to Detroit cuz it's really not something that historically has been a huge presence. And I just love it. I love to see the activity out on the streets. I love to see all the restaurants and coffee shops full of people. Just, I might tear up. >>Well, I was wondering if it would give you a little bit of that hometown pride and also the joy of bringing your community together. I mean, this is merging your two probably most core communities. Yeah, >>Yeah. Your >>Youth and your, and your career. It doesn't get more personal than that really. Right. >>It's just been, it's been really exciting to see the energy. >>Well thanks for going on the queue. Thanks for sharing. Appreciate it. Thanks >>For having us. Yeah, thank you both so much. Lisa, you were a joy of ball of energy right when you walked up. Jake, what a compelling story. Really appreciate you sharing it with us. John, thanks for the banter and the fabulous questions. I'm >>Glad I could help out. >>Yeah, you do. A lot more than help out sweetheart. And to all of you watching the Cube today, thank you so much for joining us live from Detroit, the Cube Studios. My name is Savannah Peterson and we'll see you for our event wrap up next.

(inspirational music) >> The history of high performance computing is unique and storied. You know, it's generally accepted that the first true supercomputer was shipped in the mid 1960s by Controlled Data Corporations, CDC, designed by an engineering team led by Seymour Cray, the father of Supercomputing. He left CDC in the 70's to start his own company, of course, carrying his own name. Now that company Cray, became the market leader in the 70's and the 80's, and then the decade of the 80's saw attempts to bring new designs, such as massively parallel systems, to reach new heights of performance and efficiency. Supercomputing design was one of the most challenging fields, and a number of really brilliant engineers became kind of quasi-famous in their little industry. In addition to Cray himself, Steve Chen, who worked for Cray, then went out to start his own companies. Danny Hillis, of Thinking Machines. Steve Frank of Kendall Square Research. Steve Wallach tried to build a mini supercomputer at Convex. These new entrants, they all failed, for the most part because the market at the time just wasn't really large enough and the economics of these systems really weren't that attractive. Now, the late 80's and the 90's saw big Japanese companies like NEC and Fujitsu entering the fray and governments around the world began to invest heavily in these systems to solve societal problems and make their nations more competitive. And as we entered the 21st century, we saw the coming of petascale computing, with China actually cracking the top 100 list of high performance computing. And today, we're now entering the exascale era, with systems that can complete a billion, billion calculations per second, or 10 to the 18th power. Astounding. And today, the high performance computing market generates north of $30 billion annually and is growing in the high single digits. Supercomputers solve the world's hardest problems in things like simulation, life sciences, weather, energy exploration, aerospace, astronomy, automotive industries, and many other high value examples. And supercomputers are expensive. You know, the highest performing supercomputers used to cost tens of millions of dollars, maybe $30 million. And we've seen that steadily rise to over $200 million. And today we're even seeing systems that cost more than half a billion dollars, even into the low billions when you include all the surrounding data center infrastructure and cooling required. The US, China, Japan, and EU countries, as well as the UK, are all investing heavily to keep their countries competitive, and no price seems to be too high. Now, there are five mega trends going on in HPC today, in addition to this massive rising cost that we just talked about. One, systems are becoming more distributed and less monolithic. The second is the power of these systems is increasing dramatically, both in terms of processor performance and energy consumption. The x86 today dominates processor shipments, it's going to probably continue to do so. Power has some presence, but ARM is growing very rapidly. Nvidia with GPUs is becoming a major player with AI coming in, we'll talk about that in a minute. And both the EU and China are developing their own processors. We're seeing massive densities with hundreds of thousands of cores that are being liquid-cooled with novel phase change technology. The third big trend is AI, which of course is still in the early stages, but it's being combined with ever larger and massive, massive data sets to attack new problems and accelerate research in dozens of industries. Now, the fourth big trend, HPC in the cloud reached critical mass at the end of the last decade. And all of the major hyperscalers are providing HPE, HPC as a service capability. Now finally, quantum computing is often talked about and predicted to become more stable by the end of the decade and crack new dimensions in computing. The EU has even announced a hybrid QC, with the goal of having a stable system in the second half of this decade, most likely around 2027, 2028. Welcome to theCUBE's preview of SC22, the big supercomputing show which takes place the week of November 13th in Dallas. theCUBE is going to be there. Dave Nicholson will be one of the co-hosts and joins me now to talk about trends in HPC and what to look for at the show. Dave, welcome, good to see you. >> Hey, good to see you too, Dave. >> Oh, you heard my narrative up front Dave. You got a technical