(upbeat music) >> Hello, everyone, and welcome to theCUBE's presentation of the "AWS Startup Showcase." This is season three, episode one. The focus of this episode is AI/ML: Top Startups Building Foundational Models, Infrastructure, and AI. It's great topics, super-relevant, and it's part of our ongoing coverage of startups in the AWS ecosystem. I'm your host, John Furrier, with theCUBE. Today, we're excited to be joined by Jay Marshall, VP of Business Development at Neural Magic. Jay, thanks for coming on theCUBE. >> Hey, John, thanks so much. Thanks for having us. >> We had a great CUBE conversation with you guys. This is very much about the company focuses. It's a feature presentation for the "Startup Showcase," and the machine learning at scale is the topic, but in general, it's more, (laughs) and we should call it "Machine Learning and AI: How to Get Started," because everybody is retooling their business. Companies that aren't retooling their business right now with AI first will be out of business, in my opinion. You're seeing massive shift. This is really truly the beginning of the next-gen machine learning AI trend. It's really seeing ChatGPT. Everyone sees that. That went mainstream. But this is just the beginning. This is scratching the surface of this next-generation AI with machine learning powering it, and with all the goodness of cloud, cloud scale, and how horizontally scalable it is. The resources are there. You got the Edge. Everything's perfect for AI 'cause data infrastructure's exploding in value. AI is just the applications. This is a super topic, so what do you guys see in this general area of opportunities right now in the headlines? And I'm sure you guys' phone must be ringing off the hook, metaphorically speaking, or emails and meetings and Zooms. What's going on over there at Neural Magic? >> No, absolutely, and you pretty much nailed most of it. I think that, you know, my background, we've seen for the last 20-plus years. Even just getting enterprise applications kind of built and delivered at scale, obviously, amazing things with AWS and the cloud to help accelerate that. And we just kind of figured out in the last five or so years how to do that productively and efficiently, kind of from an operations perspective. Got development and operations teams. We even came up with DevOps, right? But now, we kind of have this new kind of persona and new workload that developers have to talk to, and then it has to be deployed on those ITOps solutions. And so you pretty much nailed it. Folks are saying, "Well, how do I do this?" These big, generational models or foundational models, as we're calling them, they're great, but enterprises want to do that with their data, on their infrastructure, at scale, at the edge. So for us, yeah, we're helping enterprises accelerate that through optimizing models and then delivering them at scale in a more cost-effective fashion. >> Yeah, and I think one of the things, the benefits of OpenAI we saw, was not only is it open source, then you got also other models that are more proprietary, is that it shows the world that this is really happening, right? It's a whole nother level, and there's also new landscape kind of maps coming out. You got the generative AI, and you got the foundational models, large LLMs. Where do you guys fit into the landscape? Because you guys are in the middle of this. How do you talk to customers when they say, "I'm going down this road. I need help. I'm going to stand this up." This new AI infrastructure and applications, where do you guys fit in the landscape? >> Right, and really, the answer is both. I think today, when it comes to a lot of what for some folks would still be considered kind of cutting edge around computer vision and natural language processing, a lot of our optimization tools and our runtime are based around most of the common computer vision and natural language processing models. So your YOLOs, your BERTs, you know, your DistilBERTs and what have you, so we work to help optimize those, again, who've gotten great performance and great value for customers trying to get those into production. But when you get into the LLMs, and you mentioned some of the open source components there, our research teams have kind of been right in the trenches with those. So kind of the GPT open source equivalent being OPT, being able to actually take, you know, a multi-$100 billion parameter model and sparsify that or optimize that down, shaving away a ton of parameters, and being able to run it on smaller infrastructure. So I think the evolution here, you know, all this stuff came out in the last six months in terms of being turned loose into the wild, but we're staying in the trenches with folks so that we can help optimize those as well and not require, again, the heavy compute, the heavy cost, the heavy power consumption as those models evolve as well. So we're staying right in with everybody while they're being built, but trying to get folks into production today with things that help with business value today. >> Jay, I really appreciate you coming on theCUBE, and before we came on camera, you said you just were on a customer call. I know you got a lot of activity. What specific things are you helping enterprises solve? What kind of problems? Take us through the spectrum from the beginning, people jumping in the deep end of the pool, some people kind of coming in, starting out slow. What are the scale? Can you scope the kind of use cases and problems that are emerging that people are calling you for? >> Absolutely, so I think if I break it down to kind of, like, your startup, or I maybe call 'em AI native to kind of steal from cloud native years ago, that group, it's pretty much, you know, part and parcel for how that group already runs. So if you have a data science team and an ML engineering team, you're building models, you're training models, you're deploying models. You're seeing firsthand the expense of starting to try to do that at scale. So it's really just a pure operational efficiency play. They kind of speak natively to our tools, which we're doing in the open source. So it's really helping, again, with the optimization of the models they've built, and then, again, giving them an alternative to expensive proprietary hardware accelerators to have to run them. Now, on the enterprise side, it varies, right? You have some kind of AI native folks there that already have these teams, but you also have kind of, like, AI curious, right? Like, they want to do it, but they don't really know where to start, and so for there, we actually have an open source toolkit that can help you get into this optimization, and then again, that runtime, that inferencing runtime, purpose-built for CPUs. It allows you to not have to worry, again, about do I have a hardware accelerator available? How do I integrate that into my application stack? If I don't already know how to build this into my infrastructure, does my ITOps teams, do they know how to do this, and what does that runway look like? How do I cost for this? How do I plan for this? When it's just x86 compute, we've been doing that for a while, right? So it obviously still requires more, but at least it's a little bit more predictable. >> It's funny you mentioned AI native. You know, born in the cloud was a phrase that was out there. Now, you have startups that are born in AI companies. So I think you have this kind of cloud kind of vibe going on. You have lift and shift was a big discussion. Then you had cloud native, kind of in the cloud, kind of making it all work. Is there a existing set of things? People will throw on this hat, and then what's the difference between AI native and kind of providing it to existing stuff? 'Cause we're a lot of people take some of these tools and apply it to either existing stuff almost, and it's not really a lift and shift, but it's kind of like bolting on AI to something else, and then starting with AI first or native AI. >> Absolutely. It's a- >> How would you- >> It's a great question. I think that probably, where I'd probably pull back to kind of allow kind of retail-type scenarios where, you know, for five, seven, nine years or more even, a lot of these folks already have data science teams, you know? I mean, they've been doing this for quite some time. The difference is the introduction of these neural networks and deep learning, right? Those kinds of models are just a little bit of a paradigm shift. So, you know, I obviously was trying to be fun with the term AI native, but I think it's more folks that kind of came up in that neural network world, so it's a little bit more second nature, whereas I think for maybe some traditional data scientists starting to get into neural networks, you have the complexity there and the training overhead, and a lot of the aspects of getting a model finely tuned and hyperparameterization and all of these aspects of it. It just adds a layer of complexity that they're just not as used to dealing with. And so our goal is to help make that easy, and then of course, make it easier to run anywhere that you have just kind of standard infrastructure. >> Well, the other point I'd bring out, and I'd love to get your reaction to, is not only is that a neural network team, people who have been focused on that, but also, if you look at some of the DataOps lately, AIOps markets, a lot of data engineering, a lot of scale, folks who have been kind of, like, in that data tsunami cloud world are seeing, they kind of been in this, right? They're, like, been experiencing that. >> No doubt. I think it's funny the data lake concept, right? And you got data oceans now. Like, the metaphors just keep growing on us, but where it is valuable in terms of trying to shift the mindset, I've always kind of been a fan of some of the naming shift. I know with AWS, they always talk about purpose-built databases. And I always liked that because, you know, you don't have one database that can do everything. Even ones that say they can, like, you still have to do implementation detail differences. So sitting back and saying, "What is my use case, and then which database will I use it for?" I think it's kind of similar here. And when you're building those data teams, if you don't have folks that are doing data engineering, kind of that data harvesting, free processing, you got to do all that before a model's even going to care about it. So yeah, it's definitely a central piece of this as well, and again, whether or not you're going to be AI negative as you're making your way to kind of, you know, on that journey, you know, data's definitely a huge component of it. >> Yeah, you would have loved our Supercloud event we had. Talk about naming and, you know, around data meshes was talked about a lot. You're starting to see the control plane layers of data. I think that was the beginning of what I saw as that data infrastructure shift, to be horizontally scalable. So I have to ask you, with Neural Magic, when your customers and the people that are prospects for you guys, they're probably asking a lot of questions because I think the general thing that we see is, "How do I get started? Which GPU do I use?" I mean, there's a lot of things that are kind of, I won't say technical or targeted towards people who are living in that world, but, like, as the mainstream enterprises come in, they're going to need a playbook. What do you guys see, what do you guys offer your clients when they come in, and what do you recommend? >> Absolutely, and I think where we hook in specifically tends to be on the training side. So again, I've built a model. Now, I want to really optimize that model. And then on the runtime side when you want to deploy it, you know, we run that optimized model. And so that's where we're able to provide. We even have a labs offering in terms of being able to pair up our engineering teams with a customer's engineering teams, and we can actually help with most of that pipeline. So even if it is something where you have a dataset and you want some help in picking a model, you want some help training it, you want some help deploying that, we can actually help there as well. You know, there's also a great partner ecosystem out there, like a lot of folks even in the "Startup Showcase" here, that extend beyond into kind of your earlier comment around data engineering or downstream ITOps or the all-up MLOps umbrella. So we can absolutely engage with our labs, and then, of course, you know, again, partners, which are always kind of key to this. So you are spot on. I think what's happened with the kind of this, they talk about a hockey stick. This is almost like a flat wall now with the rate of innovation right now in this space. And so we do have a lot of folks wanting to go straight from curious to native. And so that's definitely where the partner ecosystem comes in so hard 'cause there just isn't anybody or any teams out there that, I literally do from, "Here's my blank database, and I want an API that does all the stuff," right? Like, that's a big chunk, but we can definitely help with the model to delivery piece. >> Well, you guys are obviously a featured company in this space. Talk about the expertise. A lot of companies are like, I won't say faking it till they make it. You can't really fake security. You can't really fake AI, right? So there's going to be a learning curve. They'll be a few startups who'll come out of the gate early. You guys are one of 'em. Talk about what you guys have as expertise as a company, why you're successful, and what problems do you solve for customers? >> No, appreciate that. Yeah, we actually, we love to tell the story of our founder, Nir Shavit. So he's a 20-year professor at MIT. Actually, he was doing a lot of work on kind of multicore processing before there were even physical multicores, and actually even did a stint in computational neurobiology in the 2010s, and the impetus for this whole technology, has a great talk on YouTube about it, where he talks about the fact that his work there, he kind of realized that the way neural networks encode and how they're executed by kind of ramming data layer by layer through these kind of HPC-style platforms, actually was not analogous to how the human brain actually works. So we're on one side, we're building neural networks, and we're trying to emulate neurons. We're not really executing them that way. So our team, which one of the co-founders, also an ex-MIT, that was kind of the birth of why can't we leverage this super-performance CPU platform, which has those really fat, fast caches attached to each core, and actually start to find a way to break that model down in a way that I can execute things in parallel, not having to do them sequentially? So it is a lot of amazing, like, talks and stuff that show kind of the magic, if you will, a part of the pun of Neural Magic, but that's kind of the foundational layer of all the engineering that we do here. And in terms of how we're able to bring it to reality for customers, I'll give one customer quote where it's a large retailer, and it's a people-counting application. So a very common application. And that customer's actually been able to show literally double the amount of cameras being run with the same amount of compute. So for a one-to-one perspective, two-to-one, business leaders usually like that math, right? So we're able to show pure cost savings, but even performance-wise, you know, we have some of the common models like your ResNets and your YOLOs, where we can actually even perform better than hardware-accelerated solutions. So we're trying to do, I need to just dumb it down to better, faster, cheaper, but from a commodity perspective, that's where we're accelerating. >> That's not a bad business model. Make things easier to use, faster, and reduce the steps it takes to do stuff. So, you know, that's always going to be a good market. Now, you guys have DeepSparse, which we've talked about on our CUBE conversation prior to this interview, delivers ML models through the software so the hardware allows for a decoupling, right? >> Yep. >> Which is going to drive probably a cost advantage. Also, it's also probably from a deployment standpoint it must be easier. Can you share the benefits? Is it a cost side? Is it more of a deployment? What are the benefits of the DeepSparse when you guys decouple the software from the hardware on the ML models? >> No you actually, you hit 'em both 'cause that really is primarily the value. Because ultimately, again, we're so early. And I came from this world in a prior life where I'm doing Java development, WebSphere, WebLogic, Tomcat open source, right? When we were trying to do innovation, we had innovation buckets, 'cause everybody wanted to be on the web and have their app and a browser, right? We got all the money we needed to build something and show, hey, look at the thing on the web, right? But when you had to get in production, that was the challenge. So to what you're speaking to here, in this situation, we're able to show we're just a Python package. So whether you just install it on the operating system itself, or we also have a containerized version you can drop on any container orchestration platform, so ECS or EKS on AWS. And so you get all the auto-scaling features. So when you think about that kind of a world where you have everything from real-time inferencing to kind of after hours batch processing inferencing, the fact that you can auto scale that hardware up and down and it's CPU based, so you're paying by the minute instead of maybe paying by the hour at a lower cost shelf, it does everything from pure cost to, again, I can have my standard IT team say, "Hey, here's the Kubernetes in the container," and it just runs on the infrastructure we're already managing. So yeah, operational, cost and again, and many times even performance. (audio warbles) CPUs if I want to. >> Yeah, so that's easier on the deployment too. And you don't have this kind of, you know, blank check kind of situation where you don't know what's on the backend on the cost side. >> Exactly. >> And you control the actual hardware and you can manage that supply chain. >> And keep in mind, exactly. Because the other thing that sometimes gets lost in the conversation, depending on where a customer is, some of these workloads, like, you know, you and I remember a world where even like the roundtrip to the cloud and back was a problem for folks, right? We're used to extremely low latency. And some of these workloads absolutely also adhere to that. But there's some workloads where the latency isn't as important. And we actually even provide the tuning. Now, if we're giving you five milliseconds of latency and you don't need that, you can tune that back. So less CPU, lower cost. Now, throughput and other things come into play. But that's the kind of configurability and flexibility we give for operations. >> All right, so why should I call you if I'm a customer or prospect Neural Magic, what problem do I have or when do I know I need you guys? When do I call you in and what does my environment look like? When do I know? What are some of the signals that would tell me that I need Neural Magic? >> No, absolutely. So I think in general, any neural network, you know, the process I mentioned before called sparcification, it's, you know, an optimization process that we specialize in. Any neural network, you know, can be sparcified. So I think if it's a deep-learning neural network type model. If you're trying to get AI into production, you have cost concerns even performance-wise. I certainly hate to be too generic and say, "Hey, we'll talk to everybody." But really in this world right now, if it's a neural network, it's something where you're trying to get into production, you know, we are definitely offering, you know, kind of an at-scale performant deployable solution for deep learning models. >> So neural network you would define as what? Just devices that are connected that need to know about each other? What's the state-of-the-art current definition of neural network for customers that may think they have a neural network or might not know they have a neural network architecture? What is that definition for neural network? >> That's a great question. So basically, machine learning models that fall under this kind of category, you hear about transformers a lot, or I mentioned about YOLO, the YOLO family of computer vision models, or natural language processing models like BERT. If you have a data science team or even developers, some even regular, I used to call myself a nine to five developer 'cause I worked in the enterprise, right? So like, hey, we found a new open source framework, you know, I used to use Spring back in the day and I had to go figure it out. There's developers that are pulling these models down and they're figuring out how to get 'em into production, okay? So I think all of those kinds of situations, you know, if it's a machine learning model of the deep learning variety that's, you know, really specifically where we shine. >> Okay, so let me pretend I'm a customer for a minute. I have all these videos, like all these transcripts, I have all these people that we've interviewed, CUBE alumnis, and I say to my team, "Let's AI-ify, sparcify theCUBE." >> Yep. >> What do I do? I mean, do I just like, my developers got to get involved and they're going to be like, "Well, how do I upload it to the cloud? Do I use a GPU?" So there's a thought process. And I think a lot of companies are going through that example of let's get on this AI, how can it help our business? >> Absolutely. >> What does that progression look like? Take me through that example. I mean, I made up theCUBE example up, but we do have a lot of data. We have large data models and we have people and connect to the internet and so we kind of seem like there's a neural network. I think every company might have a neural network in place. >> Well, and I was going to say, I think in general, you all probably do represent even the standard enterprise more than most. 'Cause even the enterprise is going to have a ton of video content, a ton of text content. So I think it's a great example. So I think that that kind of sea or I'll even go ahead and use that term data lake again, of data that you have, you're probably going to want to be setting up kind of machine learning pipelines that are going to be doing all of the pre-processing from kind of the raw data to kind of prepare it into the format that say a YOLO would actually use or let's say BERT for natural language processing. So you have all these transcripts, right? So we would do a pre-processing path where we would create that into the file format that BERT, the machine learning model would know how to train off of. So that's kind of all the pre-processing steps. And then for training itself, we actually enable what's called sparse transfer learning. So that's transfer learning is a very popular method of doing training with existing models. So we would be able to retrain that BERT model with your transcript data that we have now done the pre-processing with to get it into the proper format. And now we have a BERT natural language processing model that's been trained on your data. And now we can deploy that onto DeepSparse runtime so that now you can ask that model whatever questions, or I should say pass, you're not going to ask it those kinds of questions ChatGPT, although we can do that too. But you're going to pass text through the BERT model and it's going to give you answers back. It could be things like sentiment analysis or text classification. You just call the model, and now when you pass text through it, you get the answers better, faster or cheaper. I'll use that reference again. >> Okay, we can create a CUBE bot to give us questions on the fly from the the AI bot, you know, from our previous guests. >> Well, and I will tell you using that as an example. So I had mentioned OPT before, kind of the open source version of ChatGPT. So, you know, typically that requires multiple GPUs to run. So our research team, I may have mentioned earlier, we've been able to sparcify that over 50% already and run it on only a single GPU. And so in that situation, you could train OPT with that corpus of data and do exactly what you say. Actually we could use Alexa, we could use Alexa to actually respond back with voice. How about that? We'll do an API call and we'll actually have an interactive Alexa-enabled bot. >> Okay, we're going to be a customer, let's put it on the list. But this is a great example of what you guys call software delivered AI, a topic we chatted about on theCUBE conversation. This really means this is a developer opportunity. This really is the convergence of the data growth, the restructuring, how data is going to be horizontally scalable, meets developers. So this is an AI developer model going on right now, which is kind of unique. >> It is, John, I will tell you what's interesting. And again, folks don't always think of it this way, you know, the AI magical goodness is now getting pushed in the middle where the developers and IT are operating. And so it again, that paradigm, although for some folks seem obvious, again, if you've been around for 20 years, that whole all that plumbing is a thing, right? And so what we basically help with is when you deploy the DeepSparse runtime, we have a very rich API footprint. And so the developers can call the API, ITOps can run it, or to your point, it's developer friendly enough that you could actually deploy our off-the-shelf models. We have something called the SparseZoo where we actually publish pre-optimized or pre-sparcified models. And so developers could literally grab those right off the shelf with the training they've already had and just put 'em right into their applications and deploy them as containers. So yeah, we enable that for sure as well. >> It's interesting, DevOps was infrastructure as code and we had a last season, a series on data as code, which we kind of coined. This is data as code. This is a whole nother level of opportunity where developers just want to have programmable data and apps with AI. This is a whole new- >> Absolutely. >> Well, absolutely great, great stuff. Our news team at SiliconANGLE and theCUBE said you guys had a little bit of a launch announcement you wanted to make here on the "AWS Startup Showcase." So Jay, you have something that you want to launch here? >> Yes, and thank you John for teeing me up. So I'm going to try to put this in like, you know, the vein of like an AWS, like main stage keynote launch, okay? So we're going to try this out. So, you know, a lot of our product has obviously been built on top of x86. I've been sharing that the past 15 minutes or so. And with that, you know, we're seeing a lot of acceleration for folks wanting to run on commodity infrastructure. But we've had customers and prospects and partners tell us that, you know, ARM and all of its kind of variance are very compelling, both cost performance-wise and also obviously with Edge. And wanted to know if there was anything we could do from a runtime perspective with ARM. And so we got the work and, you know, it's a hard problem to solve 'cause the instructions set for ARM is very different than the instruction set for x86, and our deep tensor column technology has to be able to work with that lower level instruction spec. But working really hard, the engineering team's been at it and we are happy to announce here at the "AWS Startup Showcase," that DeepSparse inference now has, or inference runtime now has support for AWS Graviton instances. So it's no longer just x86, it is also ARM and that obviously also opens up the door to Edge and further out the stack so that optimize once run anywhere, we're not going to open up. So it is an early access. So if you go to neuralmagic.com/graviton, you can sign up for early access, but we're excited to now get into the ARM side of the fence as well on top of Graviton. >> That's awesome. Our news team is going to jump on that news. We'll get it right up. We get a little scoop here on the "Startup Showcase." Jay Marshall, great job. That really highlights the flexibility that you guys have when you decouple the software from the hardware. And again, we're seeing open source driving a lot more in AI ops now with with machine learning and AI. So to me, that makes a lot of sense. And congratulations on that announcement. Final minute or so we have left, give a summary of what you guys are all about. Put a plug in for the company, what you guys are looking to do. I'm sure you're probably hiring like crazy. Take the last few minutes to give a plug for the company and give a summary. >> No, I appreciate that so much. So yeah, joining us out neuralmagic.com, you know, part of what we didn't spend a lot of time here, our optimization tools, we are doing all of that in the open source. It's called SparseML and I mentioned SparseZoo briefly. So we really want the data scientists community and ML engineering community to join us out there. And again, the DeepSparse runtime, it's actually free to use for trial purposes and for personal use. So you can actually run all this on your own laptop or on an AWS instance of your choice. We are now live in the AWS marketplace. So push button, deploy, come try us out and reach out to us on neuralmagic.com. And again, sign up for the Graviton early access. >> All right, Jay Marshall, Vice President of Business Development Neural Magic here, talking about performant, cost effective machine learning at scale. This is season three, episode one, focusing on foundational models as far as building data infrastructure and AI, AI native. I'm John Furrier with theCUBE. Thanks for watching. (bright upbeat music)

