(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)

(upbeat music) >> Hello and welcome to what is sure to be an insightful conversation about getting business results with cloud transformation. My name is Dave Vellante and I'm here with James Miller, Chief Technologist for Cloud and Infrastructure Services and Jay Dowling, America's Sales Lead for cloud and infrastructure services both with DXC Technology. Gentlemen, thanks for your time today. Welcome to the Cube. >> Great. Thanks for having us. >> Thank you Dave. Appreciate it. >> So let's get right into it. You know, I've talked to a lot of practitioners who've said, look, if you really want to drop zeros, like a lot of zeros to the bottom line, you can't just lift and shift. You really got to think about modernizing the application portfolio, you got to think about your business model and really think about transforming your business particularly the operating model. So my first question Jim is what role does the cloud play in modernization? >> Well, there are really three aspects that the cloud plays in modernization. You mentioned multiple zeros. One is cost optimization and that can be achieved through business operations, through environmental, social and governance. Also being more efficient with your IT investments. But that's not the only aspect. There's also agility and innovation and that can be achieved through automation and productivity, speed to market for new features and functions, improvements in the customer experience and the capability to metabolize a great deal more data in your environment which the end result is an improvement in releasing of new things to the field. And finally, there's resilience and I'm not really talking about IT resilience, but more of business resilience. To be able to handle operational risk, improve your securities and controls, deal with some of the talent gap that's in the industry and also protect your brand reputation. So modernization is really about balancing these three aspects, cost optimization, agility and innovation and resilience. >> So, thank you for that. So Jay, I got to ask you, in the current climate everybody's sort of concerned and there's not great visibility on the macro. So Jim mentioned cost optimization. That seems to be one of the top areas that customers are focused on. The two I hear a lot are consolidating redundant vendors and optimizing cloud costs. So that's, you know, top of mind today. I think everybody really, you know understands the innovation and agility piece at least at a high level, maybe realizing it is different. And then the business resilience piece is really interesting because, you know, prior to the pandemic people you know, they had a DR strategy, but they realized, wow, my business might not be that resilient. So Jay, my question to you is what are you hearing when you talk to customers? What's the priority today? >> You know, priority is often an overused term in digital transformation, you know people want to get ready for next generation environments, customer experience, making sure they're improving, you know, how they engage with their clients and what their branding is. And what we find is a lot of clients don't have the underlying infrastructure in place today to get to where they want to get to. So cloud becomes an important element of that. But, you know, with DXC'S philosophy not everything necessarily needs to go to cloud to be cost optimized for instance, in many cases you can run applications, you know in your own data center or on-prem or in other environments in a hybrid environment or multi-cloud environment and still be very optimized from a cost spend standpoint, and also put yourself in position for modernization and for be able to do the bring the things to the business that the clients are you know, that their clients are looking for like the CMO and the CFO, et cetera, trying to use IT as a lever to drive business and to drive, you know business acceleration and drive profitability, frankly. So there's a lot of dependency on infrastructure, but there's a lot of elements to it. And we advocate for, you know there's not a single answer to that. We'd like to evaluate clients' environments and work with them to get them to an optimal target operating model you know, so that they can really deliver on what the promises are for their departments. >> So let's talk about some of the barriers to realizing value in a context of modernization. We talked about cost optimization, agility and resilience. But there's a business angle and there's a technical angle here. We always talk about people process and technology, technology oftentimes CIOs will tell us, well, that's the easy part, We'll figure that out whether it's true or not but I agree, people and process are sometimes the tough ones. So Jay, why don't you start, what do you see as the barriers, particularly from a business standpoint? >> Well, I think people need to let their guard down and be open to the ideas that are out there in the market from, you know, the standards that are being built by, you know best in class models, and there's many people that have gone on, you know cloud journeys and been very successful with it. There's others that have set high expectations with their business leaders that haven't necessarily met the goals that they need to meet or maybe haven't met them as quickly as they promised. So there's a, you know, there's a change management aspect that you'd need to look at with the, you know, with the environments, there's a, you know, there's a skillset environment that they need to be prepared for. Do they have the people, you know, to deliver with the, you know, with the tools and the skills and the models that they're putting themselves in place for in the future versus where they are now? There's just a lot of, you know there's a lot of different elements. It's not just a this price is better or this can operate better than one environment over the other. I think we like to try to look at things holistically and make sure that, you know, we're being, you know as much of a consultative advocate for the client, for, you know, where they want to go, what their destiny is, and based on what we've learned with other clients, you know and we can bring those best practices forward because we've worked, you know across such a