background, CTO chops, what did I miss? What are the major trends that you're seeing? >> I don't think you really- You didn't miss anything, I think it's just a question of double-clicking on some of the things that you brought up. You know, if you look back historically, supercomputing was sort of relegated to things like weather prediction and nuclear weapons modeling. And these systems would live in places like Lawrence Livermore Labs or Los Alamos. Today, that requirement for cutting edge, leading edge, highest performing supercompute technology is bleeding into the enterprise, driven by AI and ML, artificial intelligence and machine learning. So when we think about the conversations we're going to have and the coverage we're going to do of the SC22 event, a lot of it is going to be looking under the covers and seeing what kind of architectural things contribute to these capabilities moving forward, and asking a whole bunch of questions. >> Yeah, so there's this sort of theory that the world is moving toward this connectivity beyond compute-centricity to connectivity-centric. We've talked about that, you and I, in the past. Is that a factor in the HPC world? How is it impacting, you know, supercomputing design? >> Well, so if you're designing an island that is, you know, tip of this spear, doesn't have to offer any level of interoperability or compatibility with anything else in the compute world, then connectivity is important simply from a speeds and feeds perspective. You know, lowest latency connectivity between nodes and things like that. But as we sort of democratize supercomputing, to a degree, as it moves from solely the purview of academia into truly ubiquitous architecture leverage by enterprises, you start asking the question, "Hey, wouldn't it be kind of cool if we could have this hooked up into our ethernet networks?" And so, that's a whole interesting subject to explore because with things like RDMA over converged ethernet, you now have the ability to have these supercomputing capabilities directly accessible by enterprise computing. So that level of detail, opening up the box of looking at the Nix, or the storage cards that are in the box, is actually critically important. And as an old-school hardware knuckle-dragger myself, I am super excited to see what the cutting edge holds right now. >> Yeah, when you look at the SC22 website, I mean, they're covering all kinds of different areas. They got, you know, parallel clustered systems, AI, storage, you know, servers, system software, application software, security. I mean, wireless HPC is no longer this niche. It really touches virtually every industry, and most industries anyway, and is really driving new advancements in society and research, solving some of the world's hardest problems. So what are some of the topics that you want to cover at SC22? >> Well, I kind of, I touched on some of them. I really want to ask people questions about this idea of HPC moving from just academia into the enterprise. And the question of, does that mean that there are architectural concerns that people have that might not be the same as the concerns that someone in academia or in a lab environment would have? And by the way, just like, little historical context, I can't help it. I just went through the upgrade from iPhone 12 to iPhone 14. This has got one terabyte of storage in it. One terabyte of storage. In 1997, I helped build a one terabyte NAS system that a government defense contractor purchased for almost $2 million. $2 million! This was, I don't even know, it was $9.99 a month extra on my cell phone bill. We had a team of seven people who were going to manage that one terabyte of storage. So, similarly, when we talk about just where are we from a supercompute resource perspective, if you consider it historically, it's absolutely insane. I'm going to be asking people about, of course, what's going on today, but also the near future. You know, what can we expect? What is the sort of singularity that needs to occur where natural language processing across all of the world's languages exists in a perfect way? You know, do we have the compute power now? What's the interface between software and hardware? But really, this is going to be an opportunity that is a little bit unique in terms of the things that we typically cover, because this is a lot about cracking open the box, the server box, and looking at what's inside and carefully considering all of the components. >> You know, Dave, I'm looking at the exhibitor floor. It's like, everybody is here. NASA, Microsoft, IBM, Dell, Intel, HPE, AWS, all the hyperscale guys, Weka IO, Pure Storage, companies I've never heard of. It's just, hundreds and hundreds of exhibitors, Nvidia, Oracle, Penguin Solutions, I mean, just on and on and on. Google, of course, has a presence there, theCUBE has a major presence. We got a 20 x 20 booth. So, it's really, as I say, to your point, HPC is going mainstream. You know, I think a lot of times, we think of HPC supercomputing as this just sort of, off in the eclectic, far off corner, but it really, when you think about big data, when you think about AI, a lot of the advancements that occur in HPC will trickle through and go mainstream in commercial environments. And I suspect that's why there are so many companies here that are really relevant to the commercial market as well. >> Yeah, this is like the Formula 1 of computing. So if you're a Motorsports nerd, you know that F1 is the pinnacle of the sport. SC22, this is where everybody wants to be. Another little historical reference that comes to mind, there was a time in, I think, the early 2000's when Unisys partnered