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

(upbeat music) >> Okay, welcome back everyone. I'm John Furrier here in theCUBE, in Palo Alto for "CUBE Conversation" with Chris Jones, Director of Product Management at Platform9. I've got a series of questions, had a great conversation earlier. Chris, I have a couple questions for you, what do you think? >> Let's do it, John. >> Okay, how does Platform9 Solution, you- can it be used on any infrastructure anywhere, cloud, edge, on-premise? >> It can, that's the beauty of our control plane, right? It was born in the cloud, and we primarily deliver that SaaS, which allows it to work in your data center, on bare metal, on VMs, or with public cloud infrastructure. We now give you the ability to take that control plane, install it in your data center, and then use it with anything, or even in air gap. And that includes capabilities with bare metal orchestration as well. >> Second question. How does Platform9 ensure maximum uptime, and proactive issue resolution? >> Oh, that's a good question. So if you come to Platform nine we're going to talk about always on assurance. What is driving that is a system of three components around self-healing, monitoring, and proactive assistance. So our software will heal broken things on nodes, right? If something stops running that should be running, it will attempt to restart that. We also have monitoring that's deployed with everything. So you build a cluster in AWS, well, we put open source monitoring agents, that are actually Prometheus, on every single node. That means it's resilient, right? So if you lose a node, you don't lose monitoring. But that data importantly comes back to our control plane, and that's the control plane that you can put in your data center as well. That data is what alerts us, and you as a user, anytime of the day that something's going wrong. Let's say etcd latency, good example, etcd is going slow. We'll find out, we might not be able to take restorative action immediately, but we're definitely going to reach out and say,, "You have a problem, let's get ahead of this and let's prevent that from becoming a bigger problem." And that's what we're delivering. When we say always on assurance, we're talking about self-healing, we're talking about remote monitoring, we're talking about being proactive with our customers, not waiting for the phone call or the support desk ticket saying, "Oh we think something's not working." Or worse, the customer has an outage. >> Awesome. Thanks for sharing. Can you explain the process for implementing Platform9 within a company's existing infrastructure. >> Are we doing air gap, or on-prem or SaaS approached? SaaS approach I think is by far the easiest, right? We can build a dedicated Platform9 control plane instance in a manner of minutes, for any customer. So when we do a proof of concept or onboarding, we just literally put in an email address, put in the name you want for your fully qualified domain name, and your instance is up. From that point onwards, the user can just log in, and using our CLI, talk to any number of, say, virtual machines, or physical servers in their environment for, you know, doing this in a data center or colo, and say, "I want these to be my Kubernetes control plane nodes. Here's the five of them. Here's the VIP for the load balancing, the API server and here are all of my compute nodes." And that CLI will work with the SaaS control plane, and go and build the cluster. That's as simple as it, CentOS, Ubuntu, just plain old operating system. Our software takes care of all the prerequisites, installing all the pieces, putting down MetalLB, CoreDNS, Metrics Server, Kubernetes dashboard, etcd backups. You built some servers. That's essentially what you've done, and the rest is being handled by Platform9. It's as simple as that. >> Great, thanks for that. What are the two traditional paths for companies considering the cloud native journey? The two paths. >> The traditional paths. I think that's your engineering team running so fast that before you even realize that you've got, you know, 10 EKS clusters. Or, hey, we can do this. You know, I've got the I can build it mentality. Let's go DIY completely open source Kubernetes on our infrastructure, and we're going to piecemeal build it all up together. They're, I think the pathways that people traditionally look at this journey, as opposed to having that third alternative saying can I just consume it on my infrastructure, be it cloud or on-premise or at the edge. >> Third is the new way, you guys do that. >> That's been our focus since the company was, you know, brought together back in the open OpenStack days. >> Awesome, what's the makeup of your customer base? Is there a certain pattern to the size or environments that you guys work with? Is there a pattern or consistency to your customer base? >> It's a spread, right? We've got large enterprises like Juniper, and we go all the way down to people with 20, 30, 50 nodes in total. We've got people in banking and finance, we've got things all the way through to telecommunications and storage infrastructure. >> What's your favorite feature of Platform9? >> My favorite feature? You know, if I ask, should I say this as a pre-sales engineer, let me show you a favorite thing. My immediate response is, I should never do this. (John laughs) To me it's just being able to define my cluster and say, go. And in five minutes I have that environment, I can see everything that's running, right? It's all unified, it's one spot, right? I'm a cluster admin. I said I wanted three control plane, 25 workers. Here's the infrastructure, it creates it, and once it's built, I can see everything that's running, right? All the applications that are there. One UI, I don't have to go click around. I'm not trying to solve things or download things. It's the fact that it's unified and just delivered in one hit. >> What is the one thing that people should know about Platform9 that they might not know about it? >> I think it's that we help developers and engineers as much as we can help our operations teams. I think, for a long time we've sort of targeted that user and said, hey, we, we really help you. It's like, but why are they doing this? Why are they building any infrastructure or any cloud platform? Well, it's to run applications and services, to help their customers, but how do they get there? There's people building and writing those things, and we're helping them, right? For the last two years, we've been really focused on making it simple, and I think that's an important thing to know. >> Chris, thanks so much, appreciate it. >> Yeah, thank you, John. >> Okay, that's theCUBE Q&A session here with Platform9. I'm John Furrier, thanks for watching. (light music)

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

>> Well, welcome back here to the Venetian. We're in Las Vegas. It is Wednesday, Day 2 of our coverage here of AWS re:Invent, 22. I'm your host, John Walls on theCUBE and it's a pleasure to welcome in two more guests as part of our AWS startup showcase, which is again part of the startup program globally at AWS. I've got Anant Verma, who is the Vice President of Engineering at Elation. Anant, good to see you, sir. >> Good to see you too. >> Good to be with us. And Haseeb Budhani, who is the CEO and co-founder of Rafay Systems. Good to see you, sir. >> Good to see you again. >> Thanks for having, yeah. A cuber, right? You've been on theCUBE? >> Once or twice. >> Many occasions. But a first timer here, as a matter of fact, glad to have you aboard. All right, tell us about Elation. First for those whom who might not be familiar with what you're up to these days, just give it a little 30,000 foot level. >> Sure, sure. So, yeah, Elation is a startup and a leader in the enterprise data intelligence space. That really includes a lot of different things including data search, data discovery, metadata management, data cataloging, data governance, data policy management, a lot of different things that companies want to do with the hoards of data that they have and Elation, our product is the answer to solve some of those problems. We've been doing pretty good. Elation is in running for about 10 years now. We are a series A startup now, we just raised around a few, a couple of months ago. We are already a hundred million plus in revenue. So. >> John: Not shabby. >> Yeah, it's a big benchmark for companies to, startup companies, to cross that milestone. So, yeah. >> And what's the relationship? I know Rafay and you have worked together, in fact, the two of you have, which I find interesting, you have a chance, you've been meeting on Zoom for a number of months, as many of us have it meeting here for the first time. But talk about that relationship with Rafay. >> Yeah, so I actually joined Elation in January and this is part of the move of Elation to a more cloud native solution. So, we have been running on AWS since last year and as part of making our solution more cloud native, we have been looking to containerize our services and run them on Kubernetes. So, that's the reason why I joined Elation in the first place to kind of make sure that this migration or move to a cloud native actually works out really well for us. This is a big move for the companies. A lot of companies that have done in the past, including, you know, Confluent or MongoDB, when they did that, they actually really reap great benefits out of that. So to do that, of course, you know, as we were looking at Kubernetes as a solution, I was personally more looking for a way to speed up things and get things out in production as fast as possible. And that's where I think, Janeb introduced us... >> That's right. >> Two of us. I think we share the same investor actually, so that's how we found each other. And yeah, it was a pretty simple decision in terms of, you know, getting the solution, figuring it out if it's useful for us and then of course, putting it out there. >> So you've hit the keyword, Kubernetes, right? And, so if you would to honestly jump in here, there are challenges, right? That you're trying to help them solve and you're working on the Kubernetes platform. So, you know, just talk about that and how that's influenced the work that the two of you are doing together. >> Absolutely. So, the business we're in is to help companies who adopt Kubernetes as an orchestration platform do it easier, faster. It's a simple story, right? Everybody is using Kubernetes, but it turns out that Kubernetes is actually not that easy to to operationalize, playing in a sandbox is one thing. Operationalizing this at a certain level of scale is not easy. Now, we have a lot of enterprise customers who are deploying their own applications on Kubernetes, and we've had many, many of them. But when it comes to a company like Elation, it's a more complicated problem set because they're taking a very complex application, their application, but then they're providing that as a service to their customers. So then we have a chain of customers we have to make happy. Anant's team, the platform organization, his internal customers who are the developers who are deploying applications, and then, the company has customers, we have to make sure that they get a good experience as they consume this application that happens to be running on Kubernetes. So that presented a really interesting challenge, right? How do we make this partnership successful? So I will say that, we've learned a lot from each other, right? And, end of the day, the goal is, my customer, Anant's specifically, right? He has to feel that, this investment, 'cause he has to pay us money, we would like to get paid. >> John: Sure. (John laughs) >> It reduces his internal expenditure because otherwise he'd have to do it himself. And most importantly, it's not the money part, it's that he can get to a certain goalpost significantly faster because the invention time for Kubernetes management, the platform that you have to build to run Kubernetes is a very complex exercise. It took us four and a half years to get here. You want to do that again, as a company, right? Why? Why do you want to do that? We, as Rafay, the way I think about what we deliver, yes, we sell a product, but to what end? The product is the what, the why, is that every enterprise, every ISV is building a Kubernetes platform in house. They shouldn't, they shouldn't need to. They should be able to consume that as a service. They consume the Kubernetes engine the EKS is Amazon's Kubernetes, they consume that as an engine. But the management layer was a gap in the market. How do I operationalize Kubernetes? And what we are doing is we're going to, you know, the Anant said. So the warden saying, "Hey you, your team is technical, you understand the problem set. Would you like to build it or would you rather consume this as a service so you can go faster?" And, resoundingly the answer is, I don't want to do this anymore. I wouldn't allow to buy. >> Well, you know, as Haseeb is saying, speed is again, when we started talking, it only took us like a couple of months to figure out if Rafay is the right solution for us. And so we ended up purchasing Rafay in April. We launched our product based on Rafay in Kubernetes, in EKS in August. >> August. >> So that's about four months. I've done some things like this before. It takes a couple of years just to sort of figure out, how do you really work with Kubernetes, right? In a production at a large scale. Right now, we are running about a 600 node cluster on Rafay and that's serving our customers. Like, one of the biggest thing that's actually happening on December 8th is we are running what we call a virtual hands on lab. >> A virtual? >> Hands on lab. >> Okay. >> For Elation. And they're probably going to be about 500 people is going to be attending it. It's like a webinar style. But what we do in that hands on lab is we will spin up an Elation instance for each attendee, right on the spot. Okay? Now, think about this enterprise software running and people just sign up for it and it's there for you, right on the spot. And that's the beauty of the software that we have been building. There's the beauty of the work that Rafay has helped us to do over the last few months. >> Okay. >> I think we need to charge them more money, I'm getting from this congregation. I'm going to go work on that. >> I'm going to let the two of you work that out later. All right. I don't want to get in the way of a big deal. But you mentioned that, we heard about it earlier that, it's you that would offer to your cert, to your clients, these services. I assume they have their different levels of tolerance and their different challenges, right? They've got their own complexities and their own organizational barriers. So how are you juggling that end of it? Because you're kind of learning as, well, not learning, but you're experiencing some of the thing. >> Right. Same things. And yet you've got this other client base that has a multitude of experiences that they're going through. >> Right. So I think, you know a lot of our customers, they are large enterprise companies. They got a whole bunch of data that they want work with us. So one of the thing that we have learned over the past few years is that we used to actually ship our software to the customers and then they would manage it for their privacy security reasons. But now, since we're running in the cloud, they're really happy about that because they don't need to juggle with the infrastructure and the software management and upgrades and things like that, we do it for them, right? And, that's the speed for them because now they are only interested in solving the problems with the data that they're working with. They don't need to deal with all these software management issues, right? So that frees our customers up to do the thing that they want to do. Of course it makes our job harder and I'm sure in turn it makes his job harder. >> We get a short end of the stick, for sure. >> That's why he is going to get more money. >> Exactly. >> Yeah, this is a great conversation. >> No, no, no. We'll talk about that. >> So, let's talk about the cloud then. How, in terms of being the platform where all this is happening and AWS, about your relationship with them as part of the startup program and what kind of value that brings to you, what does that do for you when you go out and are looking for work and what kind of cache that brings to you >> Talk about the AWS? >> Yes, sir. >> Okay. Well, so, the thing is really like of course AWS, a lot of programs in terms of making sure that as we move our customers into AWS, they can give us some, I wouldn't call it discount, but there's some credits that you can get as you move your workloads onto AWS. So that's a really great program. Our customers love it. They want us to do more things with AWS. It's a pretty seamless way for us to, as we were talking about or thinking about moving into the cloud, AWS was our number one choice and that's the only cloud that we are in, today. We're not going to go to any other place. >> That's it. >> Yeah. >> How would you characterize? I mean, we've already heard, from one side of the fence here, but. >> Absolutely. So for us, AWS is a make or break partner, frankly. As the EKS team knows very well, we support Azure's Kubernetes and Google's Kubernetes and the community Kubernetes as well. But the number of customers on our platform who are AWS native, either a hundred percent or a large percentage is, you know, that's the majority of our customer base. >> John: Yeah. >> And AWS has made it very easy for us in a variety of ways to make us successful and our customers successful. So Anant mentioned the credit program they have which is very useful 'cause we can, you know, readily kind of bring a customer to try things out and they can do that at no cost, right? So they can spin up infrastructure, play with things and AWS will cover the cost, as one example. So that's a really good thing. Beyond that, there are multiple programs at AWS, ISV accelerate, et cetera. That, you know, you got to over time, you kind of keep getting taller and taller. And you keep getting on bigger and bigger. And as you make progress, what I'm finding is that there's a great ecosystem of support that they provide us. They introduce us to customers, they help us, you know, think through architecture issues. We get access to their roadmap. We work very, very closely with the guest team, for example. Like the, the GM for Kubernetes at AWS is a gentleman named Barry Cooks who was my sponsor, right? So, we spend a lot of time together. In fact, right after this, I'm going to be spending time with him because look, they take us seriously as a partner. They spend time with us because end of the day, they understand that if they make their partners, in this case, Rafay successful, at the end of the day helps the customer, right? Anant's customer, my customer, their AWS customers, also. So they benefit because we are collectively helping them solve a problem faster. The goal of the cloud is to help people modernize, right? Reduce operational costs because data centers are expensive, right? But then if these complex solutions this is an enterprise product, Kubernetes, at the enterprise level is a complex problem. If we don't collectively work together to save the customer effort, essentially, right? Reduce their TCO for whatever it is they're doing, right? Then the cost of the cloud is too high. And AWS clearly understands and appreciates that and that's why they are going out of their air, frankly, to make us successful and make other companies successful in the startup program. >> Well. >> I would just add a couple of things there. Yeah, so, you know, cloud is not new. It's been there for a while. You know, people used to build things on their own. And so what AWS has really done is they have advanced technology enough where everything is really simple as just turning on a switch and using it, right? So, just a recent example, and I, by the way, I love managed services, right? So the reason is really because I don't need to put my own people to build and manage those things, right? So, if you want to use a search, they got the open search, if you want to use caching, they got elastic caching and stuff like that. So it's really simple and easy to just pick and choose which services you want to use and they're ready to be consumed right away. And that's the beautiful, and that that's how we can move really fast and get things done. >> Ease of use, right? Efficiency, saving money. It's a winning combination. Thanks for sharing this story, appreciate. Anant, Haseeb thanks for being with us. >> Yeah, thank you so much having us. >> We appreciate it. >> Thank you so much. >> You have been a part of the global startup program at AWS and startup showcase. Proud to feature this great collaboration. I'm John Walls. You're watching theCUBE, which is of course the leader in high tech coverage.