broad spectrum of clients versus them being somewhat contained and sometimes can't see outside of their own, you know their own challenges if you would. So they need advocacy to help, you know bring them to the next level. And we like to translate that through you know, technology advances, which, you know Jim's really good at doing for us. >> Yeah. Jim, is the big barrier a skills issue, you know, bench strength? Are there other considerations from your perspective? >> Well, we've identified a number of factors that inhibit success of customers. One is, thinking it's only a technology change in moving to cloud when it's much broader than that. There are changes in governance, changes in process that need to take place. The other is evaluating the cloud providers on their current pricing structure and performance. And we see pricing and structure changing dramatically every few months between the various cloud providers. And you have to be flexible enough to determine which providers you want, and it may not be feasible to just have a single cloud provider in this world. The other thing is a big bang approach to transformation. I want to move everything and I want to move it all at once. That's not necessarily the best approach. A well thought out cloud journey and strategy and timing your investments, are really important to get maximizing your business return on a journey to the cloud. And finally, not engaging stakeholders early and continuously. You have to manage expectations in moving to cloud on what business factors will get affected, how you will achieve your cost savings and how you will achieve the business impact over the journey and reporting out on that with very strict metrics to all of the stakeholders. >> You know, mentioned multi-cloud just then we had in January 17th we had our Supercloud two event and Supercloud is basically, it's really what multi-cloud should have been, I'd like to say. So it's just creating a common experience across clouds, and you guys were talking about, you know there's different governance, there's different security there's different pricing. So, and one of the takeaways from this event, in talking to customers and practitioners and technologists is you can't go it alone. So I wonder if you could talk about your partnership strategy, what do partners bring to the table and what is DXC's, you know, unique value? >> I'd be happy to lead with that if you'd like. >> Great. >> I, you know, we've got a vast partner ecosystem at DXC given the size and the history of the company. I can use several examples. One of the larger partners in my particular space is Dell technology, right? They're a great, you know, partner for us across many different areas of the business. It's not just a storage and compute play anymore. They're, on the edge. They're, you know, they've got intelligence in their networking devices now and they've really brought, you know a lot of value to us as a partner. And, you know, there's somebody who could look at Dell technology as somebody that might, you know have a victim, you know, effect because of all the hyperscaler activity and all the cloud activity. But they've really taken an outstanding attitude with this and said, listen, not all things are destined for cloud or not all things would operate better in a cloud environment, and they'd like to be part of those discussions to see how they can, you know how we can bring a multi-cloud environment, you know both private and public, you know to clients and let's look at the applications and the infrastructure and, and what's, you know what's the best optimal running environment, you know for us to be able to bring, you know the greatest value to the business with speed, with security, with, you know, and, you know the things that they want to keep closest to the business are often things that you want to kind of you know, keep on your premise or keep in your own data center. So they're an ideal model of somebody that's resourced us well, partners with us well in the market and we continue to grow that relationship day in and day out with those guys. And we really appreciate, you know their support of our strategy and we like to also compliment their strategy and work, you know work together hand in hand in front of our clients. >> Yeah. You know, Jim, Matt Baker, who's the Head of Strategic Planning at Dell talks about it's not a zero sum game. And I think, you know, you're right Jay, I think initially people felt like, oh wow, it is a zero sum game, but it's clearly not. And this idea of whether you call it super cloud or Uber cloud or multi-cloud, clearly Dell is headed in that direction and I've, you know, look at some of their future projects, their narrative. I'm curious from a technology standpoint, Jim, what your role is. Is it to make it all work? Is it to, you know, end to end? I wonder if you could help, you know, us understand that. >> Help us figure this out Jim (all laughing) >> Glad to expand on that. One of my key roles is developing our product roadmap for DXC offerings. And we do that roadmap in conjunction with our partners where we can leverage the innovation that our partners bring to the table, and we often utilize engineering resources from our partners to help us jointly build those offerings that adapt to changes in the market and also adapt to many of our customers changing needs over time. So my primary role is to look at the market, talk to our customers, and work with our partners, to develop a product roadmap for delivering DXC products and services to our clients so that they can get the return on investment on their technology journeys. >> You know, we've been working with these two firms for a while now. Even predates, you know, the name DXC and that transformation. I'm curious as to what's, how you would respond to what's unique. You know, you hear a lot about partnerships, you guys got a lot of competition, Dell has a lot of competition. What's specifically unique about this combination? >> I would say our unique approach, we call it cloud right. And that approach is making the right investments at the right time and on the right platforms. And our partners play a key role in that. So we encourage our customers to not necessarily have a cloud first approach but a cloud right approach, where they place the workloads in the