with Intel and Microsoft to come up with, I think it was the ES7000, which was supposed to be the mainframe, the sort of Intel mainframe. It was an early attempt to use... And I don't say this in a derogatory way, commodity resources to create something really, really powerful. Here we are 20 years later, and we are absolutely smack in the middle of that. You mentioned the focus on x86 architecture, but all of the other components that the silicon manufacturers bring to bear, companies like Broadcom, Nvidia, et al, they're all contributing components to this mix in addition to, of course, the microprocessor folks like AMD and Intel and others. So yeah, this is big-time nerd fest. Lots of academics will still be there. The supercomputing.org, this loose affiliation that's been running these SC events for years. They have a major focus, major hooks into academia. They're bringing in legit computer scientists to this event. This is all cutting edge stuff. >> Yeah. So like you said, it's going to be kind of, a lot of techies there, very technical computing, of course, audience. At the same time, we expect that there's going to be a fair amount, as they say, of crossover. And so, I'm excited to see what the coverage looks like. Yourself, John Furrier, Savannah, I think even Paul Gillin is going to attend the show, because I believe we're going to be there three days. So, you know, we're doing a lot of editorial. Dell is an anchor sponsor, so we really appreciate them providing funding so we can have this community event and bring people on. So, if you are interested- >> Dave, Dave, I just have- Just something on that point. I think that's indicative of where this world is moving when you have Dell so directly involved in something like this, it's an indication that this is moving out of just the realm of academia and moving in the direction of enterprise. Because as we know, they tend to ruthlessly drive down the cost of things. And so I think that's an interesting indication right there. >> Yeah, as do the cloud guys. So again, this is mainstream. So if you're interested, if you got something interesting to talk about, if you have market research, you're an analyst, you're an influencer in this community, you've got technical chops, maybe you've got an interesting startup, you can contact David, david.nicholson@siliconangle.com. John Furrier is john@siliconangle.com. david.vellante@siliconangle.com. I'd be happy to listen to your pitch and see if we can fit you onto the program. So, really excited. It's the week of November 13th. I think November 13th is a Sunday, so I believe David will be broadcasting Tuesday, Wednesday, Thursday. Really excited. Give you the last word here, Dave. >> No, I just, I'm not embarrassed to admit that I'm really, really excited about this. It's cutting edge stuff and I'm really going to be exploring this question of where does it fit in the world of AI and ML? I think that's really going to be the center of what I'm really seeking to understand when I'm there. >> All right, Dave Nicholson. Thanks for your time. theCUBE at SC22. Don't miss it. Go to thecube.net, go to siliconangle.com for all the news. This is Dave Vellante for theCUBE and for Dave Nicholson. Thanks for watching. And we'll see you in Dallas. (inquisitive music)

foreign [Music] welcome to this Cube showcase accelerating business transformation with VMware Cloud on aw it's a solution Innovation conversation with two great guests Fred Ward and VP of Commercial Services at AWS and Narayan bardawaj who's the VP and general manager of cloud Solutions at VMware gentlemen thanks for uh joining me on the Showcase great to be here hey thanks for having us on it's a great topic you know we we've been covering this VMware Cloud on AWS since since the launch going back and it's been amazing to watch The Evolution from people saying oh it's the worst thing I've ever seen what's this mean uh and depressed we're we're kind of not really on board with kind of the vision but as it played out as you guys had announced together it did work out great for VMware it did work out great for a divs and it continues two years later and I want to just get an update from you guys on where you guys see this has been going obviously multiple years where is the evolution of the solution as we are right now coming off VMware Explorer just recently and going in to reinvent uh which is only a couple weeks away uh this feels like tomorrow but you know as we prepare a lot going on where are we with the evolution of the solution I mean the first thing I want to say is you know October 2016 was a seminal moment in the history of I.T right when bad girls singer and Andy jassy came together to announce this and I think John you were there at the time I was there it was a great great moment we launched the solution in 2017 the year after that at vmworld back when we called it vmworld I think we've gone from strength to strength one of the things that has really mattered to us is we've learned from AWS also and the process is this notion of working backwards so we're really really focused on customer feedback as we build the service offering now five years old pretty remarkable Journey uh you know in the first years we tried to get across all the regions you know that was a big Focus because there was so much demand for it in the second year we started going really on Enterprise great features we invented this pretty awesome feature called stretch clusters where you could stretch a vsphere cluster using vsan NSX across two azs in the same region pretty phenomenal for lines of availability that applications start started to get with that particular