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

>>Hello everyone. Welcome back to the Cube's Live coverage. I'm John Fur, host of the Cube. We got two sets here, three sets total. Another one in the executive center. It's our 10th year covering AWS Reinvent. I remember 2013 like it was yesterday. You know, now it's a massive of people buying out restaurants. 35,000 people now it's 55,000, soon to be 70,000 back. Great event. Continuing to set the standard in the industry. We had an amazing guest here, Leah Bibo, vice President of Product Marketing. She's in charge of the messaging, the product, overseeing how these products gonna market. Leah, great to see you. Thanks for joining me on the Cube today. >>Absolutely. It's great to be here. It's also my 10 reinvent, so it's, it's been a wild ride. >>Absolutely. Yeah. You and I were talking before we came on camera, how much we love products and yes, this is a product-centric company, has been from day one and you know, over the years watching the announcements, the tsunami of announcements, just all the innovation that's come out from AWS over the years has been staggering to say the least. Everyone always jokes about, oh my God, 5,000 new announcements, over 200 services you're managing and you're marketing them. It's pretty crazy right now. And Adam, as he comes on, as I called them, the solutions CEO on my piece I wrote on Friday, we're in an era where solutions, the products are enabling more solutions. Unpack the messaging around this cuz this is really big moment for aws. >>Absolutely. Well, I'll say first of all that we are a customer focused company that happens to be really good at innovating incredible products and services for our customers. So today the, the energy in the room and what Adam talked about, I think is focused on a few great things for customers that are really important for transformation. So we talked a lot about best price performance for workloads and we talked about extreme workloads, but if you think about the work that we've been doing to innovate on the silicon side, we're really talking about with Graviton all your workloads and getting really great price performance for all of them. You know, we came out with graviton three 25% faster than graviton two, also 60% more energy efficient. We talked about something that is emerging that I think is gonna be really big, which is simulation and really the ability to model these complex worlds and all the little interactions, which I think, you know, in the future as we have more complex environments like 3D simulation is gonna be a bigger part of every, every business's >>Business. You know, just as an aside, we were talking on the analyst segment that speeds and feeds are back and the old days and the data center days was like, we don't wanna talk about speeds and feeds about solutions and you know, the outcomes when you get the cloud, it was like, okay, get the workloads over there, but people want faster and lower cost performance workloads gotta be running at at high performance. And, and there's a real discussion around those. Let's unpack security data performance. What, what does that mean for customers? Because again, I get the workloads run fast. That's great. What else is behind the curtain, so to speak from a customer standpoint? >>Absolutely. Well I think if you're gonna move all your workloads to the cloud, you know, security is a really big area that's important. It's important to every one of our enterprise companies customers. Actually it's important to all of our customers and we've been working, you know, since the beginning of AWS to really create and build the most secure global infrastructure. And you know, as our customers have moved mission critical workloads, we've built out a lot more capabilities and now we have a whole portfolio of security services. And what we announced today is kind of game changing. The service called Security Lake, which brings together, you know, an ecosystem of security data in a format that's open. So you can share data between all of these sources and it's gonna give folks the opportunity to really be able to analyze data, find threats faster, and just kind of know their security posture. And I think, you know, as we talked about today, you don't wanna think about the cloud as unfathomable, the unfathomable, you really need to know that security. And I think that like a lot of things we discussed, security is a data opportunity, right? And I think we, we had a section on on data, but really if you look at the keynote across security, across solutions, across the purpose built things we made, it's all, it all comes down to data and it's really the, the transformational element that our customers >>Are. I mean the data secured is very integral part good call out there. And I, I wanna just double down on that real quick because I remember in 2014 I interviewed Steven Schmidt when he was the CSOs and back then in 2014, if you remember the conversation was this, the clouds not secure, gotta be on premises. Now in today's keynote, Adam says, and he laid out the whole global security footprint. There's a lot going on that Amazon has now become more secure than on-prem. He actually made that statement. So, and then plus you got thousands of security partners, third party partners, you got the open cyber security framework which you guys co-found with all the other, so you got securities not as a team sport, this is what they, they said yes, yes. What does that mean for customers? Because now this is a big deal. >>Well I think for customers, I mean it means nothing but goodness, right? But all of these thousands of security partners have really innovated and created solutions that our customers are using. But they all have different types of data in different silos. And to really get a full picture bringing all that data together is really important. And it's not easy today. You know, log data from different sources, data from detection services and really what customers want is an easier way to get it all together. Which is why we have the open OCS F and really analyze using the tools of their choice. And whether that's AWS tools for analytics or it's tools from our partners, customers need to be able to make that choice so that they can feel like their applications and their workloads are the most secure on aws. >>You know, I've been very impressed with guard duty and I've been following Merit Bear's blogs on online. She's in the security team, she's amazing. Shout out to her. She's been pushing guard duty for a long time now there's big news around guard duty. So you got EKS protection, you know, at Coan this was the biggest cloud native issue, the runtime of Kubernetes and inside the container and outside the container detection of threats, right? As a real software supply chain concern. How are you guys marketing that? This is a huge announcement. EKS protection I know is very nuanced but it's pretty big deal. >>It is a big deal. It is a big deal. And guard duty has been kind of like a quiet service that maybe you don't hear a lot about, but has been really, really popular with our customers. Adam mentioned that 85% of, you know, our top 2000 customers are using guard duty today. And it was a big moment. We launched EKS protection, you know, a little bit earlier and the customer uptake on that has been really incredible. And it is because you can protect your Kubernetes cluster, which is really important because so many customers are, you know, part of their migration to the cloud is containers. Yeah. And so we're pretty excited that now we can answer that question of what's going on inside the container. And so you have both, yeah, right. You know that your Kubernetes pluses are good and you know what's going on inside the container and it's just more threats that you can detect and protect >>Yourself from. You know, as an aside, I'm sure you're watching this, but you know, we go to a lot of events, you know, the C I C D pipeline as developers are getting higher velocity coding, it has moved in because of DevOps on the cloud into the C I C D pipeline. So you're seeing that developer takes some of those IT roles in the coding workflow, hence the, the shift left and or container security, which you guys now, now and are driving towards. But the security and the data teams are emerging as a very key element inside the organizational structure. When I sat down with Adam, one of the things he was very adamant about in my conversation was not just digital transformation, business transformation, structural organizational moves are making where it's not a department anymore, it is the company, a technology is the company when you transform. Absolutely. So digital is the process, business is the outcome. This is a really huge message. What's your reaction to that? What's, what can you share extra cuz that's, this is a big part of the thing. He hit it right outta the gate on the front end of the keynote. >>Absolutely. Absolutely. I mean I think, you know, companies have been migrating to the cloud for a while, but I think that this time that we're going through has really accelerated that migration And as part of that, you know, digital transformation has become real for a lot of companies. And it is true what Adam said there is technology transformation involved, there's data transformation involved, but it, it is transforming businesses. And I think if you look at some of the things that Adam talked about, you know, aws, supply chain, security Lake, aws clean rooms, and Omic, aws, omic, you know, those are all examples of data and the ability to work with data transforming different lines of business within a company, transforming horizontal processes like contact centers and like supply chain and also, you know, going into vertical specific solutions. So what it means is that as technology becomes more pervasive, as data becomes more pervasive, businesses are transforming and that means that a lot more people are going to use the cloud and interact with the cloud and they might not want to or be able to kind of use our building blocks. And so what's really exciting that what we're able to do is make cloud more accessible to lines of business folks to analysts, to security folks. So >>It's, yeah, and that's, and that's why I was calling my this this new trend I see as Amazon Classic, my words, not your words, I call the, hey there was classic cloud and then you got the next gen clown, the new next generation. And I was talking with Adrian Cockcroft, former aws, so he's now retired, he's gonna come on later today. He and I were talking, he use this thing of you got a bag of Legos aka primitives or a toy that's been assembled for you glued together, ones out of the box, but they're not mutually exclusive. You can build a durable application and foundation with the building blocks more durable. You can manage it, refine it, but you got the solution that breaks. You don't have as much flexibility but you gotta replace it. That's okay too. So like this is now kind of a new portfolio approach to the cloud. It's very interesting and I think, I think, I think that's what I took away from the keynote is that you can have both. >>Yes, absolutely. You can do both. I mean, we're gonna go full throttle on releasing innovations and pushing the envelope on compute and storage and databases and our core services because they matter. And having, you know, the choice to choose from a wide range of options. I mean that's what, that's what customers need. You know, if you're gonna run hpc, you're gonna run machine learning and you're gonna run your SAP applications or your Windows applications, you need choice of what you know, specific type of instance and compute capabilities. You need to get the price performance. It's, it's definitely not a one size fits all. It's a 600 instance type. Size fits all maybe. >>Exactly. And you got a lot of instance and we'll get to that in a second. Yeah, I love the themes. I love this keynote themes you had like at first space, but I get the whole data, then you look at it, you can look at it differently. Really good metaphor, the ocean one I love with the security because he mentioned you can have the confidence to explore go deep snorkeling versus scuba and knowing how much oxygen you have. I mean, so really cool metaphor made me think very provocative. So again, this is kind of why people go to AWS because you now have these, these abilities to do things differently, depend on the context of what products you're working with. Yes. Explain why that was the core theme. Was there any rationale behind that? Was it just how you guys saw it? I mean that was pretty clever. >>Well, I think that, you know, we're, we're talking about environments and I think in this world, you know, there's uncertainty in a lot of places and we really feel like all of us need to be prepared for different types of environments. And so we wanted to explore what that could look like. And I think, you know, we're fascinated by space and the vastness and it is very much like the world of data. I don't know about you, but I actually scuba dive. So I love the depths of the ocean. I loved working on that part. There's extremes, extreme workloads like hpc, extreme workloads like machine learning with the growing models and there's an imagination, which is also one of my favorite areas to explore. >>Yeah. And you use the Antarctica one for about the whole environment and extreme conditions. That's good in the performance. And I love that piece of it. And I want to get into the, some of the things I love the speeds and fee. I think the, the big innovation with the silicon we've been covering as, you know, like a blanket. The, he's got the GRAVITON three 25% faster than GRAVITON two, the C seven GN network intense workloads. This is kind of a big deal. I mean this is one of those things where it might not get picked up in the major press, but the network use cases are significant. Nira has been successful. Share your thoughts on these kinds of innovations because they look kind of small, but they're not, they're >>Big, they're not small for sure, especially at the scale that our customers are, are, are running their applications. Like every little optimization that you can get really makes a huge difference. And I think it's exciting. I mean you hit on, you kind of hit on it when we've been working on silicon for a while now we know that, you know, if we're gonna keep pushing the element, the envelope in these areas, we had to, we had to go down to the silicon. And I think that Nitro has really been what's kind of been a breakthrough for us. You know, reinventing that virtualization layer, offloading security and storage and networking to special purpose chips. And I think that it's not just in the area of network optimization, right? You saw training optimized instances and inference optimized instances and HPC optimized instances. So yeah, we are kind of looking at all the extremes of, of what customers want to do. >>I know you can't talk about the future, but I can almost connect the dots as you're talking. It's like, hmm, specialized instances, specialized chips, maybe programmability of workload, smart intelligence, generative AI, weaving in there. A lot of kind of cool things I can see around the corner around generative AI automation. Hey, go to this instance with that go here. This is kind of what I see kind of coming around the corner. >>And we have some of that with our instance optimizers, our cost optimizer products where, you know, we wanna help customers find the best instance for their workload, get the best utilization they possibly can, you know, cut costs, but still have the great performance. So I don't, I don't know about your future, John, it sounds great, but we have, you know, we're taking steps in that direction today. >>Still look in this code that's gonna be on this code. Okay. Any, okay, I wanna give you one final question. Well, well two questions. One was a comment Adam made, I'd love to get your reaction if you want to tighten your bell, come to the cloud. I thought that was a very interesting nuance. A lot of economic pressure. Cloud is an opportunity to get agile, time to value faster. We had Zs carve cube analyst who's with us earlier said, the more you spend on the cloud, the more you save. That was his line, which I thought was very smart. Spending more doesn't mean you're gonna lose money, means you can save money too. So a lot of cost optimization discussions. Absolutely. Hey, your belt come to the cloud. What does he mean by that? >>Well I think that in, in times where, you know, there's uncertainty and economic conditions, it is, it's really, you know, you sometimes wanna pull back kind of, you know, batten down the hatches. But the cloud really, and we saw this with C you know, if you, if you move to the cloud, not only can you cut costs, but you put yourself in this position where you can continue to innovate and you can be agile and you can be prepared for whatever environment you're in so that you know when things go back or you have a customer needs that and innovation that goes off like you, you can accelerate back up really, really quickly. And I think we talked about Airbnb, that example of how, you know, in, in that really tough time of covid when travel industry wasn't happening so much, you know, they were able to scale back and save money. And then at the same time when, you know, Airbnb's kind of once again travel came back, they were in a position to really, really quickly change with the, the customer needs. >>You know, Lee, it's always great talking with you. You got a lot of energy, you're so smart and we both love products and you're leading the product marketing. We have an Instagram challenge here on the cube. I'm gonna put you on the spot here. Oh my gosh. It's called Instagram. We called a bumper sticker section. We used to call it what's the bumper sticker for reinvent. But we kind of modernized that. If you were gonna do an Instagram reel right now, what would be the Instagram reel for reinvent Keynote day one. As we look for, we got Verner, we'll probably talk about productivity with developers. What's the Instagram reel for reinvent? >>Wow. That means I have to get short with it, right? I am, I'm not always, that's still wrong answer. Yeah, well I think, you know, this is really big day one, so it's excitement, it's, we're glad to be here. We have a lot coming for you. We're super excited. And if you think about it, it's price, performance, it's data, it's security and it's solutions for purpose-built use cases. >>Great job. Congratulations. I love the message. I love how you guys had the theme. I thought it was great. And it's great to see Amazon continue to innovate with, with the, with the, with the innovation on the product side. But as we get into transformation, starting to see these solutions and the ecosystem is thriving and looking forward to hearing the, the new partner, chief Aruba tomorrow. Absolutely. See what she's got a new plan apparently unveiling. So exciting. Everyone's pretty excited. Thanks for coming >>On. Great. Great. Thanks for having >>Me. All right. Leah, here in the cube. You are the cube, the leader in tech coverage. I'm John Fur, your host. More live coverage after the short break. We'll be right back here. Day two of the cube, day one of reinvent. Lot of great action. Three, four days of wall to wall coverage. We'll be right back.

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

(upbeat music) >> Hello, everyone and welcome back to fabulous Las Vegas, Nevada, where we are here on the show floor at AWS re:Invent. We are theCUBE. I am Savannah Peterson, joined with John Furrier. John, afternoon, day two, we are in full swing. >> Yes. >> What's got you most excited? >> Just got lunch, got the food kicking in. No, we don't get coffee. (Savannah laughing) >> Way to bring the hype there, John. >> No, there's so many people here just in Amazon. We're back to 2019 levels of crowd. The interest levels are high. Next gen, cloud security, big part of the keynote. This next segment, I am super excited about. CUBE Alumni, going back to 2013, 10 years ago he was on theCUBE. Now, 10 years later we're at re:Invent, looking forward to this guest and it's about security, great topic. >> I don't want to delay us anymore, please welcome Mark. Mark, thank you so much for being here with us. Massive day for you and the team. I know you oversee three different units at Amazon, Inspector, Detective, and the most recently announced, Security Lake. Tell us about Amazon Security Lake. >> Well, thanks Savannah. Thanks John for having me. Well, Security Lake has been in the works for a little bit of time and it got announced today at the keynote as you heard from Adam. We're super excited because there's a couple components that are really unique and valuable to our customers within Security Lake. First and foremost, the foundation of Security Lake is an open source project we call OCFS, Open Cybersecurity Framework Schema. And what that allows is us to work with the vendor community at large in the security space and develop a language where we can all communicate around security data. And that's the language that we put into Security Data Lake. We have 60 vendors participating in developing that language and partnering within Security Lake. But it's a communal lake where customers can bring all of their security data in one place, whether it's generated in AWS, they're on-prem, or SaaS offerings or other clouds, all in one location in a language that allows analytics to take advantage of that analytics and give better outcomes for our customers. >> So Adams Selipsky big keynote, he spent all the bulk of his time on data and security. Obviously they go well together, we've talked about this in the past on theCUBE. Data is part of security, but this security's a little bit different in the sense that the global footprint of AWS makes it uniquely positioned to manage some security threats, EKS protection, a very interesting announcement, runtime layer, but looking inside and outside the containers, probably gives extra telemetry on some of those supply chains vulnerabilities. This is actually a very nuanced point. You got Guard Duty kind of taking its role. What does it mean for customers 'cause there's a lot of things in this announcement that he didn't have time to go into detail. Unpack all the specifics around what the security announcement means for customers. >> Yeah, so we announced four items in Adam's keynote today within my team. So I'll start with Guard Duty for EKS runtime. It's complimenting our existing capabilities for EKS support. So today Inspector does vulnerability assessment on EKS or container images in general. Guard Duty does detections of EKS workloads based on log data. Detective does investigation and analysis based on that log data as well. With the announcement today, we go inside the container workloads. We have more telemetry, more fine grain telemetry and ultimately we can provide better detections for our customers to analyze risks within their container workload. So we're super excited about that one. Additionally, we announced Inspector for Lambda. So Inspector, we released last year at re:Invent and we focused mostly on EKS container workloads and EC2 workloads. Single click automatically assess your environment, start generating assessments around vulnerabilities. We've added Lambda to that capability for our customers. The third announcement we made was Macy sampling. So Macy has been around for a while in delivering a lot of value for customers providing information around their sensitive data within S3 buckets. What we found is many customers want to go and characterize all of the data in their buckets, but some just want to know is there any sensitive data in my bucket? And the sampling feature allows the customer to find out their sensitive data in the bucket, but we don't have to go through and do all of the analysis to tell you exactly what's in there. >> Unstructured and structured data. Any data? >> Correct, yeah. >> And the fourth? >> The fourth, Security Data Lake? (John and Savannah laughing) Yes. >> Okay, ocean theme. data lake. >> Very complimentary to all of our services, but the unique value in the data lake is that we put the information in the customer's control. It's in their S3 bucket, they get to decide who gets access to it. We've heard from customers over the years that really have two options around gathering large scale data for security analysis. One is we roll our own and we're security engineers, we're not data engineers. It's really hard for them to build these distributed systems at scale. The second one is we can pick a vendor or a partner, but we're locked in and it's in their schemer and their format and we're there for a long period of time. With Security Data Lake, they get the best of both worlds. We run the infrastructure at scale for them, put the data in their control and they get to decide what use case, what partner, what tool gives them the most value on top of their data. >> Is that always a good thing to give the customers too much control? 'Cause you know the old expression, you give 'em a knife they play with and they they can cut themselves, I mean. But no, seriously, 'cause what's the provisions around that? Because control was big part of the governance, how do you manage the security? How does the customer worry about, if I have too much control, someone makes a mistake? >> Well, what we finding out today is that many customers have realized that some of their data has been replicated seven times, 10 times, not necessarily maliciously, but because they have multiple vendors that utilize that data to give them different use cases and outcomes. It becomes costly and unwieldy to figure out where all that data is. So by centralizing it, the control is really around who has access to the data. Now, ultimately customers want to make those decisions and we've made it simple to aggregate this data in a single place. They can develop a home region if they want, where all the data flows into one region, they can distribute it globally. >> They're in charge. >> They're in charge. But the controls are mostly in the hands of the data governance person in the company, not the security analyst. >> So I'm really curious, you mentioned there's 60 AWS partner companies that have collaborated on the Security lake. Can you tell us a little bit about the process? How long does it take? Are people self-selecting to contribute to these projects? Are you cherry picking? What does that look like? >> It's a great question. There's three levels of collaboration. One is around the open source project that we announced at Black Hat early in this year called OCSF. And that collaboration is we've asked the vendor community to work with us to build a schema that is universally acceptable to security practitioners, not vendor specific and we've asked. >> Savannah: I'm sorry to interrupt you, but is this a first of its kind? >> There's multiple schemes out there developed by multiple parties. They've been around for multiple years, but they've been built by a single vendor. >> Yeah, that's what I'm drill in on a little bit. It sounds like the first we had this level of collaboration. >> There's been collaborations around them, but in a handful of companies. We've really gone to a broad set of collaborators to really get it right. And they're focused around areas of expertise that they have knowledge in. So the EDR vendors, they're focused around the scheme around EDR. The firewall vendors are focused around that area. Certainly the cloud vendors are in their scope. So that's level one of collaboration and that gets us the level playing field and the language in which we'll communicate. >> Savannah: Which is so important. >> Super foundational. Then the second area is around producers and subscribers. So many companies generate valuable security data from the tools that they run. And we call those producers the publishers and they publish the data into Security Lake within that OCSF format. Some of them are in the form of findings, many of them in the form of raw telemetry. Then the second one is in the subscriber side and those are usually analytic vendors, SIM vendors, XDR vendors that take advantage of the logs in one place and generate analytic driven outcomes on top of that, use cases, if you will, that highlight security risks or issues for customers. >> Savannah: Yeah, cool. >> What's the big customer focus when you start looking at Security Lakes? How do you see that planning out? You said there's a collaboration, love the open source vibe on that piece, what data goes in there? What's sharing? 'Cause a big part of the keynote I heard today was, I heard clean rooms, I've cut my antenna up. I'd love to hear that. That means there's an implied sharing aspect. The security industry's been sharing data for a while. What kind of data's in that lake? Give us an example, take us through. >> Well, this a number of sources within AWS, as customers run their workloads in AWS. We've identified somewhere around 25 sources that will be natively single click into Amazon Security Lake. We were announcing nine of them. They're traditional network logs, BBC flow, cloud trail logs, firewall logs, findings that are generated across AWS, EKS audit logs, RDS data logs. So anything that customers run workloads on will be available in data lake. But that's not limited to AWS. Customers run their environments hybridly, they have SaaS applications, they use other clouds in some instances. So it's open to bring all that data in. Customers can vector it all into this one single location if they decide, we make it pretty simple for them to do that. Again, in the same format where outcomes can be generated quickly and easily. >> Can you use the data lake off on premise or it has to be in an S3 in Amazon Cloud? >> Today it's in S3 in Amazon. If we hear customers looking to do something different, as you guys know, we tend to focus on our customers and what they want us to do, but they've been pretty happy about what we've decided to do in this first iteration. >> So we got a story about Silicon Angle. Obviously the ingestion is a big part of it. The reporters are jumping in, but the 53rd party sources is a pretty big number. Is that coming from the OCSF or is that just in general? Who's involved? >> Yeah, OCSF is the big part of that and we have a list of probably 50 more that want to join in part of this. >> The other big names are there, Cisco, CrowdStrike, Peloton Networks, all the big dogs are in there. >> All big partners of AWS, anyway, so it was an easy conversation and in most cases when we started having the conversation, they were like, "Wow, this has really been needed for a long time." And given our breadth of partners and where we sit from our customers perspective in the center of their cloud journey that they've looked at us and said, "You guys, we applaud you for driving this." >> So Mark, take us through the conversations you're having with the customers at re:Inforce. We saw a lot of meetings happening. It was great to be back face to face. You guys have been doing a lot of customer conversation, security Data Lake came out of that. What was the driving force behind it? What were some of the key concerns? What were the challenges and what's now the opportunity that's different? >> We heard from our customers in general. One, it's too hard for us to get all the data we need in a single place, whether through AWS, the industry in general, it's just too hard. We don't have those resources to data wrangle that data. We don't know how to pick schema. There's multiple ones out there. Tell us how we would do that. So these three challenges came out front and center for every customer. And mostly what they said is our resources are limited and we want to focus those resources on security outcomes and we have security engines. We don't want to focus them on data wrangling and large scale distributed systems. Can you help us solve that problem? And it came out loud and clear from almost every customer conversation we had. And that's where we took the challenge. We said, "Okay, let's build this data layer." And then on top of that we have services like Detective and Guard Duty, we'll take advantage of it as well. But we also have a myriad of ISV third parties that will also sit on top of that data and render out. >> What's interesting, I want to get your reaction. I know we don't have much time left, but I want to get your thoughts. When I see Security Data Lake, which is awesome by the way, love the focus, love how you guys put that together. It makes me realize the big thing in re:Invent this year is this idea of specialized solutions. You got instances for this and that, use cases that require certain kind of performance. You got the data pillars that Adam laid out. Are we going to start seeing more specialized data lakes? I mean, we have a video data lake. Is there going to be a FinTech data lake? Is there going to be, I mean, you got the Great Lakes kind of going on here, what is going on with these lakes? I mean, is that a trend that Amazon sees or customers are aligning to? >> Yeah, we have a couple lakes already. We have a healthcare lake and a financial lake and now we have a security lake. Foundationally we have Lake Formation, which is the tool that anyone can build a lake. And most of our lakes run on top of Lake Foundation, but specialize. And the specialization is in the data aggregation, normalization, enridgement, that is unique for those use cases. And I think you'll see more and more. >> John: So that's a feature, not a bug. >> It's a feature, it's a big feature. The customers have ask for it. >> So they want roll their own specialized, purpose-built data thing, lake? They can do it. >> And customer don't want to combine healthcare information with security information. They have different use cases and segmentation of the information that they care about. So I think you'll see more. Now, I also think that you'll see where there are adjacencies that those lakes will expand into other use cases in some cases too. >> And that's where the right tools comes in, as he was talking about this ETL zero, ETL feature. >> It be like an 80, 20 rule. So if 80% of the data is shared for different use cases, you can see how those lakes would expand to fulfill multiple use cases. >> All right, you think he's ready for the challenge? Look, we were on the same page. >> Okay, we have a new challenge, go ahead. >> So think of it as an Instagram Reel, sort of your hot take, your thought leadership moment, the clip we're going to come back to and reference your brilliance 10 years down the road. I mean, you've been a CUBE veteran, now CUBE alumni for almost 10 years, in just a few weeks it'll be that. What do you think is, and I suspect, I think I might know your answer to this, so feel free to be robust in this. But what do you think is the biggest story, key takeaway from the show this year? >> We're democratizing security data within Security Data Lake for sure. >> Well said, you are our shortest answer so far on theCUBE and I absolutely love and respect that. Mark, it has been a pleasure chatting with you and congratulations, again, on the huge announcement. This is such an exciting day for you all. >> Thank you Savannah, thank you John, pleasure to be here. >> John: Thank you, great to have you. >> We look forward to 10 more years of having you. >> Well, maybe we don't have to wait 10 years. (laughs) >> Well, more years, in another time. >> I have a feeling it'll be a lot of security content this year. >> Yeah, pretty hot theme >> Very hot theme. >> Pretty odd theme for us. >> Of course, re:Inforce will be there this year again, coming up 2023. >> All the res. >> Yep, all the res. >> Love that. >> We look forward to see you there. >> All right, thanks, Mark. >> Speaking of res, you're the reason we are here. Thank you all for tuning in to today's live coverage from AWS re:Invent. We are in Las Vegas, Nevada with John Furrier. My name is Savannah Peterson. We are theCUBE and we are the leading source for high tech coverage. (upbeat music)