environment that is best suited from a technology perspective, a business perspective and even a security and governance perspective. And the right approach might include mainframe, it might include an on-premises infrastructure, it could include private cloud, public cloud and SaaS components all integrated together to deliver that value. >> Yeah, Jay, please. It's a complicated situation for a lot of customers, but chime in here. >> And now if you were speaking still specifically to Dell here, like they also walk the talk, right? They invest in DXC as a partnership they put people on the ground that their only purpose in life is to help DXC succeed with Dell in, you know, arm in arm in front of clients. And it's not, you know, it's not a winner take all thing at all. It's really true partnership. They've brought solution resources. We have an account CTO, we've got executive sponsorship, we do regular QBR meetings, we have regular executive touchpoint meetings. It's really important that you keep a high level of intimacy with the client with the partners, you know, in the GSI community. And I've been with several GSI's and this is an exceptional example of true partnership and commitment to success with Dell technology. I'm really extremely impressed on the engagement level that we've had there and, you know, continue to show a lot of support, you know, both for them, you know there's other OEM partners of course in the market there's always going to be other technology solutions for certain clients but this has been a particularly strong element for us in our partnership and our go-to-market strategy. >> Well, I think too, just my observation is a lot of it is about trust. You guys have both earned the trust, kind of over the years, taking your arrows, you know, over decades, and you know, that just doesn't happen overnight. So guys, I appreciate it. Thanks for your time. It's all about getting cloud right, isn't it? >> That's right. Thank you Dave. Appreciate it very much. >> Thank you. >> Great to have you on. Keep it right there for more action on the cube right back. (upbeat music)

>> Hello and welcome to what is sure to be an insightful conversation about getting business results with cloud Transformation. My name is Dave Vellante, and I'm here with James Miller, Chief Technologist for cloud and Infrastructure Services and Jay Dowling, America's Sales Lead for cloud and Infrastructure Services, both with DXC Technology. Gentlemen, thanks for your time today, welcome to The Cube. >> Great, thanks for having us. >> Thank you, Dave, appreciate it. >> So let's get right into it. You know, I've talked to a lot of practitioners who've said, look, if you really want to drop zeros, like a lot of zeroes to the bottom line, you can't just lift and shift. You really got to think about modernizing, the application portfolio, you got to think about your business model, and really think about transforming your business, particularly the operating model. So my first question, Jim, is what role does the cloud play in modernization? >> Well there are really 3 aspects that the cloud plays in modernization. You mentioned multiple zeroes. One is cost optimization. And that can be achieved through business operations, through environmental, social, in governance. Also being more efficient with your IT investments. But that's not the only aspect. There's also agility and innovation. And that can be achieved through automation and productivity, speed to market for new features and functions, improvements in the customer experience, and the capability to metabolize a great deal more data in your environment. Which, the end result is an improvement in releasing of new things to the field. And finally, there's resilience. And I'm not really talking about IT resilience, but more of business resilience. To be able to handle operational risk, improve your securities and controls, deal with some of the talent gap that's in the industry, and also protect your brand reputation. So modernization is really about balancing these 3 aspects. Cost optimization, agility and innovation, and resilience. >> So, thank you for that, so, Jay, I got to ask you, the current climate, ever body's sort of concerned, and there's not great visibility on the macro. So, Jim mentioned cost optimization, that seems to be one of the top areas that customers are focused on. The two I hear a lot are, consolidating redundant vendors, and optimizing cloud costs. So that's, you know, top of mine today. I think everybody really, you know, understands the innovation and agility piece. At least at a high level, maybe realizing it is different. >> Sure >> And then the business resilience piece is really interesting, because, you know, prior to the pandemic, people, you know, they had a DR strategy, but they realized, wow my business may not be that resilient. So, Jay, my question to you is, what are you hearing when you talk to customers, what's the priority today? >> You know, the priority is an often overused term of digital transformation. You know, people want to get ready for next generation environments, customer experience, making sure they're improving, you know, how they engage with their clients, and what their branding is. What we find is a lot of clients don't have the underlying infrastructure in place today to get to where they want to get to. So cloud becomes an important element of that, but, you know, with DXC's philosophy, not everything necessarily needs to go to cloud to be cost optimized, for instance. In many cases you can run applications, you know, in your own data center, or on Pram or, in other environments, in the hybrid environment or multi cloud environment, and still be very optimized from a cost/spend standpoint. And also put yourself in position for modernization and be able to bring the things to the business that the clients are, you know their clients are looking for like the CMO and the CFO etc. trying to use IT as a leverage to drive business and to drive business acceleration and to drive profitability, frankly. So there's a lot of dependency on infrastructure, but there's a lot of elements to it and we advocate for, you know, there's not a single answer to that. We like to evaluate clients, environments, and work with them to get them to an optimal target operating model so that they can really