feature and we kept moving forward all kinds of integration with AWS direct connect Transit gateways with our own Advanced networking capabilities uh you know along the way Disaster Recovery we punched out you need two new Services just focused on that and then more recently we launched our outposts partnership we were up on the stage at reinvent again with Pat and Andy announcing AWS outposts and the VMware flavor of that VMware cloud and AWS outposts I think it's been significant growth in our federal sector as well the federal Empire certification more recently so all in all we're super excited we're five years old the customer momentum is really really strong we are scaling the service massively across all GEOS and industries that's great great update and I think one of the things that you mentioned was how the advantages you guys got from that relationship and this has kind of been the theme for AWS man since I can remember from day one Fred you guys do the heavy lifting as as it's always say for the customers here VMware comes on board takes advantage of the AWS and kind of just doesn't miss a beat continues to move their workloads that everyone's using you know vsphere and these are these are Big workloads on AWS what's the AWS perspective on this how do you see it yeah uh it's pretty fascinating to watch how fast customers can actually transform and move when you take the the skill set that they're familiar with and the advanced capabilities that they've been using on-prem and then overlay it on top of the AWS infrastructure that's that's evolving quickly and and building out new hardware and new instances we'll talk about uh but that combined experience between both of us on a jointly engineered solution uh to bring the best security and the best features that really matter for those workloads uh drive a lot of efficiency and speed for the for the customer so it's been well received and the partnership is stronger than ever from an engineering standpoint from a business standpoint and obviously it's been very interesting to look at just how we stay day one in terms of looking at new features and work and and responding to what customers want so pretty pretty excited about just seeing the transformation and the speed that which customers can move to uh BMC yeah that's a great value probably we've been talking about that in context to anyone building on top of the cloud they can have their own super cloud as we call it if you take advantage of all the capex and investment Amazon's made and AWS is made and and continues to make in performance I as and pass all great stuff I have to ask you guys both as you guys see this going to the next level what are some of the differentiations you see around the service compared to other options on the market what makes it different what's the combination you mentioned jointly engineered what are some of the key differentias of the service compared to others yeah I think one of the key things red talked about is this jointly engineered notion right from day one we were the earlier doctors of the AWS Nitro platform right the reinvention of ec2 back five years ago and so we've been you know having a very very strong engineering partnership at that level I think from uh we have a customer standpoint you get the full software-defined data center compute storage networking on ec2 bare metal across all regions you can scale that elastically up and down it's pretty phenomenal just having that consistency Global right on AWS ec2 Global regions now the other thing that's a real differentiator for us customers tell us about is this whole notion of a managed service right and this was somewhat new to VMware this undifferentiated heavy lifting where customers are to provision rack stack Hardware configure the software on top and then upgrade the software and the security patches on top so we took away all of that pain as customers transition to VMware cloud and AWS in fact my favorite story from last year when we were all going through the lock for Jay debacle the industry was just going through that right favorite proof point from customers was before they could even race uh this issue to us we sent them a notification saying uh we already patched all of your systems no action from you the customers were super thrilled I mean these are large Banks many other customers around the world super thrill they had to take no action for a pretty incredible industry challenge that we were all facing that's a great point you know the whole managed service piece brings up the security and you're kind of teasing at it but you know there's always vulnerabilities that emerge when you're doing complex logic and as you grow your Solutions there's more bits you know Fred we were commenting before we came on cameras more bits than ever before and and at the physics layer too as well as the software so you never know when there's going to be a zero day vulnerability out there just it happens we saw one with Fortinet this week um this came out of the woodwork but moving fast on those patches is huge this brings up the whole support angle I wanted to ask you about how you guys are doing that as well because to me we see the value when we when we talk to customers on the cube about this you know it was a real real easy understanding of how what the cloud means to them with VMware now with the AWS but the question that comes up that we want to get more clarity on is how do you guys handle the support together well what's interesting about this is that it's it's done mutually we have dedicated support teams on both sides that work together pretty seamlessly to make sure that whether