(bright music) >> Hello, everyone. Welcome back to live coverage day two or day one, day two for theCUBE, day one for the event. I'm John Furrier, host of theCUBE. It's the keynote analysis segment. Adam just finished coming off stage. I'm here with Dave Vellante and Zeus Kerravala, with principal analyst at ZK Research, Zeus, it's great to see you. Dave. Guys, the analysis is clear. AWS is going NextGen. You guys had a multi-day analyst sessions in on the pre-briefs. We heard the keynote, it's out there. Adam's getting his sea legs, so to speak, a lot of metaphors around ocean. >> Yeah. >> Space. He's got these thematic exploration as he chunked his keynote out into sections. Zeus, a lot of networking in there in terms of some of the price performance, specialized instances around compute, this end-to-end data services. Dave, you were all over this data aspect going into the keynote and obviously, we had visibility into this business transformation theme. What's your analysis? Zeus, we'll start with you. What's your take on what Amazon web service is doing this year and the keynote? What's your analysis? >> Well, I think, there was a few key themes here. The first one is I do think we're seeing better integration across the AWS portfolio. Historically, AWS makes a lot of stuff and it's not always been easy to use say, Aurora and Redshift together, although most customers buy them together. So, they announce the integration of that. It's a lot tighter now. It's almost like it could be one product, but I know they like to keep the product development separately. Also, I think, we're seeing a real legitimization of AWS in a bunch of areas where people said it wasn't possible before. Last year, Nasdaq said they're running in the cloud. The Options Exchange today announced that they're going to be moving to the cloud. Contact centers running the cloud for a lot of real time voice. And so, things that we looked at before and said those will never move to the cloud have now moved to the cloud. And I think, my third takeaway is just AWS is changing and they're now getting into areas to allow customers to do things they couldn't do before. So, if you look at what they're doing in the area of AI, a lot of their AI and ML services before were prediction. And I'm not saying you need an AI, ML to do prediction, was certainly a lot more accurate, but now they're getting into generative data. So, being able to create data where data didn't exist before and that's a whole new use case for 'em. So, AWS, I think, is actually for all the might and power they've had, it's actually stepping up and becoming a much different company now. >> Yeah, I had wrote that post. I had a one-on-one day, got used of the transcript with Adam Selipsky. He went down that route of hey, we going to change NextGen. Oh, that's my word. AWS Classic my word. The AWS Classic, the old school cloud, which a bunch of Lego blocks, and you got this new NextGen cloud with the ecosystems emerging. So, clearly, it's Amazon shifting. >> Yeah. >> But Dave, your breaking analysis teed out the keynote. You went into the whole cost recovery. We heard Adam talk about macro at the beginning of his keynote. He talked about economic impact, sustainability, big macro issues. >> Yeah. >> And then, he went into data and spent most of the time on the keynote on data. Tools, integration, governance, insights. You're all over that. You had that, almost your breaking analysis almost matched the keynote, >> Yeah. >> thematically, macro, cost savings right-sizing with the cloud. And last night, I was talking to some of the marketplace people, we think that the marketplace might be the center where people start managing their cost better. This could have an impact on the ecosystem if they're not in in the marketplace. So, again, so much is going on. >> What's your analogy? >> Yeah, there's so much to unpack, a couple things. One is we get so much insight from theCUBE community plus your sit down 101 with Adam Selipsky allowed us to gather some nuggets, and really, I think, predict pretty accurately. But the number one question I get, if I could hit the escape key a bit, is what's going to be different in the Adam Selipsky era that was different from the Jassy era. Jassy was all about the primitives. The best cloud. And Selipsky's got to double down on that. So, he's got to keep that going. Plus, he's got to do that end-to-end integration and he's got to do the deeper business integration, up the stack, if you will. And so, when you're thinking about the keynote and the spirit of keynote analysis, we definitely heard, hey, more primitives, more database features, more Graviton, the network stuff, the HPC, Graviton for HPC. So, okay, check on that. We heard some better end-to-end integration between the elimination of ETL between Aurora and Redshift. Zeus and I were sitting next to each other. Okay, it's about time. >> Yeah. >> Okay, finally we got that. So, that's good. Check. And then, they called it this thing, the Amazon data zones, which was basically extending Redshift data sharing within your organization. So, you can now do that. Now, I don't know if it works across regions. >> Well, they mentioned APIs and they have the data zone. >> Yep. And so, I don't know if it works across regions, but the interesting thing there is he specifically mentioned integration with Snowflake and Tableau. And so, that gets me to your point, at the end of the day, in order for Amazon, and this is why they win, to succeed, they've got to have this ecosystem really cranking. And that's something that is just the secret sauce of the business model. >> Yeah. And it's their integration into that ecosystem. I think, it's an interesting trend that I've seen for customers where everybody wanted best of breed, everybody wanted disaggregated, and their customers are having trouble now putting those building blocks together. And then, nobody created more building blocks than AWS. And so, I think, under Adam, what we're seeing is much more concerted effort to make it easier for customers to consume those building blocks in an easy way. And the AWS execs >> Yeah. >> I talked to yesterday all committed to that. It's easy, easy, easy. And I think that's why. (Dave laughing) Yeah, there's no question they've had a lead in cloud for a long time. But if they're going to keep that, that needs to be upfront. >> Well, you're close to this, how easy is it? >> Yeah. >> But we're going to have Adrian Cockcroft (Dave laughing) on at the end of the day today, go into one analysis. Now, that- >> Well, less difficult. >> How's that? (indistinct) (group laughing) >> There you go. >> Adrian retired from Amazon. He's a CUBE analyst retiree, but he had a good point. You can buy the bag of Lego blocks if you want primitives >> Yeah. >> or you can buy the toy that's glued together. And it works, but it breaks. And you can't really manage it, and you buy a new one. So, his metaphor was, okay, if the primitives allow you to construct a durable solutions, a lot harder relative to rolling your own, not like that, but also the simplest out-of-the box capability is what people want. They want solutions. We call Adam the solutions CEO. So, I think, you're going to start to see this purpose built specialized services allow the ecosystem to build those toys, so that the customers can have an out-of-the box experience while having the option for the AWS Classic, which is if you want durability, you want to tune it, you want to manage it, that's the way to go for the hardcore. Now, can be foundational, but I just see the solutions things being very much like an out-of-the-box. Okay, throw away, >> Yeah. >> buy a new toy. >> More and more, I'm saying less customers want to be that hardcore assembler of building blocks. And obviously, the really big companies do, but that line is moving >> Yeah. >> and more companies, I think, just want to run their business and they want those prebuilt solutions. >> We had to cut out of the keynote early. But I didn't hear a lot about... The example that they often use is Amazon Connect, the call center solution. >> Yeah. >> I didn't hear a lot to that in the keynote. Maybe it's happening right now, but look, at the end of the day, suites always win. The best of breed does well, (John laughing) takes off, generate a couple billion, Snowflake will grow, they'll get to 10 billion. But you look at Oracle, suites work. (laughs) >> Yeah. >> What I found interesting about the keynote is that he had this thematic exploration themes. First one was space that was like connect the dot, the nebula, different (mumbles) lens, >> Ocean. >> ask the right questions. (Dave laughing) >> Ocean was security which bears more, >> Yeah. >> a lot more needed to manage that oxygen going deep. Are you snorkeling? Are you scuba diving? Barely interesting amount of work. >> In Antarctica. >> Antarctica was the performance around how you handle tough conditions and you've got to get that performance. >> Dave: We're laughing, but it was good. >> But the day, the Ocean Day- >> Those are very poetic. >> I tweeted you, Dave, (Dave laughing) because I sit on theCUBE in 2011. I hate hail. (Dave laughing) It's the worst term ever. It's the day the ocean's more dynamic. It's a lot more flowing. Maybe 10 years too soon, Dave. But he announces the ocean theme and then says we have a Security Lake. So, like lake, ocean, little fun on words- >> I actually think the Security Lake is pretty meaningful, because we were listening to talk, coming over here talking about it, where I think, if you look at a lot of the existing solutions, security solutions there, I describe 'em as a collection of data ponds that you can view through one map, but they're not really connected. And the amount of data that AWS holds now, arguably more than any other company, if they're not going to provide the Security Lake, who is? >> Well, but staying >> Yeah. >> on security for a second. To me, the big difference between Azure and Amazon is the ecosystem. So, CrowdStrike, Okta, Zscaler, name it, CyberArk, Rapid7, they're all part of this ecosystem. Whereas Microsoft competes with all of those guys. >> Yes. Yeah. >> So it's a lot more white space than the Amazon ecosystem. >> Well, I want to get you guys to take on, so in your reaction, because I think, my vision of what what's happening here is that I think that whole data portion's going to be data as code. And I think, the ecosystem harvests the data play. If you look at AWS' key announcements here, Security Lake, price performance, they're going to optimize for those kinds of services. Look at security, okay, Security Lake, GuardDuty, EKS, that's a Docker. Docker has security problems. They're going inside the container and looking at threat detection inside containers with Kubernetes as the runtime. That's a little nuance point, but that's pretty significant, Dave. And they're now getting into, we're talking in the weeds on the security piece, adding that to their large scale security footprint. Security is going to be one of those things where if you're not on the inside of their security play, you're probably going to be on the outside. And of course, the price performance is going to be the killer. The networking piece surprise me. Their continuing to innovate on the network. What does that mean for Cisco? So many questions. >> We had Ajay Patel on yesterday for VMware. He's an awesome middleware guy. And I was asking about serverless and architectures. And he said, "Look, basically, serverless' great for stateless, but if you want to run state, you got to have control over the run time." But the point he made was that people used to think of running containers with straight VMs versus Fargate or Knative, if you choose, or serverless. They used to think of those as different architectures. And his point was they're all coming together. And it's now you're architecting and calling, which service you need. And that's how people are thinking about future architectures, which I think, makes a lot of sense. >> If you are running managed Kubernetes, which everyone's doing, 'cause no one's really building it in-house themselves. >> No. >> They're running it as managed service, skills gaps and a variety of other reasons. This EKS protection is very interesting. They're managing inside and outside the container, which means that gives 'em visibility on both sides, under the hood and inside the application layer. So, very nuanced point, Zeus. What's your reaction to this? And obviously, the networking piece, I'd love to get your thought. >> Well, security, obviously, it's becoming a... It's less about signatures and more of an analytics. And so, things happen inside the container and outside the container. And so, their ability to look on both sides of that allows you to happen threats in time, but then also predict threats that could happen when you spin the container up. And the difficulty with the containers is they are ephemeral. It's not like a VM where it's a persistent workload that you can do analysis on. You need to know what's going on with the container almost before it spins up. >> Yeah. >> And that's a much different task. So, I do think the amount of work they're doing with the containers gives them that entry into that and I think, it's a good offering for them. On the network side, they provide a lot of basic connectivity. I do think there's a role still for the Ciscos and the Aristas and companies like that to provide a layer of enhanced network services that connects multicloud. 'Cause AWS is never going to do that. But they've certainly, they're as legitimate network vendor as there is today. >> We had NetApp on yesterday. They were talking about latency in their- >> I'll tell you this, the analyst session, Steven Armstrong said, "You are going to hear us talk about multicloud." Yes. We're not going to necessarily lead with it. >> Without a mention. >> Yeah. >> But you said it before, never say never with Amazon. >> Yeah. >> We talk about supercloud and you're like, Dave, ultimately, the cloud guys are going to get into supercloud. They have to. >> Look, they will do multicloud. I predict that they will do multicloud. I'll tell you why. Just like in networking- >> Well, customers are asking for it. >> Well, one, they have the, not by design, but by defaulter and multiple clouds are in their environment. They got to deal with that. I think, the supercloud and sky cloud visions, there will be common services. Remember networking back in the old days when Cisco broke in as a startup. There was no real shortest path, first thinking. Policy came in after you connected all the routers together. So, right now, it's going to be best of breed, low latency, high performance. But I think, there's going to be a need in the future saying, hey, I want to run my compute on the slower lower cost compute. They already got segmentation by their announcements today. So, I think, you're going to see policy-based AI coming in where developers can look at common services across clouds and saying, I want to lock in an SLA on latency and compute services. It won't be super fast compared to say, on AWS, with the next Graviton 10 or whatever comes out. >> Yeah. >> So, I think, you're going to start to see that come in. >> Actually, I'm glad you brought Graviton up too, because the work they're doing in Silicon, actually I think, is... 'Cause I think, the one thing AWS now understands is some things are best optimized in Silicon, some at software layers, some in cloud. And they're doing work on all those layers. And Graviton to me is- >> John: Is a home run. >> Yeah. >> Well- >> Dave, they've got more instances, it's going to be... They already have Gravitons that's slower than the other versions. So, what they going to do, sunset them? >> They don't deprecate anything ever. So, (John laughing) Amazon paid $350 million. People believe that it's a number for Annapurna, which is like one of the best acquisitions in history. (group laughing) And it's given them, it's put them on an arm curve for Silicon that is blowing away Intel. Intel's finally going to get Sapphire Rapids out in January. Meanwhile, Amazon just keeps spinning out new Gravitons and Trainiums. >> Yeah. >> And so, they are on a price performance curve. And like you say, no developer ever wants to run on slower hardware, ever. >> Today, if there's a common need for multicloud, they might say, hey, I got the trade off latency and performance on common services if that's what gets me there. >> Sure. >> If there's maybe a business case to do that. >> Well, that's what they're- >> Which by the way, I want to.... Selipsky had strong quote I thought was, "If you're looking to tighten your belt, the cloud is the place >> Yeah. >> to do it." I thought >> I tweeted that. >> that was very strong. >> Yeah. >> Yeah. >> And I think, he's right. And then, the other point I want to make on that is, I think, I don't have any data on this, but I believe believe just based on some of the discussions I've had that most of Amazon's revenue is on demand. Paid by the drink. Those on demand customers are at risk, 'cause they can go somewhere else. So, they're trying to get you into optimized pricing, whether it's reserved instances or one year or three-year subscriptions. And so, they're working really hard at doing that. >> My prediction on that is that's a great point you brought up. My prediction is that the cost belt tightening is going to come in the marketplace, is going to be a major factor as companies want to get their belts tighten. How they going to do that, Dave? They're going to go in the marketplace saying, hey, I already overpaid a three-year commitment. Can I get some cohesively in there? Can I get some of this or that and the other thing? >> Yep. >> You're going to start to see the vendors and the ecosystem. If they're not in the marketplace, that's where I think, the customers will go. There are other choices to either cut their supplier base or renegotiate. I think, it's going to happen in the marketplace. Let's watch. I think, we're going to watch that grow. >> I actually think the optimization services that AWS has to help customers lower spend is a secret sauce for them that they... Customers tell me all the time, AWS comes in, they'll bring their costs down and they wind up spending more with them. >> Dave: Yeah. >> And the other cloud providers don't do that. And that has been almost a silver bullet for them to get customers to stay with them. >> Okay. And this is always the way. You drop the price of storage, you drop the price of memory, you drop the price of compute, people buy more. And in the question, long term is okay. And does AWS get commoditized? Is that where they're going? Or do they continue to thrive up the stack? John, you're always asking people about the bumper sticker. >> Hold on. (John drowns out Dave) Before we get the bumper sticker, I want to get into what we missed, what they missed on the keynote. >> Yeah, there are some blind spots. >> I think- >> That's good call. >> Let's go around the horn and think what did they miss? I'll start, I think, they missed the developer productivity angle. Supply chain software was not talked about at all. We see that at all the other conferences. I thought that could have been weaved in. >> Dave: You mean security in the supply chain? >> Just overall developer productivity has been one of the most constant themes I've seen at events. Who are building the apps? Who are the builders? What are they actually doing? Maybe Werner will bring that up on his last day, but I didn't hear Adam talk about it all, developer productivity. What's your take in this? >> Yeah, I think, on the security side, they announced security data lake. I think, the other cloud providers do a better job of providing insights on how they do security. With AWS, it's almost a black hole. And I know there's a careful line they walk between what they do, what their partners do. But I do think they could be a little clearer on how they operate, much like Azure and GCP. They announce a lot of stuff on how their operations works and things like that. >> I think, platform across cloud is definitely a blind spot for these guys. >> Yeah. >> I think, look at- >> But none of the cloud providers have embraced that, right? >> It's true. >> Yeah. >> Maybe Google a little bit >> Yeah. >> and Microsoft a little bit. Certainly, AWS hasn't at this point in time, but I think, they perceive the likes of Mongo and Snowflake and Databricks, and others as ISVs and they're not. They're platform players that are building across clouds. They're leveraging, they're building superclouds. So, I think that's an opportunity for the ecosystem. And very curious to see how Amazon plays there down the stream. So, John, what do you think is the bumper sticker? We're only in day one and a half here. What do you think so far the bumper sticker is for re:Invent 2022? >> Well, to me, the day one is about infrastructure performance with the whole what's in the data center? What's at the chip level? Today was about data, specialized services, and security. I think that was the key theme here. And then, that's going to sequence into how they're going to reorganize their ecosystem. They have a new leader, Ruba Borno, who's going to be leading the charge. They've integrated all their bespoke fragmented partner network pieces into one leadership. That's going to be really important to hear that. And then, finally, Werner for developers and event-based services, micro services. What that world's going on, because that's where the developers are. And ultimately, they build the app. So, you got infrastructure, data, specialized services, and security. Machine learning with Swami is going to be huge. And again, how do developers code it all up is going to be key. And is it the bag of Legos or the glued toy? (Dave chuckles) So, what do you want? Out-of-the-box or you want to build your own? >> And that's the bottom line is connecting those dots. All they got to be is good enough. I think, Zeus, to your point, >> Yep. >> if they're just good enough, less complicated, the will keep people on the base. >> Yeah. I think, the bumper stickers, the more you buy, the more you're saving. (John laughing) Because from an operational perspective, they are trying to bring down the complexity level. And with their optimization services and the way their credit model works, I do think they're trending down that path. >> And my bumper sticker's ecosystem, ecosystem, ecosystem. This company has 100,000 partners and that is a business model secret weapon. >> All right, there it is. The keynote announced. More analysis coming up. We're going to have the leader of (indistinct) coming up next, here on to break down their perspective, you got theCUBE's analyst perspective here. Thanks for watching. Day two, more live coverage for the next two more days, so stay with us. I'm John Furrier with Dave Vellante and Zeus Kerravala here on theCUBE. Be right back. (bright music)