deliver on what the promises are for their departments. >> So, lets talk about some of the barriers to realizing value in the context of modernization. We talked about cost optimization, agility, and resilience. But there's a business angle and there's a technical angle here. We already talked about people, process, and technology. Technology oftentimes CIO's will tell us 'Well that's the easy part. We'll figure that out.' Whether it's true or not; but I agree. People and process is sometimes the tough one. So Jay, why don't you start. What do you see as the barriers particularly from a business standpoint? I think people need to let their guard down and be open to the ideas that are out there in the market from the standards that are being built by Best in Class models. And there's many people who that have got on cloud juries have been very successful with it. There's others that have set high expectations with their business leaders that haven't necessarily met the goals that they need to meet, or maybe haven't met them as quickly as they promised. So there's a change management aspect that you need to look at with the environments. There's a skillset environment that they need to be prepared for. Do they have the people to deliver with the tools and the skills and the models that they're putting themselves in place for in the future versus where they are now. There's just a lot of different elements. It's not just that this price is better or this can operate better than one environment over the other. I think we like to try and look at things holistically and make sure that we're being as much of a consultative advocate for the client for where they want to go, what their destiny is and based on what we've learned with other clients and we can bring those best practices forward because we've worked across such a broad spectrum of clients versus them being somewhat contained and sometimes can't see outside of their own challenges, if you would. So they need advocacy to help bring them to the next level. And we like to translate that through technology advances which Jim is really good at doing for us. >> Yeah Jim, is the big barrier a skills issue? You know, bench strength? Are their other considerations from your perspective? >> We've identified a number of factors that inhibit success of customers. One is thinking it's only a technology change; in moving to cloud. When it's much broader than that. There are changes in governance, changes in process that need to take place. The other is evaluating the other cloud providers on their current pricing structure and performance. And we see pricing and structure changing dramatically every few months between the various cloud providers. And you have to be flexible enough to determine which providers you want; and it may not be feasible to just have a single cloud provider in this world. The other thing is a big bang approach to transformation. I want to move everything and I want to move it all at once. That's not necessarily the best approach. A well thought out cloud journey and strategy, and timing your investments are really important to maximizing your business return on the journey to the cloud. And finally, not engaging stakeholders early and continuously. You have to manage expectations in moving to cloud on what business factors will get affected, how you will achieve your costs savings, and how you will achieve the business impact over the journey and reporting out on that with very strict metrics to all of the stakeholders. >> You mentioned multi-cloud just then. On January 17th we had our Super Cloud 2 event. And Super Cloud is basically what multi-cloud should have been I like to say. So it's creating a common experience across clouds. You guys were talking about you know, there's different governance, different securities, different pricing. So, and one of the takeaways from this event and talking to customers and practitioners and technologists is you can't go it alone. So I wonder if you'd talk about your partnership strategy? What do partners bring to the table? What is DXC's unique value? >> I'd be happy to lead with that if you'd like. >> Great >> We've got a vast partner ecosystem at DXC, given the size and the history of the company. I use several examples. One of the larger partners in my particular space is Dell Technology. They're a great partner for us across many different areas of the business. It's not just storage and compute play anymore. They're on the edge. They've got intelligence in their networking devices now. And they've really brought a lot of value to us as a partner. You can look at Dell Technology as somebody that might have a victim effect because of all of the hyper-scaling activity and all of the cloud activity but they've really taken an outstanding attitude with this and said listen not all things are destined for cloud or not all things would operate better in a cloud environment. And they like to be apart of those discussions to see how they can, how we can bring a multi-cloud environment, both private and public to clients and let's look at the applications and the infrastructure and what's the best optimal running environment for us to be able to bring the greatest value to the business with speed, with security and the the things that they want to keep close to the business are often things that you want to keep on your premise or keep in your own data centers. So they're an ideal model of somebody that's resourced this well, partnered in this well in the market and we continue to grow that relationship day in and day out with those guys. And we really appreciate their support of our strategy and we like to also compliment their strategy and work together hand in hand in front of our clients. >> Yeah you know Jim, Matt Baker who's the Head of Strategic Planning at Dell talks about it's not zero-sum game and I think you're right Jay. I think initially people felt like oh wow, it is a zero-sum game but it's clearly not. And this idea of whether you call it Super Cloud or Uber Cloud or Multi Cloud, clearly Dell is headed in that direction. Look at some of their future projects, their narrative. I'm curious from a technology standpoint Jim, what your role is. Is it to make it all work? Is it to end to end? Wondering if you could help us understand that. >> Help us figure it