there's a issue at any layer including all the way up into the app layer as you think about some of the other workloads like sap we'll go end to end and make sure that we support the customer regardless of where the particular issue might be for them uh and on top of that we look at where where we're improving reliability in as a first order of principle between both companies so from an availability and reliability standpoint it's it's top of mind and no matter where the particular item might land we're going to go help the customer resolve that works really well on the VMware side let's spend the feedback there what's the what's some of the updates same scene yeah yeah I think uh look I mean VMware owns and operates the service will be a phenomenal back in relationship with AWS customers call VMware for the service for any issues and then we have a awesome relationship with AWS in the back end for support issues for any hardware issues capacity management that we jointly do right all the hard problems that customers don't have to worry about uh I think on the front end we also have a really good group of solution Architects across the companies that help to really explain the solution do complex things like Cloud migration which is much much easier with VMware on AWS we're presenting that easy button to the public cloud in many ways and so we have a whole technical audience across the two companies that are working with customers every single day you know you had mentioned a list here some of the Innovations the you mentioned the stretch clustering you know getting the GEOS working Advanced Network disaster recovery um you know fed fed ramp public sector certifications outposts all good you guys are checking the boxes every year you got a good good accomplishments list there on the VMware AWS side here in this relationship the question that I'm interested in is what's next what uh recent Innovations are you doing are you making investments in what's on the list this year what items will be next year how do you see the the new things the list of the cosmos people want to know what's next they don't want to see stagnant uh growth here they want to see more action you know as as uh Cloud kind of continues to scale and modern applications Cloud native you're seeing more and more containers more and more you know more CF CI CD pipelining with with modern apps putting more pressure on the system what's new what's the new Innovations absolutely and I think as a five-year-old service offering uh Innovation is top of mind for us every single day so just to call out a few recent innovations that we announced in San Francisco at VMware Explorer um first of all uh our new platform i4i dot metal it's isolate based it's pretty awesome it's the latest and greatest uh all the speeds and beats that you would expect from VMware and AWS at this point in our relationship we announced two different storage options this notion of working from customer feedback allowing customers even more price reductions really take off that storage and park it externally right and you know separate that from compute so two different storage offerings there one is with AWS FSX NetApp on tap which brings in our NetApp partnership as well into the equation and really get that NetApp based really excited about this offering as well and the second storage offering called VMware Cloud Flex story vmware's own managed storage offering beyond that we've done a lot of other Innovations as well I really wanted to talk about VMware Cloud Flex compute where previously customers could only scale by hosts you know host is 36 to 48 cores give or take but with VMware cloudflex compute we are now allowing this notion of a resource defined compute model where customers can just get exactly the vcpu memory and storage that maps to the applications however small they might be so this notion of granularity is really a big innovation that that we are launching in the market this year and then last but not least topper ransomware of course it's a Hot Topic in the industry we are seeing many many customers ask for this we are happy to announce a new ransomware recovery with our VMware Cloud VR solution a lot of innovation there and the way we are able to do machine learning and make sure the workloads that are covered from snapshots backups are actually safe to use so there's a lot of differentiation on that front as well a lot of networking Innovations with project North Star the ability to have layer 4 through layer seven uh you know new SAS services in that area as well keep in mind that the service already supports managed kubernetes for containers it's built in to the same clusters that have virtual machines and so this notion of a single service with a great TCO for VMS and containers is sort of at the heart of our option the networking side certainly is a hot area to keep innovating on every year it's the same same conversation get better faster networking more more options there the flex computes interesting if you don't mind me getting a quick clarification could you explain the address between resource defined versus Hardware defined because this is kind of what we had saw at explore coming out that notion of resource defined versus Hardware defined what's that what does that mean yeah I mean I think we've been super successful in this Hardware defined notion where we're scaling by the hardware unit uh that we present as software-defined data centers right so that's been super successful but we you know customers wanted more especially customers in different parts of the world wanted to start even smaller and grow even more incrementally right lower