>>Hello everyone. Welcome back to the Cube Live, AWS Reinvent 2022. This is our first day of three and a half days of wall to wall coverage on the cube. Lisa Martin here with Dave Valante. Dave, it's getting louder and louder behind us. People are back. They're excited. >>You know what somebody told me today? Hm? They said that less than 15% of the audience is developers. I'm like, no way. I don't believe it. But now maybe there's a redefinition of developers because it's all about the data and it's all about the developers in my mind. And that'll never change. >>It is. And one of the things we're gonna be talking about is app modernization. As customers really navigate the journey to do that so that they can be competitive and, and meet the demands of customers. We've got an alumni back with us to talk about that. AJ Patel joins us, the SVP and GM Modern Apps and Management business group at VMware. Aj, welcome back. Thank >>You. It's always great to be here, so thank you David. Good to see >>You. Isn't great. It's great to be back in person. So the VMware Tansu team here back at Reinvent on the Flow Shore Flow show floor. There we go. Talk about some of the things that you guys are doing together, innovating with aws. >>Yeah, so it's, it's great to be back after in person after multiple years and the energy level continues to amaze me. The partnership with AWS started on the infrastructure side with VMware cloud on aws. And when with tanza, we're extending it to the application space. And the work here is really about how do you make developers productive To your earlier point, it's all about developers. It's all about getting applications in production securely, safely, continuously. And tanza is all about making that bridge between great applications being built, getting them deployed and running, running and operating at scale. And EKS is a dominant Kubernetes platform. And so the better together story of tanu and EKS is a great one for us, and we're excited to announce some sort of innovations in that area. >>Well, Tanu was so front and center at VMware Explorer. I wasn't at in, in VMware Explorer, Europe. Right. But I'm sure it was a similar kind of focus. When are customers choosing Tanu? Why are they choosing Tanu? What's, what's, what's the update since last August when >>We, you know, the market settled into three main use cases. One is all about developer productivity. You know, consistently we're all dealing with skill set gap issues. How do we make every developer productive, modern developer? And so 10 is all about enabling that develop productivity. And we can talk quite a bit about it. Second one is security's front and center and security's being shifted left right into how you build great software. How do you secure that through the entire supply chain process? And how do you run and operationalize secure at runtime? So we're hearing consistently about making secure software supply chain heart of what our solution is. And third one is, how do I run and operate the modern application at scale across any Kubernetes, across any cloud? These are the three teams that are continuing to get resonance and empowering. All of this is exciting. David is this formation of platform teams. I just finished a study with Bain Consulting doing some research for me. 40% of our organization now have some form of a central team that's responsive for, for we call platform engineering and building platforms to make developers productive. That is a big change since about two years ago even. So this is becoming mainstream and customers are really focusing on delivering in value to making developers productive. >>Now. And, and, and the other nuance that I see, and you kinda see it here in the ecosystem, but when you talk about your customers with platform engineering, they're actually building their, they're pointing their business. They gonna page outta aws, pointing their businesses to their customers, right? Becoming software companies, becoming cloud companies and really generating new forms of revenue. >>You know, the interesting thing is, some of my customers I would never have thought as leading edge are retailers. Yeah. And not your typical Starbucks that you get a great example. I have an auto parts company that's completely modernizing how they deliver point of sale all the way to the supply chain. All built on ES at scale. You're typically think of that a financial services or a telco leading the pack. But I'm seeing innovation in India. I'm seeing the innovation in AMEA coming out of there, across the board. Every industry is becoming a product company. A digital twin as we would call it. Yeah. And means they become software houses. Yeah. They behave more like you and I in this event versus a, a traditional enterprise. >>And they're building their own ecosystems and that ecosystem's generating data that's generating more value. And it's just this cycle. It's, >>It's a amazing, it's a flywheel. So innovation continues to grow. Talk about really unlocking the developer experience and delivering to them what they need to modernize apps to move as fast and quickly as they want to. >>So, you know, I think AWS coin this word undifferentiated heavy lifting. If you think of a typical developer today, how much effort does he have to put in before he can get a single line of code out in production? If you can take away all the complexity, typically security compliance is a big headache for them, right? Developer doesn't wanna worry about that. Infrastructure provisioning, getting all the configurations right, is a headache for them. Being able to understand what size of infrastructure or resource to use cost effectively. How do you run it operationally? Cuz the application team is responsible for the operational cost of the product or service. So these are the un you know, heavy lifting that developers want to get away from. So they wanna write great code, build great experiences. And we've always talked about frameworks a way to abstract with the complexity. And so for us, there's a massive opportunity to say, how do I simplify and take away all the heavy lifting to get an idea into production seamlessly, continuously, securely. >>Is that part of your partnership? Because you think about a aws, they're really not about frameworks, they're about primitives. I mean, Warner Vos even talks about that in his, in his speech, you know, but, but that makes it more challenging for developers. >>No, actually, if you look at some of their initial investments around proton and et cetera work, they're starting to do, they're recognized, you know, PS is a bad, bad word, but the outcomes a platform as a service offers is what everybody wants. Just talking to the AWS leaders, responsible area, he actually has a separate build team. He didn't know what to call the third team. He has a Kubernetes team, he has a serverless team and has a build team. And that build team is everything above Kubernetes to make the developer productive. Right. And the ecosystem to bring together to make that happen. So I think AWS is recognizing that primitives are great for the elite developers, but if they want to get the mass scale and adoption in the business, it, if you will, they're gonna have to provide richer set of building blocks and reduce the complex and partnership like ours. Make that a reality. And what I'm excited about is there's a clear gap here, and t's the best platform to kind of fill that gap. Well, >>And I, I think that, you know, they're gonna double down triple, I just wrote about this double down, triple down on the primitives. Yes. They have to have the best, you know, servers and storage and database. And I think the way they, they, I call it taping the seams is with the ecosystem. Correct. You know, and they, nobody has a, a better ecosystem. I mean, you guys are, you know, the, the postage child for the ecosystem and now this even exceeds that. But partnering up, that's how they >>Continue to, and they're looking for someone who's open, right? Yeah. Yeah. And so one of the first question is, you know, are you proprie or open? Because one of the things they're fighting against is the lock in. So they can find a friendly partner who is open source, led, you know, upstream committing to the code, delivering that innovation, and bring the ecosystem into orchestrated choreography. It's like singing a music, right? They're running a, running an application delivery team is like running a, a musical orchestra. There's so many moving parts here, right? How do you make them sing together? And so if Tan Zoo and our platform can help them sing and drive more of their services, it's only more valuable for them. And >>I think the partners would generally say, you know, AWS always talking about customer obsession. It's like becomes this bromine, you go, yeah, yeah. But I actually think in the field, the the sellers would say, yeah, we're gonna do what the customer, if that means we're gonna partner up. Yeah. And I think AWS's comp structure makes it sort >>Of, I learned today how, how incentives with marketplaces work. Yeah. And it is powerful. It's very powerful. Yeah. Right. So you line up the sales incentive, you line up the customer and the benefits, you line up bringing the ecosystem to drive business results and everybody, and so everybody wins. And which is what you're seeing here, the excitement and the crowd is really the whole, all boats are rising. Yeah. Yeah. Right, right. And it's driven by the fact that customers are getting true value out of it. >>Oh, absolutely. Tremendous value. Speaking of customers, give us an example of a customer story that you think really articulates the value of what Tanzi was delivering, especially making that developer experience far simpler. What are some of those big business outcomes that that delivers? >>You know, at Explorer we had the CIO of cvs and with their acquisition of Aetna and CVS Health, they're transforming the, the health industry. And they talked about the whole covid and then how they had to deliver the number of, you know, vaccines to u i and how quickly they had to deliver on that. It talked about Tanu and how they leverage, leverage a Tanza platform to get those new applications out and start to build that. And Ro was basically talking about his number one prior is how does he get his developers more productive? Number to priority? How does he make sure the apps are secure? Number three, priority, how does he do it cost effectively in the world? Particularly where we're heading towards where, you know, the budgets are gonna get tighter. So how do I move more dollars to innovation while I continue to drive more efficiency in my platform? And so cloud is the future. How does he make the best use of the cloud both for his developers and his operations team? Right? >>What's happening in serverless, I, in 2017, Andy Chassy was in the cube. He said if AWS or if Amazon had to build all over again, they would build in, in was using serverless. And that was a big quote. We've mined that for years. And as you were talking about developer productivity, I started writing down all the things developers have to do. Yep. With it, they gotta, they gotta build a container image. They said they gotta deploy an EC two instance. They gotta allocate memory, they gotta fence off the apps in a virtual machine. They gotta run the, you know, compute against the app goes, they gotta pay for all that. So, okay, what's your story on, what's the market asking for in terms of serverless? Because there's still some people who want control over the run time. Help us sift through that. >>And it really comes back to the application pattern or the type you're running. If it's a stateless application that you need to spin up and spin down. Serverless is awesome. Why would I wanna worry about scaling it up in, I wanna set up some SLAs, SLIs service level objectives or, or, or indicators and then let the systems bring the resources I need as I need them. That's a perfect example for serverless, right? On the other hand, if you have a, a more of a workflow type application, there's a sequence, there's state, try building an application using serverless where you had to maintain state between two, two steps in the process. Not so much fun, right? So I don't think serverless is the answer for everything, but many use cases, the scale to zero is a tremendous benefit. Events happen. You wanna process something, work is done, you quietly go away. I don't wanna shut down the server started up, I want that to happen magically. So I think there's a role of serverless. So I believe Kubernetes and servers are the new runtime platform. It's not one or the other. It's about marrying that around the application patterns. I DevOps shouldn't care about it. That's an infrastructure concern. Let me just run application, let the infrastructure manage the operations of it, whether it's serverless, whether it's Kubernetes clusters, whether it's orchestration, that's details right. I I I shouldn't worry about it. Right. >>So we shouldn't think of those as separate architectures. We should think of it as an architecture, >>The continuum in some ways Yeah. Of different application workload types. And, and that's a toolkit that the operator has at his disposal to configure and saying, where does, should that application run? Should I want control? You can run it on a, a conveyance cluster. Can I just run it on a serverless infrastructure and and leave it to the cloud provider? Do it all for me. Sure. What, what was PAs? PAs was exactly that. Yeah. Yeah. Write the code once you do the rest. Yeah. Okay. Those are just elements of that. >>And then K native is kinda in the middle, >>Right? K native is just a technology that's starting to build that capability out in a standards way to make serverless available consistently across all clouds. So I'm not building to a, a lambda or a particular, you know, technology type. I'm building it in a standard way, in a standard programming model. And infrastructure just >>Works for me on any cloud. >>The whole idea portability. Consistency. >>Right. Powerful. Yep. >>What are some of the things that, that folks can expect to learn from VMware Tan to AWS this week at the >>Show? Yeah, so there's some really great announcements. First of all, we're excited to extend our, our partnership with AWS in the area of eks. What I mean by that is we traditionally, we would manage an EKS cluster, you visibility of what's running in there, but we weren't able to manage the lifecycle With this announcement. We can give you a full management of lifecycle of S workloads. Our customers have 400 plus EKS clusters, multiple teams sharing those in a multi-tenanted way with common policy. And they wanna manage a full life cycle, including all the upstream open source component that make up Kubernetes people. That ES is the one thing, it's a collection of a lot of open, open source packages. We're making it simple to manage it consistently from a single place on the security front. We're now making tons of service mesh available in the marketplace. >>And if you look at what service MeSHs, it's an overlay. It's an abstraction. I can create an idea of a global name space that cuts across multiple VPCs. I'm, I'm hearing at Amazon's gonna make some announcements around VPC and how they stitch VPCs together. It's all moving towards this idea of abstractions. I can set policy at logical level. I don't have to worry about data security and the communication between services. These are the things we're now enabling, which are really an, and to make EKS even more productive, making enterprise grade enterprise ready. And so a lot of excitement from the EKS development teams as well to partner closely with us to make this an end to end solution for our >>Customers. Yeah. So I mean it's under chasy, it was really driving those primitives and helping developers under continuing that path, but also recognizing the need for solutions. And that's where the ecosystem comes in, >>Right? And the question is, what is that box? As you said last time, right? For the super cloud, there is a cloud infrastructure, which is becoming the new palette, but how do you make sense of the 300 plus primitives? How do you bring them together? What are the best practices, patterns? How do I manage that when something goes wrong? These are real problems that we're looking to solve. >>And if you're gonna have deeper business integration with the cloud and technology in general, you have to have that >>Abstraction. You know, one of the simple question I ask is, how do you know you're getting value from your cloud investment? That's a very hard question. What's your trade off between performance and cost? Do you know where your security, when a lock 4G happens, do you know all the open source packages you need to patch? These are very simple questions, but imagine today having to do that when everybody's doing in a bespoke manner using the set of primitives. You need a platform. The industry is shown at scale. You have to start standardizing and building a consistent way of delivering and abstracting stuff. And that's where the next stage of the cloud journey >>And, and with the economic environment, I think people are also saying, okay, how do we get more? Exactly. We're in the cloud now. How do we get more? How do we >>Value out of the cloud? >>Exactly. Totally. >>How do we transform the business? Last question, AJ for you, is, if you had a bumper sticker and you're gonna put it on your fancy car, what would it say about VMware tan zone aws? >>I would say tan accelerates apps. >>Love >>It. Thank you so much. >>Thank you. Thank you so much for joining us. >>Appreciate it. Always great to be here. >>Pleasure. Likewise. For our guest, I'm Dave Ante. I'm Lisa Martin. You're watching The Cube, the leader in emerging and enterprise tech coverage.

(upbeat techno music) >> Hello, wonderful cloud community, and welcome to theCUBE's continuing coverage of AWS re:Invent. My name is Savannah Peterson, and I am very excited to be joined by two brilliant gentlemen today. Please welcome Keith from Cockroach Labs and Jeff from AMD. Thank you both for tuning in, coming in from the East coast. How you doing? >> Not too bad. A little cold, but we're going >> Doing great. >> Love that and I love the enthusiasm Keith, you're definitely bringing the heat in the green room before we got on, so I'm going to open this up with you. Cockroach Labs puts out a pretty infamous and useful cloud report each year. Can you tell us a little bit about that, the approach and the data that you report on? >> Yeah, so Cockroach Labs builds a distributed SQL database that we are able to run across multiple cloud regions, multiple sites, multiple data centers. Frequently is running a hybrid kind of a use case and it's important for our customers to be able to compare the performance of configurations when they don't have exact the same hardware available to them in every single location. So since we were already doing this internally for ourselves and for our customers, we decided to turn it into something we shared with the greater community. And it's been a great experience for us. A lot of people come and ask us every year, "Hey, when's the new cloud report coming out?" Because they want to read it. It's been a great win for us. >> How many different things are you looking at? I mean, when you're comparing configurations I imagine there's a lot of different complex variables there. Just how much are you taking into consideration when you publish this report? >> Yeah, so we look at micro benchmarks around CPU network and storage. And then our flagship benchmark is we use the database itself where we have the most expertise to create a real world benchmark on across all of these instances. This year I think we tested over 150 different discrete configurations and it's a bit of a labor of love for us because we then not only do we consume it for best practices for our own as a service offering, but we share it with our customers. We use it internally to make all kinds of different decisions. >> Yeah, 150 different comparisons is not a small number. And Jeff, I know that AMD's position in this cloud report is really important. Where do you fit into all of this and what does it mean for you? >> Right, so what it means for us and for our customers is, there's a good breath and depth of testing that has gone of from the lab. And you look at this cloud report and it helps them traverse this landscape of, why to go on instance A, B, or C on certain workloads. And it really is very meaningful because they now have the real data across all those dimensional kinds of tests. So this definitely helps not only the customers but also for ourselves. So we can now look at ourselves more independently for feedback loops and say, "Hey, here's where we're doing well, here's where we're doing okay, here's where we need to improve on." All those things are important for us. So love seeing the lab present out such a great report as I've seen, very comprehensive, so I very much appreciate it. >> And specifically I love that you're both fans of each other, obviously, specifically digging in there, what does it mean that AMD had the best performance ratio tested on AWS instances? >> Yeah, so when we're looking at instances, we're not just looking at how fast something is, we're also looking at how much it costs to get that level of performance because CockroachDB as a distributed system has the opportunity to scale up and out. And so rather than necessarily wanting the fastest single instance performance, which is an important metric for certain use cases for sure, the comparison of price for performance when you can add notes to get more performance can be a much more economical thing for a lot of our customers. And so AMD has had a great showing on the price performance ratio for I think two years now. And it makes it hard to justify other instance types in a lot of circumstances simply because it's cheaper to get, for each transaction per second that you need, it's cheaper to use an AMD instance than it would be a competitive instance from another vendor. >> I mean, everyone I think no matter their sector wants to do things faster and cheaper and you're able to achieve both, it's easy to see why it's a choice that many folks would like to make. So what do these results mean for CIOs and CTOs? I can imagine there's a lot of value here in the FinOps world. >> Yep. Oh, I'll start a few of 'em. So from the C-suite when they're really looking at the problem statement, think of it as less granular, but higher level. So they're really looking at CapEx, OpEx, sustainability, security, sort of ecosystem on there. And then as Keith pointed out, hey, there's this TCO conversation that has to happen. In other words, as they're moving from sort of this lift and shift from their on-prem into the cloud, what does that mean to them for spend? So now if you're looking at the consistency around sort of the performance and the total cost of running this to their insights, to the conclusions, less time, more money in their pocket and maybe a reduction for their own customers so they can provide better for the customer side. What you're actually seeing is that's the challenge that they're facing in that landscape that they're driving towards that they need guidance and help with towards that. And we find AMD lends itself well to that scale out architecture that connects so well with how cloud microservices are run today. >> It's not surprising to hear that. Keith, what other tips and tricks do you have for CIOs and CTOs trying to reduce FinOps and continue to excel as they're building out? >> Yeah, so there were a couple of other insights that we learned this year. One of those two insights that I'd like to mention is that it's not always obvious what size and shape infrastructure you need to acquire to maximize your cost productions, right? So we found that smaller instance types were by and large had a better TCO than larger instances even across the exact same configurations, we kept everything else the same. Smaller instances had a better price performance ratio than the larger instances. The other thing that we discovered this year that was really interesting, we did a bit of a cost analysis on networking. And largely because we're distributed system, we can scan span across availability zones, we can span across regions, right? And one of the things we discovered this year is the amount of cost for transferring data between availability zones and the amount of cost for transferring data across regions at least in the United States was the same. So you could potentially get more resiliency by spanning your infrastructure across regions, then you would necessarily just spanning across availability zones. So you could be across multiple regions at the same cost as you were across availability zones, which for something like CockroachDB, we were designed to support those workloads is a really big and important thing for us. Now you have to be very particular about where you're purchasing your infrastructure and where those regions are. Because those data transfer rates change depending on what the source and the target is. But at least within the United States, we found that there was a strong correlation to being more survivable if you were in a multi-region deployment and the cost stayed pretty flat. >> That's interesting. So it's interesting to see what the correlation is between things and when you think there may be relationship between variables and when there maybe isn't. So on that note, since it seems like you're both always learning, I can imagine, what are you excited to test or learn about looking forward? Jeff, let's start with you actually. >> For sort of future testing. One of those things is certainly those more scale out sort of workloads with respect to showing scale. Meaning as I'm increasing the working set, as I'm increasing the number of connections, variability is another big thing of showing that minimization from run to run because performance is interesting but consistency is better. And as the lower side is from the instant sizes as I was talking about earlier, a (indistinct) architecture lends itself so well to it because they have the local caching and the CCDs that you can now put a number of vCPUs that will benefit from that delivery of the local caching and drive better performance at the lower side for that scale out sort of architecture, which is so consistent with the microservices. So I would be looking for more of those dimensional testings variability across a variety of workloads that you can go from memory intense workloads to database persistence store as well as a blend of the two, Kafka, et cetera. So there's a great breath and depth of testing that I am looking for and to more connect with sort of the CTOs and CIOs, the higher level that really show them that that CapEx, OpEx, sustainability and provide a bit more around that side of it because those are are the big things that they're focused on as well as security, the fact that based on working sets et cetera, AMD has the ability with confidential compute around those kind of offerings that can start to drive to those outcomes and help from what the CTOs and CIOs are looking for from compliance as well. So set them out (indistinct). >> So you're excited about a lot. No, that's great. That means you're very excited about the future. >> It's a journey that continues as Keith knows, there's always something new. >> Yeah, absolutely. What about you Keith? What is the most excited on the journey? >> Yeah, there are a couple of things I'd like to see us test next year. One of those is to test a multi-region CockroachDB config. We have a lot of customers running in that configuration and production but we haven't scaled that testing up to the same breadth that we we do with our single region testing which is what we've based the cloud report on for the past four years. The other thing that I'd really love to see us do,, I'm a Kubernetes SME, at least that's kind of my technical background. I would love to see us get to a spot where we're comparing the performance of raw EC2 instances to using that same infrastructure running CockroachDB via EKS and kind of see what the differences are there. The vast majority of CockroachDB customers are running at least a portion of their infrastructure in Kubernetes. So I feel like that would be a real great value add to the report for the next time that we go around but go about publishing it. >> If I don't mind adding to that just to volley it back for a moment. And also as I was saying about the ScaleOut and how it leverages our AMD architecture so well with EKS specifically around the spin up, spin down. So you think of a whole development life cycle. As they grow and shrink the resources over time, time of those spin ups to spin downs are expensive. So that has to be as reduced as much as possible. And I think they'll see a lot of benefits in AMD's architecture with EKS running on it as well. >> The future is bright. There's a lot of hype about many of the technologies that you both just mentioned, so I'm very curious to see what the next cloud report looks like. Thank you Keith, and the team for the labor of love that you put into that every year. And Jeff, I hope that you continue to be as well positioned as everyone's innovation journey continues. Keith and Jeff, thank you so much for being on the show with us today. As you know, this is a continuation of our coverage of AWS re:Invent here on theCUBE. My name's Savannah Peterson and we'll see you for our next fascinating segment. (upbeat music)