out Jim, here. >> Glad to expand on that. Well, one of my key roles is developing our product roadmap for DXC offerings. And we do that roadmap in conjunction with our partners where we can leverage the innovation that our partners bring to the table and we often utilize engineering resources from our partners to help us jointly build those offerings that adapt to changes in the market and also adapt to many of our customer's changing needs overtime. So my primary role is to look at the market, talk to our customers, and work with our partners to develop a product roadmap for delivering DXC products and services to our clients so that they can get the return on investment on their technology journeys. >> You know, we've been working with these two firms for a while now; pre-dates the name DXC and that transformation. I'm curious as to what's, how you would respond to what's unique. You know you hear a lot about partnerships, you guys got a lot of competition. Dell has a lot of competition. What's specifically unique about this combination? >> I think- go ahead Jim >> I would say our unique approach is, we call it cloud right. And that approach is making the right investments, at the right time, and on the right platforms. And our partners play a key role in that. So we encourage our customers to not necessarily have a cloud first approach, but a cloud right approach where they place the workloads in the environment that is best suited from a technology perspective, a business perspective, and even a security and governance perspective. And the right approach might include main frame, it might include and on-premises infrastructure it could include private cloud, public cloud and SAS components all integrated together to deliver that value. >> Yeah Jay please. Let me tell you, this is a complicated situation for a lot of customers. But, chime in here. >> Yeah if you're speaking specifically to Dell here like, they also walk the talk right. They invest in DXC as a partnership. They put people on the ground. Their only purpose in life is to help DXC succeed with Dell, arm in arm, in front of clients. And it's not a winner take all thing at all. It's really a true partnership. They've brought solution resources. We have an account CTO, we've got executive sponsorship. We do regular QVR meetings. We have regular executive touch-point meetings. It's really important that you keep high level of intimacy with the clients, with the partners in the GSI community. And I've been with several GSI's and this is an exceptional example of true partnership and commitment to success with Dell Technology. I'm really extremely impressed on the engagement level that we've had there, and continue to show a lot of support both for them. And there's other OEM partners of course in the market. There's always going to be other technology solutions for certain clients, but this has been a particularly strong element for us and our partnership and our go-to-market strategy. >> Well I think too, just my observation is a lot of it is about trust. You guys have both earned the trust over the years. Ticking your arrows over decades, and that just doesn't happen overnight. Guys I appreciate it. Thanks for your time. It's all about getting Cloud Right, isn't it? >> That's right. Thank you Dave. Appreciate it very much. >> Thank you >> Jay, great to have you on. Keep it right there for more action on The CUBE. We'll be right back.

>>We are back in the final stretch at Supercomputing 22 here in Dallas. I'm your host Paul Gillum with my co-host Dave Nicholson, and we've been talking to so many smart people this week. It just, it makes, boggles my mind are next guest. J Poso is the HPC and AI technology strategist at Dell. Jay also has a PhD in astronomy from the University of Texas. And I'm guessing you were up watching the Artemis launch the other night? >>I, I wasn't. I really should have been, but, but I wasn't, I was in full super computing conference mode. So that means discussions at, you know, various venues with people into the wee hours. >>How did you make the transition from a PhD in astronomy to an HPC expert? >>It was actually really straightforward. I did theoretical astrophysics and I was modeling what white dwarfs look like when they create matter and then explode as type one A super Novi, which is a class of stars that blow up. And it's a very important class because they blow up almost exactly the same way. So if you know how bright they are physically, not just how bright they appear in the sky, but if you can determine from first principles how bright they're, then you have a standard ruler for the universe when they go off in a galaxy, you know how far the galaxy is about how faint it is. So to model these though, you had to understand equations of physics, including electron degeneracy pressure, as well as normal fluid dynamics kinds of of things. And so you were solving for an explosive burning front, ripping through something. And that required a supercomputer to have anywhere close to the fat fidelity to get a reasonable answer and, and hopefully some understanding. >>So I've always said electrons are degenerate. I've always said it and I, and I mentioned to Paul earlier, I said, finally we're gonna get a guest to consort through this whole dark energy dark matter thing for us. We'll do that after, after, after the segment. >>That's a whole different, >>So, well I guess super computing being a natural tool that you would use. What is, what do you do in your role as a strategist? >>So I'm in the product management team. I spend a lot of time talking to customers about what they want to do next. HPC customers are always trying to be maximally productive of what they've got, but always wanting to know what's coming next. Because if you think about it, we can't simulate the entire human body cell for cell on any supercomputer day. We can simulate parts of it, cell for cell or the whole body with macroscopic physics, but not at the, you know, atomic level, the entire organism. So we're always trying to build more powerful computers to solve larger problems with more fidelity and less approximations in it. And so I help people try to understand which technologies for their next system might give them the best advance in capabilities for their simulation work, their data analytics work, their