the cost even more and so this is the part where resource defined starts to be very very interesting as a way to think about you know here's my bag of resources exactly based on what the customer's requested it would be for fiber machines five containers its size exactly for that and then as utilization grows we elastically behind the scenes were able to grow it through policies so that's a whole different dimension it's a whole different service offering that adds value when customers are comfortable they can go from one to the other they can go back to that post-based model if they so choose to and there's a jump off point across these two different economic models it's kind of cloud flexibility right there I like the name Fred let's get into some of the uh examples of customers if you don't mind let's get into some of these we have some time I want to unpack a little bit of what's going on with the customer deployments one of the things we've heard again on the cube is from customers is they like the clarity of the relationship they love the cloud positioning of it and then what happens is they lift and shift the workloads and it's like feels great it's just like we're running VMware on AWS and then they start consuming higher level Services kind of that adoption Next Level happens um and because it's in the cloud so so can you guys take us through some recent examples of customer wins or deployments where they're using VMware Cloud on AWS on getting started and then how do they progress once they're there how does it evolve can you just walk us through a couple use cases sure um there's a well there's a couple one it's pretty interesting that you know like you said as there's more and more bids you need better and better hardware and networking and we're super excited about the I-4 uh and the capabilities there in terms of doubling and or tripling what we're doing around a lower variability on latency and just improving all the speeds but what customers are doing with it like the college in New Jersey they're accelerating their deployment on a on onboarding over like 7 400 students over a six to eight month period and they've really realized a ton of savings but what's interesting is where and how they can actually grow onto additional native Services too so connectivity to any other services is available as they start to move and migrate into this um the the options there obviously are tied to all the Innovation that we have across any Services whether it's containerized and with what they're doing with tanzu or with any other container and or services within AWS so so there's there's some pretty interesting scenarios where that data and or the processing which is moved quickly with full compliance whether it's in like health care or regulatory business is is allowed to then consume and use things for example with text extract or any other really cool service that has you know monthly and quarterly Innovations so there's things that you just can't could not do before that are coming out uh and saving customers money and building Innovative applications on top of their uh their current uh app base in in a rapid fashion so pretty excited about it there's a lot of examples I think I probably don't have time to go into too many here yeah but that's actually the best part is listening to customers and seeing how many net new services and new applications are they actually building on top of this platform now Ryan what's your perspective from the VMware psychics you know you guys have now a lot of head room to offer customers with Amazon's you know higher level services and or whatever's homegrown what is being rolled out because you now have a lot of hybrid too so so what's your what's your take on what what's happening and with customers I mean it's been phenomenal the customer adoption of this and you know Banks and many other highly sensitive verticals are running production grade applications tier one applications on the service over the last five years and so you know I have a couple of really good examples SNP Global is one of my favorite examples large Bank the merch with IHS Market big sort of conglomeration now both customers were using VMware cloud and AWS in different ways and with the uh with the use case one of their use cases was how do I just respond to these Global opportunities without having to invest in physical data centers and then how do I migrate and consolidate all my data centers across the globe of which there were many and so one specific example for this company was how they migrated thousand one thousand workloads to VMware cloud and AWS in just six weeks pretty phenomenal if you think about everything that goes into a cloud migration process people process technology and the beauty of the technology going from VMware point a to VMware point B the the lowest cost lowest risk approach to adopting we have our cloud in AWS so that's uh you know one of my favorite examples there are many other examples across other verticals that we continue to see the good thing is we're seeing rapid expansion across the globe we're constantly entering new markets uh with a limited number of regions and progressing our roadmap it's great to see I mean the data center migrations go from months many many months to weeks it's interesting to see some of those success stories so congratulations another one of the other uh interesting uh and fascinating uh uh benefits is the sustainability Improvement in terms of being green so the efficiency gains that we have both in current uh generation and New Generation processors and everything that we're doing to make sure that when a customer can be