(lively music) >> Good morning. Welcome back to theCUBE's coverage at Supercomputing Conference 2022, live here in Dallas. I'm Dave Nicholson with my co-host Paul Gillin. So far so good, Paul? It's been a fascinating morning Three days in, and a fascinating guest, Ian from AWS. Welcome. >> Thanks, Dave. >> What are we going to talk about? Batch computing, HPC. >> We've got a lot, let's get started. Let's dive right in. >> Yeah, we've got a lot to talk about. I mean, first thing is we recently announced our batch support for EKS. EKS is our Kubernetes, managed Kubernetes offering at AWS. And so batch computing is still a large portion of HPC workloads. While the interactive component is growing, the vast majority of systems are just kind of fire and forget, and we want to run thousands and thousands of nodes in parallel. We want to scale out those workloads. And what's unique about our AWS batch offering, is that we can dynamically scale, based upon the queue depth. And so customers can go from seemingly nothing up to thousands of nodes, and while they're executing their work they're only paying for the instances while they're working. And then as the queue depth starts to drop and the number of jobs waiting in the queue starts to drop, then we start to dynamically scale down those resources. And so it's extremely powerful. We see lots of distributed machine learning, autonomous vehicle simulation, and traditional HPC workloads taking advantage of AWS Batch. >> So when you have a Kubernetes cluster does it have to be located in the same region as the HPC cluster that's going to be doing the batch processing, or does the nature of batch processing mean, in theory, you can move something from here to somewhere relatively far away to do the batch processing? How does that work? 'Cause look, we're walking around here and people are talking about lengths of cables in order to improve performance. So what does that look like when you peel back the cover and you look at it physically, not just logically, AWS is everywhere, but physically, what does that look like? >> Oh, physically, for us, it depends on what the customer's looking for. We have workflows that are all entirely within a single region. And so where they could have a portion of say the traditional HPC workflow, is within that region as well as the batch, and they're saving off the results, say to a shared storage file system like our Amazon FSx for Lustre, or maybe aging that back to an S3 object storage for a little lower cost storage solution. Or you can have customers that have a kind of a multi-region orchestration layer to where they say, "You know what? "I've got a portion of my workflow that occurs "over on the other side of the country "and I replicate my data between the East Coast "and the West Coast just based upon business needs. "And I want to have that available to customers over there. "And so I'll do a portion of it in the East Coast "a portion of it in the West Coast." Or you can think of that even globally. It really depends upon the customer's architecture. >> So is the intersection of Kubernetes with HPC, is this relatively new? I know you're saying you're, you're announcing it. >> It really is. I think we've seen a growing perspective. I mean, Kubernetes has been a long time kind of eating everything, right, in the enterprise space? And now a lot of CIOs in the industrial space are saying, "Why am I using one orchestration layer "to manage my HPC infrastructure and another one "to manage my enterprise infrastructure?" And so there's a growing appreciation that, you know what, why don't we just consolidate on one? And so that's where we've seen a growth of Kubernetes infrastructure and our own managed Kubernetes EKS on AWS. >> Last month you announced a general availability of Trainium, of a chip that's optimized for AI training. Talk about what's special about that chip or what is is customized to the training workloads. >> Yeah, what's unique about the Trainium, is you'll you'll see 40% price performance over any other GPU available in the AWS cloud. And so we've really geared it to be that most price performance of options for our customers. And that's what we like about the silicon team, that we're part of that Annaperna acquisition, is because it really has enabled us to have this differentiation and to not just be innovating at the software level but the entire stack. That Annaperna Labs team develops our network cards, they develop our ARM cards, they developed this Trainium chip. And so that silicon innovation has become a core part of our differentiator from other vendors. And what Trainium allows you to do is perform similar workloads, just at a lower price performance. >> And you also have a chip several years older, called Inferentia- >> Um-hmm. >> Which is for inferencing. What is the difference between, I mean, when would a customer use one versus the other? How would you move the workload? >> What we've seen is customers traditionally have looked for a certain class of machine, more of a compute type that is not as accelerated or as heavy as you would need for Trainium for their inference portion of their workload. So when they do that training they want the really beefy machines that can grind through a lot of data. But when you're doing the inference, it's a little lighter weight. And so it's a different class of machine. And so that's why we've got those two different product lines with the Inferentia being there to support those inference portions of their workflow and the Trainium to be that kind of heavy duty training work. >> And then you advise them on how to migrate their workloads from one to the other? And once the model is trained would they switch to an Inferentia-based instance? >> Definitely, definitely. We help them work through what does that design of that workflow look like? And some customers are very comfortable doing self-service and just kind of building it on their own. Other customers look for a more professional services engagement to say like, "Hey, can you come in and help me work "through how I might modify my workflow to "take full advantage of these resources?" >> The HPC world has been somewhat slower than commercial computing to migrate to the cloud because- >> You're very polite. (panelists all laughing) >> Latency issues, they want to control the workload, they want to, I mean there are even issues with moving large amounts of data back and forth. What do you say to them? I mean what's the argument for ditching the on-prem supercomputer and going all-in on AWS? >> Well, I mean, to be fair, I started at AWS five years ago. And I can tell you when I showed up at Supercomputing, even though I'd been part of this community for many years, they said, "What is AWS doing at Supercomputing?" I know you care, wait, it's Amazon Web Services. You care about the web, can you actually handle supercomputing workloads? Now the thing that very few people appreciated is that yes, we could. Even at that time in 2017, we had customers that were performing HPC workloads. Now that being said, there were some real limitations on what we could perform. And over those past five years, as we've grown as a company, we've started to really eliminate those frictions for customers to migrate their HPC workloads to the AWS cloud. When I started in 2017, we didn't have our elastic fabric adapter, our low-latency interconnect. So customers were stuck with standard TCP/IP. So for their highly demanding open MPI workloads, we just didn't have the latencies to support them. So the jobs didn't run as efficiently as they could. We didn't have Amazon FSx for Lustre, our managed lustre offering for high performant, POSIX-compliant file system, which is kind of the key to a large portion of HPC workloads is you have to have a high-performance file system. We didn't even, I mean, we had about 25 gigs of networking when I started. Now you look at, with our accelerated instances, we've got 400 gigs of networking. So we've really continued to grow across that spectrum and to eliminate a lot of those really, frictions to adoption. I mean, one of the key ones, we had a open source toolkit that was jointly developed by Intel and AWS called CFN Cluster that customers were using to even instantiate their clusters. So, and now we've migrated that all the way to a fully functional supported service at AWS called AWS Parallel Cluster. And so you've seen over those past five years we have had to develop, we've had to grow, we've had to earn the trust of these customers and say come run your workloads on us and we will demonstrate that we can meet your demanding requirements. And at the same time, there's been, I'd say, more of a cultural acceptance. People have gone away from the, again, five years ago, to what are you doing walking around the show, to say, "Okay, I'm not sure I get it. "I need to look at it. "I, okay, I, now, oh, it needs to be a part "of my architecture but the standard questions, "is it secure? "Is it price performant? "How does it compare to my on-prem?" And really culturally, a lot of it is, just getting IT administrators used to, we're not eliminating a whole field, right? We're just upskilling the people that used to rack and stack actual hardware, to now you're learning AWS services and how to operate within that environment. And it's still key to have those people that are really supporting these infrastructures. And so I'd say it's a little bit of a combination of cultural shift over the past five years, to see that cloud is a super important part of HPC workloads, and part of it's been us meeting the the market segment of where we needed to with innovating both at the hardware level and at the software level, which we're going to continue to do. >> You do have an on-prem story though. I mean, you have outposts. We don't hear a lot of talk about outposts lately, but these innovations, like Inferentia, like Trainium, like the networking innovation you're talking about, are these going to make their way into outposts as well? Will that essentially become this supercomputing solution for customers who want to stay on-prem? >> Well, we'll see what the future lies, but we believe that we've got the, as you noted, we've got the hardware, we've got the network, we've got the storage. All those put together gives you a a high-performance computer, right? And whether you want it to be redundant in your local data center or you want it to be accessible via APIs from the AWS cloud, we want to provide that service to you. >> So to be clear, that's not that's not available now, but that is something that could be made available? >> Outposts are available right now, that have this the services that you need. >> All these capabilities? >> Often a move to cloud, an impetus behind it comes from the highest levels in an organization. They're looking at the difference between OpEx versus CapEx. CapEx for a large HPC environment, can be very, very, very high. Are these HPC clusters consumed as an operational expense? Are you essentially renting time, and then a fundamental question, are these multi-tenant environments? Or when you're referring to batches being run in HPC, are these dedicated HPC environments for customers who are running batches against them? When you think about batches, you think of, there are times when batches are being run and there are times when they're not being run. So that would sort of conjure, in the imagination, multi-tenancy, what does that look like? >> Definitely, and that's been, let me start with your second part first is- >> Yeah. That's been a a core area within AWS is we do not see as, okay we're going to, we're going to carve out this super computer and then we're going to allocate that to you. We are going to dynamically allocate multi-tenant resources to you to perform the workloads you need. And especially with the batch environment, we're going to spin up containers on those, and then as the workloads complete we're going to turn those resources over to where they can be utilized by other customers. And so that's where the batch computing component really is powerful, because as you say, you're releasing resources from workloads that you're done with. I can use those for another portion of the workflow for other work. >> Okay, so it makes a huge difference, yeah. >> You mentioned, that five years ago, people couldn't quite believe that AWS was at this conference. Now you've got a booth right out in the center of the action. What kind of questions are you getting? What are people telling you? >> Well, I love being on the show floor. This is like my favorite part is talking to customers and hearing one, what do they love, what do they want more of? Two, what do they wish we were doing that we're not currently doing? And three, what are the friction points that are still exist that, like, how can I make their lives easier? And what we're hearing is, "Can you help me migrate my workloads to the cloud? "Can you give me the information that I need, "both from a price for performance, "for an operational support model, "and really help me be an internal advocate "within my environment to explain "how my resources can be operated proficiently "within the AWS cloud." And a lot of times it's, let's just take your application a subset of your applications and let's benchmark 'em. And really that, AWS, one of the key things is we are a data-driven environment. And so when you take that data and you can help a customer say like, "Let's just not look at hypothetical, "at synthetic benchmarks, let's take "actually the LS-DYNA code that you're running, perhaps. "Let's take the OpenFOAM code that you're running, "that you're running currently "in your on-premises workloads, "and let's run it on AWS cloud "and let's see how it performs." And then we can take that back to your to the decision makers and say, okay, here's the price for performance on AWS, here's what we're currently doing on-premises, how do we think about that? And then that also ties into your earlier question about CapEx versus OpEx. We have models where actual, you can capitalize a longer-term purchase at AWS. So it doesn't have to be, I mean, depending upon the accounting models you want to use, we do have a majority of customers that will stay with that OpEx model, and they like that flexibility of saying, "Okay, spend as you go." We need to have true ups, and make sure that they have insight into what they're doing. I think one of the boogeyman is that, oh, I'm going to spend all my money and I'm not going to know what's available. And so we want to provide the, the cost visibility, the cost controls, to where you feel like, as an HPC administrator you have insight into what your customers are doing and that you have control over that. And so once you kind of take away some of those fears and and give them the information that they need, what you start to see too is, you know what, we really didn't have a lot of those cost visibility and controls with our on-premises hardware. And we've had some customers tell us we had one portion of the workload where this work center was spending thousands of dollars a day. And we went back to them and said, "Hey, we started to show this, "what you were spending on-premises." They went, "Oh, I didn't realize that." And so I think that's part of a cultural thing that, at an HPC, the question was, well on-premises is free. How do you compete with free? And so we need to really change that culturally, to where people see there is no free lunch. You're paying for the resources whether it's on-premises or in the cloud. >> Data scientists don't worry about budgets. >> Wait, on-premises is free? Paul mentioned something that reminded me, you said you were here in 2017, people said AWS, web, what are you even doing here? Now in 2022, you're talking in terms of migrating to cloud. Paul mentioned outposts, let's say that a customer says, "Hey, I'd like you to put "in a thousand-node cluster in this data center "that I happen to own, but from my perspective, "I want to interact with it just like it's "in your data center." In other words, the location doesn't matter. My experience is identical to interacting with AWS in an AWS data center, in a CoLo that works with AWS, but instead it's my physical data center. When we're tracking the percentage of IT that's that is on-prem versus off-prem. What is that? Is that, what I just described, is that cloud? And in five years are you no longer going to be talking about migrating to cloud because people go, "What do you mean migrating to cloud? "What do you even talking about? "What difference does it make?" It's either something that AWS is offering or it's something that someone else is offering. Do you think we'll be at that point in five years, where in this world of virtualization and abstraction, you talked about Kubernetes, we should be there already, thinking in terms of it doesn't matter as long as it meets latency and sovereignty requirements. So that, your prediction, we're all about insights and supercomputing- >> My prediction- >> In five years, will you still be talking about migrating to cloud or will that be something from the past? >> In five years, I still think there will be a component. I think the majority of the assumption will be that things are cloud-native and you start in the cloud and that there are perhaps, an aspect of that, that will be interacting with some sort of an edge device or some sort of an on-premises device. And we hear more and more customers that are saying, "Okay, I can see the future, "I can see that I'm shrinking my footprint." And, you can see them still saying, "I'm not sure how small that beachhead will be, "but right now I want to at least say "that I'm going to operate in that hybrid environment." And so I'd say, again, the pace of this community, I'd say five years we're still going to be talking about migrations, but I'd say the vast majority will be a cloud-native, cloud-first environment. And how do you classify that? That outpost sitting in someone's data center? I'd say we'd still, at least I'll leave that up to the analysts, but I think it would probably come down as cloud spend. >> Great place to end. Ian, you and I now officially have a bet. In five years we're going to come back. My contention is, no we're not going to be talking about it anymore. >> Okay. >> And kids in college are going to be like, "What do you mean cloud, it's all IT, it's all IT." And they won't remember this whole phase of moving to cloud and back and forth. With that, join us in five years to see the result of this mega-bet between Ian and Dave. I'm Dave Nicholson with theCUBE, here at Supercomputing Conference 2022, day three of our coverage with my co-host Paul Gillin. Thanks again for joining us. Stay tuned, after this short break, we'll be back with more action. (lively music)

(upbeat synth intro music) >> Hey everyone and welcome to Detroit, Michigan. theCUBE is live at KubeCon CloudNativeCon, North America 2022. Lisa Martin here with John Furrier. John, this event, the keynote that we got out of a little while ago was, standing room only. The Solutions hall is packed. There's so much buzz. The community is continuing to mature. They're continuing to contribute. One of the big topics is Cloud Native at Scale. >> Yeah, I mean, this is a revolution happening. The developers are coming on board. They will be running companies. Developers, structurally, will be transforming companies with just, they got to get powered somewhere. And, I think, the Cloud Native at Scale speaks to getting everything under the covers, scaling up to support developers. In this next segment, we have two Kube alumnis. We're going to talk about Cloud Native at Scale. Some of the things that need to be there in a unified architecture, should be great. >> All right, it's going to be fantastic. Let's go under the covers here, as John mentioned, two alumni with us, Madhura Maskasky joins us, co-founder of Platform9. Sirish Raghuram, also co-founder of Platform9 joins us. Welcome back to theCUBE. Great to have you guys here at KubeCon on the floor in Detroit. >> Thank you for having us. >> Thank you for having us. >> Excited to be here >> So, talk to us. You guys have some news, Madhura, give us the sneak peak. What's going on? >> Definitely, we are very excited. So, we have John, not too long ago we spoke about our very new open source project called Arlon. And, we were talking about the launch of Arlon in terms of its first release and etcetera. And, just fresh hot of the press, we, Platform9 had its 5.6 release which is its most recent release of our product. And there's a number of key interesting announcements that we'd like to share as part of that. I think, the prominent one is, Platform9 added support for EKS Kubernetes cluster management. And, so, this is part of our vision of being able to add value, no matter where you run your Kubernetes clusters, because, Kubernetes or cluster management, is increasingly becoming commodity. And, so, I think the companies that succeed are going to add value on top, and are going to add value in a way that helps end users, developers, DevOps solve problems that they encounter as they start running these environments, with a lot of scale and a lot of diversity. So, towards that, key features in the 5.6 six release. First, is the very first package release of the product online, which is the open source project that we've kicked off to do cluster and application, entire cluster management at scale. And, then there's few other very interesting capabilities coming out of that. >> I want to just highlight something and then get your thoughts on this next, this release 5.6. First of all, 5.6, it's been around for a while, five reps, but, now, more than ever, you mentioned the application in Ops. You're seeing WebAssembly trends, you're seeing developers getting more and more advanced capability. It's going to accelerate their ability to write code and compose applications. So, you're seeing a application tsunami coming. So, the pressure is okay, they're going to need infrastructure to run all that stuff. And, so, you're seeing more clusters being spun up, more intelligence trying to automate. So you got the automation, so you got the dynamic, the power dynamic of developers and then under the covers. What does 5.6 do to push the mission forward for developers? How would you guys summarize that for people watching? what's in it for them right now? >> So it's, I think going back to what you just said, right, the breadth of applications that people are developing on top of something like Kubernetes and Cloud Native, is always growing. So, it's not just a number of clusters, but also the fact that different applications and different development groups need these clusters to be composed differently. So, a certain version of the application may require some set of build components, add-ons, and operators, and extensions. Whereas, a different application may require something entirely different. And, now, you take this in an enterprise context, right. Like, we had a major media company that worked with us. They have more than 10,000 pods being used by thousands of developers. And, you now think about the breadth of applications, the hundreds of different applications being built. how do you consistently build, and compose, and manage, a large number of communities clusters with a a large variety of extensions that these companies are trying to manage? That's really what I think 5.6 is bringing to the table. >> Scott Johnston just was on here early as the CEO of Docker. He said there's more applications being pushed now than in the history of application development combined. There's more and more apps coming, more and more pressure on the system. >> And, that's where, if you go, there's this famous landscape chart of the CNCF ecosystem technologies. And, the problem that people here have is, how do they put it all together? How do they make sense of it? And, what 5.6 and Arlon and what Platform9 is doing is, it's helping you declaratively capture blueprints of these clusters, using templates, and be able to manage a small number of blueprints that helps you make order out of the chaos of these hundreds of different projects, that are all very interesting and powerful. >> So Project Arlon really helping developers produce the configuration and the deployment complexities of Kubernetes at scale. >> That's exactly right. >> Talk about the, the impact on the business side. Ease of use, what's the benefits for 5.6? What's does it turn into for a benefit standpoint? >> Yeah, I think the biggest benefit, right, is being able to do Cloud Native at Scale faster, and while still keeping a very lean Ops team that is able to spend, let's say 70 plus percent of their time, caring for your actual business bread and butter applications, and not for the infrastructure that serves it, right. If you take the analogy of a restaurant, you don't want to spend 70% of your time in building the appliances or setting up your stoves etcetera. You want to spend 90 plus percent of your time cooking your own meal, because, that is your core key ingredient. But, what happens today in most enterprises is, because, of the level of automation, the level of hands-on available tooling, being there or not being there, majority of the ops time, I would say 50, 70% plus, gets spent in making that kitchen set up and ready, right. And, that is exactly what we are looking to solve, online. >> What would a customer look like, or prospect environment look like that would be really ready for platform9? What, is it more apps being pushed, big push on application development, or is it the toil of like really inefficient infrastructure, or gaps in skills of people? What does an environment look like? So, someone needs to look at their environment and say, okay, maybe I should call platform9. What's it look like? >> So, we generally see customers fall into two ends of the barbell, I would say. One, is the advanced communities users that are running, I would say, typically, 30 or more clusters already. These are the people that already know containers. They know, they've container wise... >> Savvy teams. >> They're savvy teams, a lot of them are out here. And for them, the problem is, how do I manage the complexity at scale? Because, now, the problem is how do I scale us? So, that's one end of the barbell. The other end of the barbell, is, how do we help make Kubernetes accessible to companies that, as what I would call the mainstream enterprise. We're in Detroit in Motown, right, And, we're outside of the echo chamber of the Silicon Valley. Here's the biggest truth, right. For all the progress that we made as a community, less than 20% of applications in the enterprise today are running on Kubernetes. So, what does it take? I would say it's probably less than 10%, okay. And, what does it take, to grow that in order of magnitude? That's the other kind of customer that we really serve, is, because, we have technologies like Kube Word, which helps them take their existing applications and start adopting Kubernetes as a directional roadmap, but, while using the existing applications that they have, without refactoring it. So, I would say those are the two ends of the barbell. The early adopters that are looking for an easier way to adopt Kubernetes as an architectural pattern. And, the advanced savvy users, for whom the problem is, how do they operationally solve the complexity of managing at scale. >> And, what is your differentiation message to both of those different user groups, as you talked about in terms of the number of users of Kubernetes so far? The community groundswell is tremendous, but, there's a lot of opportunity there. You talked about some of the barriers. What's your differentiation? What do you come in saying, this is why Platform9 is the right one for you, in the both of these groups. >> And it's actually a very simple message. We are the simplest and easiest way for a new user that is adopting Kubernetes as an architectural pattern, to get started with existing applications that they have, on the infrastructure that they have. Number one. And, for the savvy teams, our technology helps you operate with greater scale, with constrained operations teams. Especially, with the economy being the way it is, people are not going to get a lot more budget to go hire a lot more people, right. So, that all of them are being asked to do more with less. And, our team, our technology, and our teams, help you do more with less. >> I was talking with Phil Estes last night from AWS. He's here, he is one of their engineer open source advocates. He's always on the ground pumping up AWS. They've had great success, Amazon Web Services, with their EKS. A lot of people adopting clusters on the cloud and on-premises. But Amazon's doing well. You guys have, I think, a relationship with AWS. What's that, If I'm an Amazon customer, how do I get involved with Platform9? What's the hook? Where's the value? What's the product look like? >> Yeah, so, and it kind of goes back towards the point we spoke about, which is, Kubernetes is going to increasingly get commoditized. So, customers are going to find the right home whether it's hyperscalers, EKS, AKS, GKE, or their own infrastructure, to run Kubernetes. And, so, where we want to be at, is, with a project like Arlon, Sirish spoke about the barbell strategy, on one end there is these advanced Kubernetes users, majority of them are running Kubernetes on AKS, right? Because, that was the easiest platform that they found to get started with. So, now, they have a challenge of running these 50 to 100 clusters across various regions of Amazon, across their DevTest, their staging, their production. And, that results in a level of chaos that these DevOps or platform... >> So you come in and solve that. >> That is where we come in and we solve that. And it, you know, Amazon or EKS, doesn't give you tooling to solve that, right. It makes it very easy for you to create those number of clusters. >> Well, even in one hyperscale, let's say AWS, you got regions and locations... >> Exactly >> ...that's kind of a super cloud problem, we're seeing, opportunity problem, and opportunity is that, on Amazon, availability zones is one thing, but, now, also, you got regions. >> That is absolutely right. You're on point John. And the way we solve it, is by using infrastructure as a code, by using GitOps principles, right? Where you define it once, you define it in a yaml file, you define exactly how for your DevTest environment you want your entire infrastructure to look like, including EKS. And then you stamp it out. >> So let me, here's an analogy, I'll throw out this. You guys are like, someone learns how to drive a car, Kubernetes clusters, that's got a couple clusters. Then once they know how to drive a car, you give 'em the sports car. You allow them to stay on Amazon and all of a sudden go completely distributed, Edge, Global. >> I would say that a lot of people that we meet, we feel like they're figuring out how to build a car with the kit tools that they have. And we give them a car that's ready to go and doesn't require them to be trying to... ... they can focus on driving the car, rather than trying to build the car. >> You don't want people to stop, once they get the progressions, they hit that level up on Kubernetes, you guys give them the ability to go much bigger and stronger. >> That's right. >> To accelerate that applications. >> Building a car gets old for people at a certain point in time, and they really want to focus on is driving it and enjoying it. >> And we got four right behind us, so, we'll get them involved. So that's... >> But, you're not reinventing the wheel. >> We're not at all, because, what we are building is two very, very differentiated solutions, right. One, is, we're the simplest and easiest way to build and run Cloud Native private clouds. And, this is where the operational complexity of trying to do it yourself. You really have to be a car builder, to be able to do this with our Platform9. This is what we do uniquely that nobody else does well. And, the other end is, we help you operate at scale, in the hyperscalers, right. Those are the two problems that I feel, whether you're on-prem, or in the cloud, these are the two problems people face. How do you run a private cloud more easily, more efficiently? And, how do you govern at scale, especially in the public clouds? >> I want to get to two more points before we run out of time. Arlon and Argo CD as a service. We previously mentioned up coming into KubeCon, but, here, you guys couldn't be more relevant, 'cause Intuit was on stage on the keynote, getting an award for their work. You know, Argo, it comes from Intuit. That ArgoCon was in Mountain View. You guys were involved in that. You guys were at the center of all this super cloud action, if you will, or open source. How does Arlon fit into the Argo extension? What is Argo CD as a service? Who's going to take that one? I want to get that out there, because, Arlon has been talked about a lot. What's the update? >> I can talk about it. So, one of the things that Arlon uses behind the scenes, is it uses Argo CD, open source Argo CD as a service, as its key component to do the continuous deployment portion of its entire, the infrastructure management story, right. So, we have been very strongly partnering with Argo CD. We, really know and respect the Intuit team a lot. We, as part of this effort, in 5.6 release, we've also put out Argo CD as a service, in its GA version, right. Because, the power of running Arlon along with Argo CD as a service, in our mind, is enabling you to run on one end, your infrastructure as a scale, through GitOps, and infrastructure as a code practices. And on the other end, your entire application fleet, at scale, right. And, just marrying the two, really gives you the ability to perform that automation that we spoke about. >> But, and avoid the problem of sprawl when you have distributed teams, you have now things being bolted on, more apps coming out. So, this is really solves that problem, mainly. >> That is exactly right. And if you think of it, the way those problems are solved today, is, kind of in disconnected fashion, which is on one end you have your CI/CD tools, like Argo CD is an excellent one. There's some other choices, which are managed by a separate team to automate your application delivery. But, that team, is disconnected from the team that does the infrastructure management. And the infrastructure management is typically done through a bunch of Terraform scripts, or a bunch of ad hoc homegrown scripts, which are very difficult to manage. >> So, Arlon changes sure, as they change the complexity and also the sprawl. But, that's also how companies can die. They're growing fast, they're adding more capability. That's what trouble starts, right? >> I think in two ways, right. Like one is, as Madhura said, I think one of the common long-standing problems we've had, is, how do infrastructure and application teams communicate and work together, right. And, you've seen Argo's really get adopted by the application teams, but, it's now something that we are making accessible for the infrastructure teams to also bring the best practices of how application teams are managing applications. You can now use that to manage infrastructure, right. And, what that's going to do is, help you ultimately reduce waste, reduce inefficiency, and improve the developer experience. Because, that's what it's all about, ultimately. >> And, I know that you just released 5.6 today, congratulations on that. Any customer feedback yet? Any, any customers that you've been able to talk to, or have early access? >> Yeah, one of our large customers is a large SaaS retail company that is B2C SaaS. And, their feedback has been that this, basically, helps them bring exactly what I said in terms of bring some of the best practices that they wanted to adopt in the application space, down to the infrastructure management teams, right. And, we are also hearing a lot of customers, that I would say, large scale public cloud users, saying, they're really struggling with the complexity of how to tame the complexity of navigating that landscape and making it consumable for organizations that have thousands of developers or more. And that's been the feedback, is that this is the first open source standard mechanism that allows them to kind of reuse something, as opposed to everybody feels like they've had to build ad hoc solutions to solve this problem so far. >> Having a unified infrastructure is great. My final question, for me, before I end up, for Lisa to ask her last question is, if you had to explain Platform9, why you're relevant and cool today, what would you say? >> If I take that? I would say that the reason why Platform9, the reason why we exist, is, putting together a cloud, a hybrid cloud strategy for an enterprise today, historically, has required a lot of DIY, a lot of building your own car. Before you can drive a car, or you can enjoy the car, you really learn to build and operate the car. And that's great for maybe a 100 tech companies of the world, but, for the next 10,000 or 50,000 enterprises, they want to be able to consume a car. And that's why Platform9 exists, is, we are the only company that makes this delightfully simple and easy for companies that have a hybrid cloud strategy. >> Why you cool and relevant? How would you say it? >> Yeah, I think as Kubernetes becomes mainstream, as containers have become mainstream, I think automation at scale with ease, is going to be the key. And that's exactly what we help solve. Automation at scale and with ease. >> With ease and that differentiation. Guys, thank you so much for joining me. Last question, I guess, Madhura, for you, is, where can Devs go to learn more about 5.6 and get their hands on it? >> Absolutely. Go to platform9.com. There is info about 5.6 release, there's a press release, there's a link to it right on the website. And, if they want to learn about Arlon, it's an open source GitHub project. Go to GitHub and find out more about it. >> Excellent guys, thanks again for sharing what you're doing to really deliver Cloud Native at Scale in a differentiated way that adds ostensible value to your customers. John, and I, appreciate your insights and your time. >> Thank you for having us. >> Thanks so much >> Our pleasure. For our guests and John Furrier, I'm Lisa Martin. You're watching theCUBE Live from Detroit, Michigan at KubeCon CloudNativeCon 2022. Stick around, John and I will be back with our next guest. Just a minute. (light synth outro music)