AI work, et cetera. Another part of it is talking to our great technology partner ecosystem and learning about which technologies they have. Cause it feeds the first thing, right? So understanding what's coming, and Dell has a, we're very proud of our large partner ecosystem. We embrace many different partners in that with different capabilities. So understanding those helps understand what your future systems might be. That those are two of the major roles in it. Strategic customers and strategic technologies. >>So you've had four days to wander the, this massive floor here and lots of startups, lots of established companies doing interesting things. What have you seen this week that really excites you? >>So I'm gonna tell you a dirty little secret here. If you are working for someone who makes super computers, you don't get as much time to wander the floor as you would think because you get lots of meetings with people who really want to understand in an NDA way, not just in the public way that's on the floor, but what's, what are you not telling us on the floor? What's coming next? And so I've been in a large number of customer meetings as well as being on the floor. And while I can't obviously share the everything, that's a non-disclosure topic in those, some things that we're hearing a lot about, people are really concerned with power because they see the TDP on the roadmaps for all the silicon providers going way up. And so people with power comes heat as waste. And so that means cooling. >>So power and cooling has been a big topic here. Obviously accelerators are, are increasing in importance in hpc not just for AI calculations, but now also for simulation calculations. And we are very proud of the three new accelerator platforms we launched here at the show that are coming out in a quarter or so. Those are two of the big topics we've seen. You know, there's, as you walk the floor here, you see lots of interesting storage vendors. HPC community's been do doing storage the same way for roughly 20 years. But now we see a lot of interesting players in that space. We have some great things in storage now and some great things that, you know, are coming in a year or two as well. So it's, it's interesting to see that diversity of that space. And then there's always the fun, exciting topics like quantum computing. We unveiled our first hybrid classical quantum computing system here with I on Q and I can't say what the future holds in this, in this format, but I can say we believe strongly in the future of quantum computing and that this, that future will be integrated with the kind of classical computing infrastructure that we make and that will help make quantum computing more powerful downstream. >>Well, let's go down that rabbit hole because, oh boy, boy, quantum computing has been talked about for a long time. There was a lot of excitement about it four or five years ago, some of the major vendors were announcing quantum computers in the cloud. Excitement has kind of died down. We don't see a lot of activity around, no, not a lot of talk around commercial quantum computers, yet you're deep into this. How close are we to have having a true quantum computer or is it a, is it a hybrid? More >>Likely? So there are probably more than 20 and I think close to 40 companies trying different approaches to make quantum computers. So, you know, Microsoft's pursuing a topol topological approach, do a photonics based approach. I, on Q and i on trap approach. These are all different ways of trying to leverage the quantum properties of nature. We know the properties exist, we use 'em in other technologies. We know the physics, but trying the engineering is very difficult. It's very difficult. I mean, just like it was difficult at one point to split the atom. It's very difficult to build technologies that leverage quantum properties of nature in a consistent and reliable and durable way, right? So I, you know, I wouldn't wanna make a prediction, but I will tell you I'm an optimist. I believe that when a tremendous capability with, with tremendous monetary gain potential lines up with another incentive, national security engineering seems to evolve faster when those things line up, when there's plenty of investment and plenty of incentive things happen. >>So I think a lot of my, my friends in the office of the CTO at Dell Technologies, when they're really leading this effort for us, you know, they would say a few to several years probably I'm an optimist, so I believe that, you know, I, I believe that we will sell some of the solution we announced here in the next year for people that are trying to get their feet wet with quantum. And I believe we'll be selling multiple quantum hybrid classical Dell quantum computing systems multiple a year in a year or two. And then of course you hope it goes to tens and hundreds of, you know, by the end of the decade >>When people talk about, I'm talking about people writ large, super leaders in supercomputing, I would say Dell's name doesn't come up in conversations I have. What would you like them to know that they don't know? >>You know, I, I hope that's not true, but I, I, I guess I understand it. We are so good at making the products from which people make clusters that we're number one in servers, we're number one in enterprise storage. We're number one in so many areas of enterprise technology that I, I think in some ways being number one in those things detracts a little bit from a subset of the market that is a solution subset as opposed to a product subset. But, you know, depending on which analyst you talk to and how they count, we're number one or number two in the world in supercomputing revenue. We don't always do the biggest splashy systems. We do the, the frontier system at t, the HPC five system at ENI in Europe. That's the largest academic supercomputer in the world and the largest industrial super >>That's based the world on Dell. Dell >>On Dell hardware. Yep. But we, I think our vision is really that we want to help more people use HPC to solve more problems than any vendor in the world. And those problems are various scales. So we are really concerned about the more we're democratizing HPC to make it easier for more people to get in at any scale that their budget and workloads require, we're optimizing it to make sure that it's