elastic they're also saving power which is really critical in a lot of regions worldwide at this point in time they're they're seeing those benefits if you're running really inefficiently in your own data center that is just a not a great use of power so the actual calculators and the benefits to these workloads is are pretty phenomenal just in being more green which I like we just all need to do our part there and and this is a big part of it here it's a huge it's a huge point about sustainability for everyone glad you called that out the other one I would say is supply chain issues another one you see that constrains I can't buy hardware and the third one is really obvious but no one really talks about it it's security right I mean um I remember interviewing Steven Schmidt with that AWS and many years ago this is like 2013 and um you know at that time people saying the Cloud's not secure and he's like listen it's more secure in the cloud than on premise and if you look at the security breaches it's all about the on-premise data center vulnerabilities not so much Hardware so there's a lot you gotta the the stay current on on the isolation there is hard so I think I think the security and supply chain threat is another one do you agree I I absolutely agree uh it's it's hard to manage supply chain nowadays we put a lot of effort into that and I think we have a great ability to forecast and make sure that we can lean in and have the resources that are available and run them run them more efficiently yeah and then like you said on the security Point Security is job one it is it is the only P1 and if you think of how we build our infrastructure from Nitro all the way up and how we respond and work with our partners and our customers there's nothing more important and Narayan your point earlier about the managed service patching and being on top of things is really going to get better all right final question I really want to thank you for your time on this showcase it's really been a great conversation uh Fred you had made a comment earlier I want to kind of end with the kind of a curveball and put you guys on the spot we're talking about a modern a new modern shift it's another we're seeing another inflection point we've been documenting it it's almost like Cloud hitting another inflection point um with application and open source growth significantly at the app layer continue to put a lot of pressure and innovation in the infrastructure side so the question is for you guys each to answer is what's the same and what's different in today's market so it's kind of like we want more of the same here but also things have changed radically and better here what are the what's what's changed for better and where what's still the same kind of thing hanging around that people are focused on can you share your perspective I'll I'll tackle it um you know uh businesses are complex and they're often unique uh that that's the same uh what's changed is how fast you can innovate the ability to combine manage services and new Innovative services and build new applications is so much faster today leveraging world-class Hardware uh that you don't have to worry about that's elastic you could not do that even five ten years ago to the degree you can today especially with the Innovation so Innovation is accelerating uh at a rate that most people can't even comprehend and understand the the set of services that are available to them it's really fascinating to see what a one pizza team of of Engineers can go actually develop in a week it is phenomenal so super excited about this space and it's only going to continue to accelerate that that's my take there I am you got a lot of platform to compete on with Amazon I got a lot to build on the memory which then you're right on your side what's your what's your answer to that question I think we're seeing a lot of innovation with new applications that customers [Music] I think uh what we see is this whole notion of how do you go from desktop to production to the secure supply chain and how can we truly uh you know build on the agility that developers desire and build all the security and the pipelines to energize that motor production quickly and efficiently I think we are seeing uh you know we're at the very start of that sort of uh of Journey um of course we have invested in kubernetes means to an end but it's so much more Beyond that's happening in the industry and I think we're at the very very beginning of this Transformations Enterprise transformation that many of our customers are going through and we're inherently part of it yeah well gentlemen I really appreciate that we're seeing the same things more the same here on you know solving these complexities with abstractions whether it's you know higher level services with large-scale infrastructure um at your fingertips infrastructure is code infrastructure to be provisioned serverless all the good stuff happening Fred with AWS on your side and we're seeing customers resonate with this idea of being an operator again being a cloud operator and developer so the developer Ops is kind of devops is kind of changing too so all for the better thank you for spending the time we're seeing again that traction with the VMware customer base and it was getting getting along great together so thanks for sharing your perspectives they appreciate it thank you so much okay thank you John okay this is thecube and AWS VMware showcase accelerating business transformation VMware Cloud on AWS jointly engineered solution bringing Innovation to the VMware customer base going to the cloud and Beyond I'm John Furrier your host thanks for watching [Music]