(upbeat music) >> Hey guys, welcome back to the show floor of KubeCon + CloudNativeCon '22 North America from Detroit, Michigan. Lisa Martin here with John Furrier. This is day one, John at theCUBE's coverage. >> CUBE's coverage. >> theCUBE's coverage of KubeCon. Try saying that five times fast. Day one, we have three wall-to-wall days. We've been talking about Kubernetes, containers, adoption, cloud adoption, app modernization all morning. We can't talk about those things without addressing security. >> Yeah, this segment we're going to hear container and Kubernetes security for modern application 'cause the enterprise are moving there. And this segment with Red Hat's going to be important because they are the leader in the enterprise when it comes to open source in Linux. So this is going to be a very fun segment. >> Very fun segment. Two guests from Red Hat join us. Please welcome Doron Caspin, Senior Principal Product Manager at Red Hat. Michael Foster joins us as well, Principal Product Marketing Manager and StackRox Community Lead at Red Hat. Guys, great to have you on the program. >> Thanks for having us. >> Thank you for having us. >> It's awesome. So Michael StackRox acquisition's been about a year. You got some news? >> Yeah, 18 months. >> Unpack that for us. >> It's been 18 months, yeah. So StackRox in 2017, originally we shifted to be the Kubernetes-native security platform. That was our goal, that was our vision. Red Hat obviously saw a lot of powerful, let's say, mission statement in that, and they bought us in 2021. Pre-acquisition we were looking to create a cloud service. Originally we ran on Kubernetes platforms, we had an operator and things like that. Now we are looking to basically bring customers in into our service preview for ACS as a cloud service. That's very exciting. Security conversation is top notch right now. It's an all time high. You can't go with anywhere without talking about security. And specifically in the code, we were talking before we came on camera, the software supply chain is real. It's not just about verification. Where do you guys see the challenges right now? Containers having, even scanning them is not good enough. First of all, you got to scan them and that may not be good enough. Where's the security challenges and where's the opportunity? >> I think a little bit of it is a new way of thinking. The speed of security is actually does make you secure. We want to keep our images up and fresh and updated and we also want to make sure that we're keeping the open source and the different images that we're bringing in secure. Doron, I know you have some things to say about that too. He's been working tirelessly on the cloud service. >> Yeah, I think that one thing, you need to trust your sources. Even if in the open source world, you don't want to copy paste libraries from the web. And most of our customers using third party vendors and getting images from different location, we need to trust our sources and we have a really good, even if you have really good scanning solution, you not always can trust it. You need to have a good solution for that. >> And you guys are having news, you're announcing the Red Hat Advanced Cluster Security Cloud Service. >> Yes. >> What is that? >> So we took StackRox and we took the opportunity to make it as a cloud services so customer can consume the product as a cloud services as a start offering and customer can buy it through for Amazon Marketplace and in the future Azure Marketplace. So customer can use it for the AKS and EKS and AKS and also of course OpenShift. So we are not specifically for OpenShift. We're not just OpenShift. We also provide support for EKS and AKS. So we provided the capability to secure the whole cloud posture. We know customer are not only OpenShift or not only EKS. We have both. We have free cloud or full cloud. So we have open. >> So it's not just OpenShift, it's Kubernetes, environments, all together. >> Doron: All together, yeah. >> Lisa: Meeting customers where they are. >> Yeah, exactly. And we focus on, we are not trying to boil the ocean or solve the whole cloud security posture. We try to solve the Kubernetes security cluster. It's very unique and very need unique solution for that. It's not just added value in our cloud security solution. We think it's something special for Kubernetes and this is what Red that is aiming to. To solve this issue. >> And the ACS platform really doesn't change at all. It's just how they're consuming it. It's a lot quicker in the cloud. Time to value is right there. As soon as you start up a Kubernetes cluster, you can get started with ACS cloud service and get going really quickly. >> I'm going to ask you guys a very simple question, but I heard it in the bar in the lobby last night. Practitioners talking and they were excited about the Red Hat opportunity. They actually asked a question, where do I go and get some free Red Hat to test some Kubernetes out and run helm or whatever. They want to play around. And do you guys have a program for someone to get start for free? >> Yeah, so the cloud service specifically, we're going to service preview. So if people sign up, they'll be able to test it out and give us feedback. That's what we're looking for. >> John: Is that a Sandbox or is that going to be in the cloud? >> They can run it in their own environment. So they can sign up. >> John: Free. >> Doron: Yeah, free. >> For the service preview. All we're asking for is for customer feedback. And I know it's actually getting busy there. It's starting December. So the quicker people are, the better. >> So my friend at the lobby I was talking to, I told you it was free. I gave you the sandbox, but check out your cloud too. >> And we also have the open source version so you can download it and use it. >> Yeah, people want to know how to get involved. I'm getting a lot more folks coming to Red Hat from the open source side that want to get their feet wet. That's been a lot of people rarely interested. That's a real testament to the product leadership. Congratulations. >> Yeah, thank you. >> So what are the key challenges that you have on your roadmap right now? You got the products out there, what's the current stake? Can you scope the adoption? Can you share where we're at? What people are doing specifically and the real challenges? >> I think one of the biggest challenges is talking with customers with a slightly, I don't want to say outdated, but an older approach to security. You hear things like malware pop up and it's like, well, really what we should be doing is keeping things into low and medium vulnerabilities, looking at the configuration, managing risk accordingly. Having disparate security tools or different teams doing various things, it's really hard to get a security picture of what's going on in the cluster. That's some of the biggest challenges that we talk with customers about. >> And in terms of resolving those challenges, you mentioned malware, we talk about ransomware. It's a household word these days. It's no longer, are we going to get hit? It's when? It's what's the severity? It's how often? How are you guys helping customers to dial down some of the risk that's inherent and only growing these days? >> Yeah, risk, it's a tough word to generalize, but our whole goal is to give you as much security information in a way that's consumable so that you can evaluate your risk, set policies, and then enforce them early on in the cluster or early on in the development pipeline so that your developers get the security information they need, hopefully asynchronously. That's the best way to do it. It's nice and quick, but yeah. I don't know if Doron you want to add to that? >> Yeah, so I think, yeah, we know that ransomware, again, it's a big world for everyone and we understand the area of the boundaries where we want to, what we want to protect. And we think it's about policies and where we enforce it. So, and if you can enforce it on, we know that as we discussed before that you can scan the image, but we never know what is in it until you really run it. So one of the thing that we we provide is runtime scanning. So you can scan and you can have policy in runtime. So enforce things in runtime. But even if one image got in a way and get to your cluster and run on somewhere, we can stop it in runtime. >> Yeah. And even with the runtime enforcement, the biggest thing we have to educate customers on is that's the last-ditch effort. We want to get these security controls as early as possible. That's where the value's going to be. So we don't want to be blocking things from getting to staging six weeks after developers have been working on a project. >> I want to get you guys thoughts on developer productivity. Had Docker CEO on earlier and since then I had a couple people messaging me. Love the vision of Docker, but Docker Hub has some legacy and it might not, has does something kind of adoption that some people think it does. Are people moving 'cause there times they want to have these their own places? No one place or maybe there is, or how do you guys see the movement of say Docker Hub to just using containers? I don't need to be Docker Hub. What's the vis-a-vis competition? >> I mean working with open source with Red Hat, you have to meet the developers where they are. If your tool isn't cutting it for developers, they're going to find a new tool and really they're the engine, the growth engine of a lot of these technologies. So again, if Docker, I don't want to speak about Docker or what they're doing specifically, but I know that they pretty much kicked off the container revolution and got this whole thing started. >> A lot of people are using your environment too. We're hearing a lot of uptake on the Red Hat side too. So, this is open source help, it all sorts stuff out in the end, like you said, but you guys are getting a lot of traction there. Can you share what's happening there? >> I think one of the biggest things from a developer experience that I've seen is the universal base image that people are using. I can speak from a security standpoint, it's awesome that you have a base image where you can make one change or one issue and it can impact a lot of different applications. That's one of the big benefits that I see in adoption. >> What are some of the business, I'm curious what some of the business outcomes are. You talked about faster time to value obviously being able to get security shifted left and from a control perspective. but what are some of the, if I'm a business, if I'm a telco or a healthcare organization or a financial organization, what are some of the top line benefits that this can bubble up to impact? >> I mean for me, with those two providers, compliance is a massive one. And just having an overall look at what's going on in your clusters, in your environments so that when audit time comes, you're prepared. You can get through that extremely quickly. And then as well, when something inevitably does happen, you can get a good image of all of like, let's say a Log4Shell happens, you know exactly what clusters are affected. The triage time is a lot quicker. Developers can get back to developing and then yeah, you can get through it. >> One thing that we see that customers compliance is huge. >> Yes. And we don't want to, the old way was that, okay, I will provision a cluster and I will do scans and find things, but I need to do for PCI DSS for example. Today the customer want to provision in advance a PCI DSS cluster. So you need to do the compliance before you provision the cluster and make all the configuration already baked for PCI DSS or HIPAA compliance or FedRAMP. And this is where we try to use our compliance, we have tools for compliance today on OpenShift and other clusters and other distribution, but you can do this in advance before you even provision the cluster. And we also have tools to enforce it after that, after your provision, but you have to do it again before and after to make it more feasible. >> Advanced cluster management and the compliance operator really help with that. That's why OpenShift Platform Plus as a bundle is so popular. Just being able to know that when a cluster gets provision, it's going to be in compliance with whatever the healthcare provider is using. And then you can automatically have ACS as well pop up so you know exactly what applications are running, you know it's in compliance. I mean that's the speed. >> You mentioned the word operator, I get triggering word now for me because operator role is changing significantly on this next wave coming because of the automation. They're operating, but they're also devs too. They're developing and composing. It's almost like a dashboard, Lego blocks. The operator's not just manually racking and stacking like the old days, I'm oversimplifying it, but the new operators running stuff, they got observability, they got coding, their servicing policy. There's a lot going on. There's a lot of knobs. Is it going to get simpler? How do you guys see the org structures changing to fill the gap on what should be a very simple, turn some knobs, operate at scale? >> Well, when StackRox originally got acquired, one of the first things we did was put ACS into an operator and it actually made the application life cycle so much easier. It was very easy in the console to go and say, Hey yeah, I want ACS my cluster, click it. It would get provisioned. New clusters would get provisioned automatically. So underneath it might get more complicated. But in terms of the application lifecycle, operators make things so much easier. >> And of course I saw, I was lucky enough with Lisa to see Project Wisdom in AnsibleFest. You going to say, Hey, Red Hat, spin up the clusters and just magically will be voice activated. Starting to see AI come in. So again, operations operator is got to dev vibe and an SRE vibe, but it's not that direct. Something's happening there. We're trying to put our finger on. What do you guys think is happening? What's the real? What's the action? What's transforming? >> That's a good question. I think in general, things just move to the developers all the time. I mean, we talk about shift left security, everything's always going that way. Developers how they're handing everything. I'm not sure exactly. Doron, do you have any thoughts on that. >> Doron, what's your reaction? You can just, it's okay, say what you want. >> So I spoke with one of our customers yesterday and they say that in the last years, we developed tons of code just to operate their infrastructure. That if developers, so five or six years ago when a developer wanted VM, it will take him a week to get a VM because they need all their approval and someone need to actually provision this VM on VMware. And today they automate all the way end-to-end and it take two minutes to get a VM for developer. So operators are becoming developers as you said, and they develop code and they make the infrastructure as code and infrastructure as operator to make it more easy for the business to run. >> And then also if you add in DataOps, AIOps, DataOps, Security Ops, that's the new IT. It seems to be the new IT is the stuff that's scaling, a lot of data's coming in, you got security. So all that's got to be brought in. How do you guys view that into the equation? >> Oh, I mean you become big generalists. I think there's a reason why those cloud security or cloud professional certificates are becoming so popular. You have to know a lot about all the different applications, be able to code it, automate it, like you said, hopefully everything as code. And then it also makes it easy for security tools to come in and look and examine where the vulnerabilities are when those things are as code. So because you're going and developing all this automation, you do become, let's say a generalist. >> We've been hearing on theCUBE here and we've been hearing the industry, burnout, associated with security professionals and some DataOps because the tsunami of data, tsunami of breaches, a lot of engineers getting called in the middle of the night. So that's not automated. So this got to get solved quickly, scaled up quickly. >> Yes. There's two part question there. I think in terms of the burnout aspect, you better send some love to your security team because they only get called when things get broken and when they're doing a great job you never hear about them. So I think that's one of the things, it's a thankless profession. From the second part, if you have the right tools in place so that when something does hit the fan and does break, then you can make an automated or a specific decision upstream to change that, then things become easy. It's when the tools aren't in place and you have desperate environments so that when a Log4Shell or something like that comes in, you're scrambling trying to figure out what clusters are where and where you're impacted. >> Point of attack, remediate fast. That seems to be the new move. >> Yeah. And you do need to know exactly what's going on in your clusters and how to remediate it quickly, how to get the most impact with one change. >> And that makes sense. The service area is expanding. More things are being pushed. So things will, whether it's a zero day vulnerability or just attack. >> Just mix, yeah. Customer automate their all of things, but it's good and bad. Some customer told us they, I think Spotify lost the whole a full zone because of one mistake of a customer because they automate everything and you make one mistake. >> It scale the failure really. >> Exactly. Scaled the failure really fast. >> That was actually few contact I think four years ago. They talked about it. It was a great learning experience. >> It worked double edge sword there. >> Yeah. So definitely we need to, again, scale automation, test automation way too, you need to hold the drills around data. >> Yeah, you have to know the impact. There's a lot of talk in the security space about what you can and can't automate. And by default when you install ACS, everything is non-enforced. You have to have an admission control. >> How are you guys seeing your customers? Obviously Red Hat's got a great customer base. How are they adopting to the managed service wave that's coming? People are liking the managed services now because they maybe have skills gap issues. So managed service is becoming a big part of the portfolio. What's your guys' take on the managed services piece? >> It's just time to value. You're developing a new application, you need to get it out there quick. If somebody, your competitor gets out there a month before you do, that's a huge market advantage. >> So you care how you got there. >> Exactly. And so we've had so much Kubernetes expertise over the last 10 or so, 10 plus year or well, Kubernetes for seven plus years at Red Hat, that why wouldn't you leverage that knowledge internally so you can get your application. >> Why change your toolchain and your workflows go faster and take advantage of the managed service because it's just about getting from point A to point B. >> Exactly. >> Well, in time to value is, you mentioned that it's not a trivial term, it's not a marketing term. There's a lot of impact that can be made. Organizations that can move faster, that can iterate faster, develop what their customers are looking for so that they have that competitive advantage. It's definitely not something that's trivial. >> Yeah. And working in marketing, whenever you get that new feature out and I can go and chat about it online, it's always awesome. You always get customers interests. >> Pushing new code, being secure. What's next for you guys? What's on the agenda? What's around the corner? We'll see a lot of Red Hat at re:Invent. Obviously your relationship with AWS as strong as a company. Multi-cloud is here. Supercloud as we've been saying. Supercloud is a thing. What's next for you guys? >> So we launch the cloud services and the idea that we will get feedback from customers. We are not going GA. We're not going to sell it for now. We want to get customers, we want to get feedback to make the product as best what we can sell and best we can give for our customers and get feedback. And when we go GA and we start selling this product, we will get the best product in the market. So this is our goal. We want to get the customer in the loop and get as much as feedback as we can. And also we working very closely with our customers, our existing customers to announce the product to add more and more features what the customer needs. It's all about supply chain. I don't like it, but we have to say, it's all about making things more automated and make things more easy for our customer to use to have security in the Kubernetes environment. >> So where can your customers go? Clearly, you've made a big impact on our viewers with your conversation today. Where are they going to be able to go to get their hands on the release? >> So you can find it on online. We have a website to sign up for this program. It's on my blog. We have a blog out there for ACS cloud services. You can just go there, sign up, and we will contact the customer. >> Yeah. And there's another way, if you ever want to get your hands on it and you can do it for free, Open Source StackRox. The product is open source completely. And I would love feedback in Slack channel. It's one of the, we also get a ton of feedback from people who aren't actually paying customers and they contribute upstream. So that's an awesome way to get started. But like you said, you go to, if you search ACS cloud service and service preview. Don't have to be a Red Hat customer. Just if you're running a CNCF compliant Kubernetes version. we'd love to hear from you. >> All open source, all out in the open. >> Yep. >> Getting it available to the customers, the non-customers, they hopefully pending customers. Guys, thank you so much for joining John and me talking about the new release, the evolution of StackRox in the last season of 18 months. Lot of good stuff here. I think you've done a great job of getting the audience excited about what you're releasing. Thank you for your time. >> Thank you. >> Thank you. >> For our guest and for John Furrier, Lisa Martin here in Detroit, KubeCon + CloudNativeCon North America. Coming to you live, we'll be back with our next guest in just a minute. (gentle music)