not just some parts they're getting, that they are validated to work together with maximum scalability and performance. And we have a great HPC and AI innovation lab that does this engineering work. Cuz you know, one of the myths is, oh, I can just go buy a bunch of servers from company X and a network from company Y and a storage system from company Z and then it'll all work as an equivalent cluster. Right? Not true. It'll probably work, but it won't be the highest performance, highest scalability, highest reliability. So we spend a lot of time optimizing and then we are doing things to try to advance the state of HPC as well. What our future systems look like in the second half of this decade might be very different than what they look like right. Now. >>You mentioned a great example of a limitation that we're running up against right now. You mentioned an entire human body as a, as a, as an organism >>Or any large system that you try to model at the atomic level, but it's a huge macro system, >>Right? So will we be able to reach milestones where we can get our arms entirely around something like an entire human organism with simply quantitative advances as opposed to qualitative advances? Right now, as an example, let's just, let's go down to the basics from a Dell perspective. You're in a season where microprocessor vendors are coming out with next gen stuff and those next NextGen microprocessors, GPUs and CPUs are gonna be plugged into NextGen motherboards, PCI e gen five, gen six coming faster memory, bigger memory, faster networking, whether it's NS or InfiniBand storage controllers, all bigger, better, faster, stronger. And I suspect that systems like Frontera, I don't know, but I suspect that a lot of the systems that are out there are not on necessarily what we would think of as current generation technology, but maybe they're n minus one as a practical matter. So, >>But yeah, I mean they have a lifetime, so Exactly. >>The >>Lifetime is longer than the evolution. >>That's the normal technologies. Yeah. So, so what some people miss is this is, this is the reality that when, when we move forward with the latest things that are being talked about here, it's often a two generation move for an individual, for an individual organization. Yep. >>So now some organizations will have multiple systems and they, the system's leapfrog and technology generations, even if one is their real large system, their next one might be newer technology, but smaller, the next one might be a larger one with newer technology and such. Yeah. So the, the biggest super computing sites are, are often running more than one HPC system that have been specifically designed with the latest technologies and, and designed and configured for maybe a different subset of their >>Workloads. Yeah. So, so the, the, to go back to kinda the, the core question, in your opinion, do we need that qualitative leap to something like quantum computing in order to get to the point, or is it simply a question of scale and power at the, at the, at the individual node level to get us to the point where we can in fact gain insight from a digital model of an entire human body, not just looking at a, not, not just looking at an at, at an organ. And to your point, it's not just about human body, any system that we would characterize as being chaotic today, so a weather system, whatever. Do you, are there any milestones that you're thinking of where you're like, wow, you know, I have, I, I understand everything that's going on, and I think we're, we're a year away. We're a, we're, we're a, we're a compute generation away from being able to gain insight out of systems that right now we can't simply because of scale. It's a very, very long question that I just asked you, but I think I, but hopefully, hopefully you're tracking it. What, what are your, what are your thoughts? What are these, what are these inflection points that we, that you've, in your mind? >>So I, I'll I'll start simple. Remember when we used to buy laptops and we worried about what gigahertz the clock speed was Exactly. Everybody knew the gigahertz of it, right? There's some tasks at which we're so good at making the hardware that now the primary issues are how great is the screen? How light is it, what's the battery life like, et cetera. Because for the set of applications on there, we we have enough compute power. We don't, you don't really need your laptop. Most people don't need their laptop to have twice as powerful a processor that actually rather up twice the battery life on it or whatnot, right? We make great laptops. We, we design for all of those, configure those parameters now. And what, you know, we, we see some customers want more of x, somewhat more of y but the, the general point is that the amazing progress in, in microprocessors, it's sufficient for most of the workloads at that level. Now let's go to HPC level or scientific and technical level. And when it needs hpc, if you're trying to model the orbit of the moon around the earth, you don't really need a super computer for that. You can get a highly accurate model on a, on a workstation, on a server, no problem. It won't even really make it break a sweat. >>I had to do it with a slide rule >>That, >>That >>Might make you break a sweat. Yeah. But to do it with a, you know, a single body orbiting with another body, I say orbiting around, but we both know it's really, they're, they're both ordering the center of mass. It's just that if one is much larger, it seems like one's going entirely around the other. So that's, that's not a super computing problem. What about the stars in a galaxy trying to understand how galaxies form spiral arms and how they spur star formation. Right now you're talking a hundred billion stars plus a massive amount of inter stellar medium in there. So can you solve that on that server? Absolutely not. Not even close. Can you solve it on the largest super computer in the world today? Yes and no. You can solve it with approximations on the largest super computer in the world today. But there's a lot of approximations that go into even that. >>The good news is the simulations produce things that we see through our great telescopes. So we know the approximations are sufficient to get good fidelity, but until you really are doing direct numerical simulation of every