(uplifting music) >> Hello and welcome to The Cube, here in Palo Alto, California for a special program on cloud-native at scale, enabling next generation cloud or SuperCloud for modern application cloud-native developers. I'm John Furrier, host of The Cube. My pleasure to have here Madhura Maskasky, co-founder and VP of Product at Platform9. Thanks for coming in today for this cloud-native at scale conversation. >> Thank you for having me. >> So, cloud-native at scale, something that we're talking about because we're seeing the next level of mainstream success of containers, Kubernetes and cloud-native developers, basically DevOps in the CICD pipeline. It's changing the landscape of infrastructure as code, it's accelerating the value proposition and the SuperCloud as we call it, has been getting a lot of traction because this next generation cloud is looking a lot different, but kind of the same as the first generation. What's your view on SuperCloud as it fits to cloud-native as scales up? >> Yeah, you know, I think what's interesting, and I think the reason why SuperCloud is a really good and a really fit term for this, and I think, I know my CEO was chatting with you as well, and he was mentioning this as well, but I think there needs to be a different term than just multi-cloud or cloud. And the reason is because as cloud-native and cloud deployments have scaled, I think we've reached a point now where, instead of having the traditional data center style model where you have a few large distributors of infrastructure and workload at a few locations, I think the model is kind of flipped around, right, where you have a large number of micro sites. These micro sites could be your public cloud deployment, your private, on-prem infrastructure deployments, or it could be your edge environment, right? And every single enterprise, every single industry is moving that direction. And so you got to refer that with a terminology that indicates the scale and complexity of it. And so I think SuperCloud is an appropriate term for that. >> So, you brought a couple things I want to dig into. You mentioned edge nodes. We're seeing not only edge nodes being the next kind of area of innovation, mainly because it's just popping up everywhere. And that's just the beginning. What even know what's around the corner. You got buildings, you got IOT, OT and IT kind of coming together, but you also got this idea of regions, global infrastructure is a big part of it. I just saw some news around CloudFlare shutting down a site here. There's policies being made at scale. These new challenges there. Can you share, because you got to have edge. So, hybrid cloud is a winning formula. Everybody knows that it's a steady state. >> Madhura: Yeah. >> But across multiple clouds brings in this new un-engineered area, yet it hasn't been done yet. Spanning clouds. People say they're doing it, but you start to see the toe in the water, it's happening, it's going to happen. It's only going to get accelerated with the edge and beyond globally. So I have to ask you, what is the technical challenges in doing this? Because it's something business consequences as well, but there are technical challenges. Can you share your view on what the technical challenges are for the SuperCloud or across multiple edges and regions? >> Yeah, absolutely. So, I think, you know, in the context of this, this term of SuperCloud, I think, it's sometimes easier to visualize things in terms of two axes, right? I think on one end you can think of the scale in terms of just pure number of nodes that you have, deploy number of clusters in the Kubernetes space. And then, on the other access you would have your distribution factor, right? Which is, do you have these tens of thousands of nodes in one site or do you have them distributed across tens of thousands of sites with one node at each site? Right? And if you have just one flavor of this, there is enough complexity but potentially manageable. But when you are expanding on both these axes you really get to a point where that scale really needs some well thought out, well structured solutions to address it. Right? A combination of homegrown tooling along with your, you know, favorite distribution of Kubernetes is not a strategy that can help you in this environment. It may help you when you have one of this or when your scale is not at the level. >> Can you scope the complexity? Because I mean, I hear a lot of moving parts going on there, the technology's also getting better. We're seeing cloud-native becomes successful. There's a lot to configure, there's a lot to install. Can you scope the scale of the problem? Because about at scale, >> Madhura: Yeah. >> Challenges here. >> Yeah. Absolutely. And I think, you know, I like to call it, you know, the problem that the scale creates, you know, there's various problems, but I think one problem, one way to think about it is you know, it works on my cluster problem, right? So, you know, I come from engineering background and there's a, you know, there's a famous saying between engineers and QA and the support folks, right. Which is, it works on my laptop, which is I tested this change, everything was fantastic, it worked flawlessly on my machine, on production, it's not working. And the exact same problem now happens in these distributed environments, but at massive scale, right. Which is that, you know, developers test their applications, et cetera within the sanctity of their sandbox environments. But once you expose that change in the wild world of your production deployment, right. And the production deployment could be going at the radio cell tower at the edge location where a cluster is running there, or it could be sending, you know, these applications and having them run at my customer site where they might not have configured that cluster exactly the same way as I configured it, or they configured the cluster right. But maybe they didn't deploy the security policies or they didn't deploy the other infrastructure plugins that my app relies on. All of these various factors add their own layer of complexity. And there really isn't a simple way to solve that today. And that is just, you know, one example of an issue that happens. I think another, you know, whole new ballgame of issues come in the context of security, right? Because when you are deploying applications at scale in a distributed manner, you got to make sure someone's job is on the line to ensure that the right security policies are enforced regardless of that scale factor. So, I think that's another example of problems that occur. >> Okay. So, I have to ask about scale because there are a lot of multiple steps involved when you see the success of cloud native. You know, you see some, you know, some experimentation. They set up a cluster, say, it's containers and Kubernetes, and then you say, okay, we got this, we configure it. And then, they do it again and again, they call it day two. Some people call it day one, day two operation, whatever you call it. Once you get past the first initial thing, then you got to scale it. Then you're seeing security breaches, you're seeing configuration errors. This seems to be where the hotspot is. And when companies transition from, I got this to, oh no, it's harder than I thought at scale. Can you share your reaction to that and how you see this playing out? >> Yeah, so, you know, I think it's interesting. There's multiple problems that occur when, you know, the two factors of scale, as we talked about start expanding. I think, one of them is what I like to call the, you know, it works fine on my cluster problem, which is back in, when I was a developer, we used to call this, it works on my laptop problem, which is, you know, you have your perfectly written code that is operating just fine on your machine, your sandbox environment. But the moment it runs production, it comes back with P zeros and P ones from support teams, et cetera. And those issues can be really difficult to triage. Right. And so, in the Kubernetes environment, this problem kind of multi-folds, it goes, you know, escalates to a higher degree because you have your sandbox developer environments, they have their clusters and things work perfectly fine in those clusters because these clusters are typically handcrafted or a combination of some scripting and handcrafting. And so, as you give that change to then run at your production edge location, like say your radio cell tower site or you hand it over to a customer to run it on their cluster, they might not have configured that cluster exactly how you did, or they might not have configured some of the infrastructure plugins. And so the things don't work. And when things don't work, triaging them becomes like (indistinct) hard, right? It's just one of the examples of the problem. Another whole bucket of issues is security, which is you have these distributed clusters at scale, you got to ensure someone's job is on the line to make sure that the security policies are configured properly. >> So, this is a huge problem. I love that comment. That's not happening on my system. It's the classic, you know, debugging mentality. >> Madhura: Yeah. >> But at scale it's hard to do that with error prone. I can see that being a problem. And you guys have a solution you're launching. Can you share what Arlon is this new product? What is it all about? Talk about this new introduction. >> Yeah, absolutely. I'm very, very excited. You know, it's one of the projects that we've been working on for some time now because we are very passionate about this problem and just solving problems at scale in on-prem or at in the cloud or at edge environments. And what Arlon is, it's an open source project and it is a tool, it's a Kubernetes native tool for a complete end-to-end management of not just your clusters, but your clusters, all of the infrastructure that goes within and along the sites of those clusters, security policies, your middleware plugins, and finally your applications. So, what Arlon lets you do in a nutshell is in a declarative way, it lets you handle the configuration and management of all of these components in at scale. >> So, what's the elevator pitch simply put for what dissolves in terms of the chaos you guys are reigning in, what's the bumper sticker? >> Yeah. >> What would it do? >> There's a perfect analogy that I love to reference in this context, which is think of your assembly line, you know, in a traditional, let's say, you know, an auto manufacturing factory or et cetera, and the level of efficiency at scale that assembly line brings, right? Arlon, and if you look at the logo we've designed, it's this funny little robot, and it's because when we think of Arlon, we think of these enterprise large scale environments, you know, sprawling at scale creating chaos because there isn't necessarily a well thought through, well-structured solution that's similar to an assembly line, which is taking each component, you know, addressing them, manufacturing, processing them in a standardized way, then handing to the next stage where again, it gets, you know, processed in a standardized way. And that's what Arlon really does. That's like deliver the pitch. If you have problems of scale of managing your infrastructure, you know, that is distributed. Arlon brings the assembly line level of efficiency and consistency for those. >> So keeping it smooth, the assembly line, things are flowing, CICD, pipelining. >> Madhura: Exactly. >> So, that's what you're trying to simplify that OPS piece for the developer. I mean, it's not really OPS, it's their OPS, it's coding. >> Yeah. Not just developer, the OPS, the operations folks as well, right? Because developers, you know, there is, developers are responsible for one picture of that layer, which is my apps, and then maybe that middle layer of applications that they interface with, but then they hand it over to someone else who's then responsible to ensure that these apps are secured properly, that they are logging, logs are being collected properly, monitoring and observability is integrated. And so, it solves problems for both those teams. >> Yeah, it's DevOps. So, the DevOps is the cloud-needed developer. The option teams have to kind of set policies. Is that where the declarative piece comes in? Is that why that's important? >> Absolutely. Yeah. And, you know, Kubernetes really introduced or elevated this declarative management, right? Because you know, Kubernetes clusters are, or your, yeah, you know, specifications of components that go in Kubernetes are defined in declarative way, and Kubernetes always keeps that state consistent with your defined state. But when you go outside of that world of a single cluster, and when you actually talk about defining the clusters or defining everything that's around it, there really isn't a solution that does that today. And so Arlon addresses that problem at the heart of it, and it does that using existing open source, well-known solutions. >> And, I want get into the benefits, what's in it for me as the customer, developer, but I want to finish this out real quick and get your thoughts. You mentioned open source. Why open source? What's the current state of the product? You run the product group over there, Platform9, is it open source? And you guys have a product that's commercial. Can you explain the open-source dynamic? And first of all, why open source? >> Madhura: Yeah. >> And what is the consumption? I mean, open source is great, people want open source, they can download it, look up the code, but you know, maybe want to buy the commercial. So, I'm assuming you have that thought through, can you share? >> Madhura: Yeah. >> Open source and commercial relationship. >> Yeah. I think, you know, starting with why open source, I think, it's, you know, we as a company, we have, you know, one of the things that's absolutely critical to us is that we take mainstream open-source technologies components, and then we, you know, make them available to our customers at scale through either a SaaS model or on-prem model, right? But, so as we are a company or startup or a company that benefits, you know, in a massive way by this open-source economy, it's only right, I think in my mind that, we do our part of the duty, right? And contribute back to the community that feeds us. And so, you know, we have always held that strongly as one of our principles. And we have, you know, created and built independent products starting all the way with Fission, which was a serverless product, you know, that we had built to various other, you know, examples that I can give. But that's one of the main reasons why open source and also open source because we want the community to really firsthand engage with us on this problem, which is very difficult to achieve if your product is behind a wall, you know, behind a block box. >> Well, and that's what the developers want too. I mean, what we're seeing in reporting with SuperCloud is the new model of consumption is I want to look at the code and see what's in there. >> Madhura: That's right. >> And then also, if I want to use it, I'll do it. Great. That's open source, that's the value. But then at the end of the day, if I want to move fast, that's when people buy in. So it's a new kind of freemium, I guess, business model. I guess that's the way is, well, but that's the benefit of open source. This is why standards and open source growing so fast, you have that confluence of, you know, a way for us to try before they buy, but also actually kind of date the application, if you will. We, you know, Adrian (indistinct) uses the dating metaphor, you know, hey, you know, I want to check it out first before I get married. >> Madhura: Right. >> And that's what open source. So, this is the new, this is how people are selling. This is not just open source, this is how companies are selling. >> Absolutely. Yeah. Yeah. You know, I think in, you know, two things, I think one is just, you know, this cloud-native space is so vast that if you're building a close flow solution, sometimes there's also a risk that it may not apply to every single enterprise's use cases. And so having it open source gives them an opportunity to extend it, expand it, to make it proper to their use case if they choose to do so. Right? But at the same time, what's also critical to us is we are able to provide a supported version of it with an SLA that we, you know, that's backed by us, a Saas-hosted version of it as well, for those customers who choose to go that route, you know, once they have used the open-source version and loved it and want to take it at scale and in production and need a partner to collaborate with, who can, you know, support them for that production environment. >> I have to ask you. Now, let's get into what's in it for the customer. I'm a customer, why should I be enthused about Arlon? What's in it for me? You know. 'Cause if I'm not enthused about it, I'm not going to be confident and it's going to be hard for me to get behind this. Can you share your enthusiastic view of, you know, why I should be enthused about Arlon? I'm a customer. >> Yeah, absolutely. And so, and there's multiple, you know, enterprises that we talk to, many of them, you know, our customers, where this is a very kind of typical story that you hear, which is we have, you know, a Kubernetes distribution. It could be on premise, it could be public cloud-native Kubernetes, and then, we have our CICD pipelines that are automating the deployment of applications, et cetera. And then, there's this gray zone. And the gray zone is well before you can, your CICD pipelines can deploy the apps, somebody needs to do all of that groundwork of, you know, defining those clusters and yeah, you know, properly configuring them. And as these things start by being done hand grown. And then, as you scale, what typically enterprises would do today is they will have their homegrown DIY solutions for this. I mean, a number of folks that I talk to that have built Terraform automation, and then, you know, some of those key developers leave. So, it's a typical open source or typical, you know, DIY challenge. And the reason that they're writing it themselves is not because they want to. I mean, of course, technology is always interesting to everybody, but it's because they can't find a solution that's out there that perfectly fits the problem. And so that's that pitch. I think, (indistinct) would be delighted. The folks that we've talk, you know, spoken with, have been absolutely excited and have, you know, shared that this is a major challenge we have today because we have, you know, few hundreds of clusters on EKS Amazon, and we want to scale them to few thousands, but we don't think we are ready to do that. And this will give us the ability to, >> Yeah, I think, people are scared. I won't say scare, that's a bad word. Maybe I should say that they feel nervous because, you know, at scale, small mistakes can become large mistakes. This is something that is concerning to enterprises. And I think, this is going to come up at (indistinct) this year where enterprises are going to say, okay, I need to see SLAs. I want to see track record, I want to see other companies that have used it. >> Madhura: Yeah. >> How would you answer that question to, or challenge, you know, hey, I love this, but is there any guarantees? Is there any, what's the SLA, I'm an enterprise, I got tight, you know, I love the open source trying to free fast and loose, but I need hardened code. >> Yeah, absolutely. So, two parts to that, right? One is Arlon leverages existing open-source components, products that are extremely popular. Two specifically. One is Arlon uses ArgoCD, which is probably one of the highest rated and used CD open-source tools that's out there, right? It's created by folks that are as part of into team now, you know, really brilliant team. And it's used at scale across enterprises. That's one. Second is Arlon also makes use of cluster API (indistinct), which is a Kubernetes' sub-component, right? For life cycle management of clusters. So, there is enough of, you know, community users, et cetera, around these two products, right? Or open-source projects that will find Arlon to be right up in their alley because they're already comfortable, familiar with ArgoCD. Now, Arlon just extends the scope of what ArgoCD can do. And so, that's one. And then, the second part is going back to your point of the comfort. And that's where, you know, Platform9 has a role to play, which is when you are ready to deploy Arlon at scale, because you've been, you know, playing with it in your (indistinct) test environments, you're happy with what you get with it, then Platform9 will stand behind it and provide that SLA. >> And what's been the reaction from customers you've talked to Platform9 customers with, that are familiar with Argo and then Arlon? What's been some of the feedback? >> Yeah, I think, the feedback's been fantastic. I mean, I can give examples of customers where, you know, initially, you know, when you are telling them about your entire portfolio of solutions, it might not strike a card right away. But then we start talking about Arlon, and we talk about the fact that it uses ArgoCD they start opening up, they say, we have standardized on Argo and we have built these components, homegrown, we would be very interested. Can we co-develop? Does it support these use cases? So, we've had that kind of validation. We've had validation all the way at the beginning of Arlon before we even wrote a single line of code saying, this is something we plan on doing. And the customer said, if you had it today, I would've purchased it. So, it's been really great validation. >> All right. So, next question is, what is the solution to the customer? If I asked you, look at, I have, I'm so busy, my team's overworked. I got a skills gap, I don't need another project that's so I'm so tied up right now, and I'm just chasing my tail. How does Platform9 help me? >> Yeah, absolutely. So I think, you know, one of the core tenants of Platform9 has always been that, we try to bring that public cloud like simplicity by hosting, you know, this in a lot of such similar tools in a SaaS-hosted manner for our customers, right? So, our goal behind doing that is taking away or trying to take away all of that complexity from customer's hands and offloading it to our hands, right? And giving them that full white glove treatment as we call it. And so, from a customer's perspective, one, something like Arlon will integrate with what they have, so, they don't have to rip and replace anything. In fact, it will, even in the next versions, it may even discover your clusters that you have today, and, you know, give you an inventory. And then, >> So, customers have clusters that are growing, that's a sign, >> Correct. >> Call you guys. >> Absolutely. Either they have massive large clusters. Right. That they want to split into smaller clusters, but they're not comfortable doing that today, or they've done that already on say, public cloud or otherwise. And now, they have management challenges. >> So, especially, operationalizing the clusters, whether they want to kind of reset everything and remove things around and reconfigure >> Madhura: Yeah. >> And or scale out. >> That's right. Exactly. >> And you provide that layer of policy. >> Absolutely. Yes. >> That's the key value here. >> That's right. >> So, policy-based configuration for cluster scale up. >> Profile and policy-based, declarative configuration and life cycle management for clusters. >> If I asked you how this enables SuperCloud, what would you say to that? >> I think, this is one of the key ingredients to SuperCloud, right? If you think about a SuperCloud environment, there is at least few key ingredients that come to my mind that are really critical. Like they are, you know, life-saving ingredients at that scale. One is having a really good strategy for managing that scale. You know, in a, going back to assembly line in a very consistent, predictable way. So, that Arlon solves, then you need to compliment that with the right kind of observability and monitoring tools at scale, right? Because ultimately issues are going to happen and you're going to have to figure out, you know, how to solve them fast. And Arlon by the way, also helps in that direction, but you also need observability tools. And then, especially if you're running at on the public cloud, you need some cost management tools. In my mind, these three things are like the most necessary ingredients to make SuperCloud successful. And you know, Arlon flows in one, >> Okay, so now, the next level is, okay, that makes sense. It's under the covers kind of speak under the hood. >> Madhura: Yeah. >> How does that impact the app developers of the cloud-native modern application workflows? Because the impact to me seems the apps are going to be impacted. Are they going to be faster, stronger? I mean, what's the impact, if you do all those things as you mentioned, what's the impact of the apps? >> Yeah, the impact is that your apps are more likely to operate in production the way you expect them to, because the right checks and balances have gone through, and any discrepancies have been identified prior to those apps, prior to your customer running into them, right? Because developers run into this challenge today where there's a split responsibility, right? I'm responsible for my code, I'm responsible for some of these other plugins, but I don't own the stack end to end. I have to rely on my OPS counterpart to do their part, right? And so, this really gives them, you know, the right tooling for that. >> So, this is actually a great kind of relevant point, you know, as cloud becomes more scalable, you're starting to see this fragmentation gone of the days of the full-stack developer to the more specialized role. But this is a key point, and I have to ask you because if this Arlon solution takes place, as you say, and the apps are going to be (indistinct), they're designed to do, the question is, what does the current pain look like? Are the apps breaking? What is the signals to the customer, >> Madhura: Yeah. >> That they should be calling you guys up into implementing Arlon, Argo, and on all the other goodness to automate, what does some of the signals, is it downtime? Is it failed apps, is it latency? What are some of the things that, >> Madhura: Yeah, absolutely. >> Would be indications of things are F'ed up a little bit. >> Yeah. More frequent down times, down times that are, that take longer to triage. And so your, you know, your mean times on resolution, et cetera, are escalating or growing larger, right? Like we have environments of customers where they have a number of folks on in the field that have to take these apps and run them at customer sites. And that's one of our partners, and they're extremely interested in this because the rate of failures they're encountering for this, you know, the field when they're running these apps on site, because the field is automating their clusters that are running on sites using their own scripts. So, these are the kinds of challenges, and those are the pain points, which is, you know, if you're looking to reduce your mean time to resolution, if you're looking to reduce the number of failures that occur on your production site, that's one. And second, if you're looking to manage these at scale environments with a relatively small, focused, nimble OPS team, which has an immediate impact on your budget. So, those are the signals. >> This is the cloud-native at scale situation, the innovation going on. Final thought is your reaction to the idea that, if the world goes digital, which it is, and the confluence of physical and digital coming together, and cloud continues to do its thing, the company becomes the application, not where IT used to be supporting the business, you know, the back office and the (indistinct) terminals and some PCs and handhelds. Now, if technology's running, the business is the business. >> Yeah. >> Company is the application. >> Yeah. >> So, it can't be down. So, there's a lot of pressure on CSOs and CIOs now and boards is saying, how is technology driving the top-line revenue? That's the number one conversation. >> Yeah. >> Do you see the same thing? >> Yeah, it's interesting. I think there's multiple pressures at the CXO, CIO level, right? One is that there needs to be that visibility and clarity and guarantee almost that, you know, the technology that's, you know, that's going to drive your top line is going to drive that in a consistent, reliable, predictable manner. And then second, there is the constant pressure to do that while always lowering your costs of doing it, right? Especially, when you're talking about, let's say, retailers or those kinds of large-scale vendors, they many times make money by lowering the amount that they spend on, you know, providing those goods to their end customers. So, I think those, both those factors kind of come into play and the solution to all of them is usually in a very structured strategy around automation. >> Final question. What does cloud-native at scale look like to you? If all the things happen the way we want them to happen, the magic wand, the magic dust, what does it look like? >> What that looks like to me is a CIO sipping at his desk on coffee, production is running absolutely smooth. And he's running that at a nimble, nimble team size of at the most, a handful of folks that are just looking after things, but things are just taking care of themselves. >> John: And the CIO doesn't exist and there's no CISO, there at the beach. >> (laughs) Yeah. >> Thank you for coming on, sharing the cloud-native at scale here on The Cube. Thank you for your time. >> Fantastic. Thanks for having me. >> Okay. I'm John Furrier here, for special program presentation, special programming cloud-native at scale, enabling SuperCloud modern applications with Platform9. Thanks for watching. (gentle music)