particle, right? Right. Which is impossible to do. You need a computer as big as the universe to do that. But the approximations and the science in the science as well as the known parts of the science are good enough to give fidelity. So, and answer your question, there's tremendous number of problem scales. There are problems in every field of science and study that exceed the der direct numerical simulation capabilities of systems today. And so we always want more computing power. It's not macho flops, it's real, we need it, we need exo flops and we will need zeta flops beyond that and yada flops beyond that. But an increasing number of problems will be solved as we keep working to solve problems that are farther out there. So in terms of qualitative steps, I do think technologies like quantum computing, to be clear as part of a hybrid classical quantum system, because they're really just accelerators for certain kinds of algorithms, not for general purpose algorithms. I do think advances like that are gonna be necessary to solve some of the very hardest problem. It's easy to actually formulate an optimization problem that is absolutely intractable by the larger systems in the world today, but quantum systems happen to be in theory when they're big and stable enough, great at that kind of problem. >>I, that should be understood. Quantum is not a cure all for absolutely. For the, for the shortage of computing power. It's very good for certain, certain >>Problems. And as you said at this super computing, we see some quantum, but it's a little bit quieter than I probably expected. I think we're in a period now of everybody saying, okay, there's been a lot of buzz. We know it's gonna be real, but let's calm down a little bit and figure out what the right solutions are. And I'm very proud that we offered one of those >>At the show. We, we have barely scratched the surface of what we could talk about as we get into intergalactic space, but unfortunately we only have so many minutes and, and we're out of them. Oh, >>I'm >>J Poso, HPC and AI technology strategist at Dell. Thanks for a fascinating conversation. >>Thanks for having me. Happy to do it anytime. >>We'll be back with our last interview of Supercomputing 22 in Dallas. This is Paul Gillen with Dave Nicholson. Stay with us.

>>Hey everyone. Welcome back to the cubes day two coverage of VMware Explorer, 22 from San Francisco. Lisa Martin, back here with you with Dave Nicholson, we have a couple of guests from VMware. Joining us, please. Welcome Jay Workman, senior director, cloud partner, and alliances marketing, and Jeff Thompson, VP cloud provider sales at VMware guys. It's great to have you on the program. >>Ah, good to be here. Thanks for having us on. >>We're gonna be talking about a really interesting topic. Sovereign cloud. What is sovereign cloud? Jeff? Why is it important, but fundamentally, what is >>It? Yeah, well, we were just talking a second ago. Aren't we? And it's not about royalty. So yeah, data sovereignty is really becoming super important. It's about the regulation and control of data. So lots of countries now are being very careful and advising companies around where to place data and the jurisdictional controls mandate that personal data or otherwise has to be secured. We ask, we have to have access controls around it and privacy controls around it. So data sovereign clouds are clouds that have been built by our cloud providers in, in, in VMware that specifically satisfy the requirements of those jurisdictions and regulated industries. So we've built a, a little program around that. We launched it about a year ago and continuing to add cloud providers to that. >>Yeah, and I, I think it's also important just to build on what Jeff said is, is who can access that data is becoming increasingly important data is, is almost in it's. It is becoming a bit of a currency. There's a lot of value in data and securing that data is, is becoming over the years increasingly important. So it's, it's not like we built a problem or we created a solution for problem that didn't exist. It's gotten it's, it's been a problem for a while. It's getting exponentially bigger data is expanding and growing exponentially, and it's becoming increasingly important for organizations and companies to realize where my data sits, who can access it, what types of data needs to go and what type of clouds. And it's very, very aligned with multi-cloud because some data can sit in a, in a public cloud, which is fine, but some data needs to be secure. It needs to be resident within country. And so this is, this is what we're addressing through our partners. >>Yeah, I, yeah, I was just gonna add to that. I think there's a classification there there's data residency, and then there's data sovereignty. So residency is just about where is the data, which country is it in sovereignty is around who can access that data. And that's the critical aspect of, of data sovereignty who's got control and access to that data. And how do we make sure that all the controls are in place to make sure that only the right people can get access to that data? Yeah. >>So let's, let's sort of build from the ground up an example, and let's use Western Europe as an example, just because state to state in the United States, although California is about to adopt European standards for privacy in a, in a unique, in a unique, unique way, pick a country in, in Europe, I'm a service provider. I have an offering and that offering includes a stack of hardware and I'm running what we frequently refer to as the STDC or software defined data center stack. So I've got NEX and I've got vs N and I've got vSphere and I'm running and I have a cloud and you have all of the operational tools around that, and you can spin up VMs and render under applications there. And here we are within the borders of this country, what makes it a sovereign cloud at that? So at that point, is that a sovereign cloud or? >>No, not yet. Not it's close. I mean, you nailed, >>What's >>A secret sauce. You nailed the technology underpinning. So we've got 4,500 plus cloud provider partners around the world. Less than 10% of those partners are running the full STDC stack, which we've branded as VMware cloud verified. So the technology underpinning from our perspective is the starting point. Okay. For sovereignty. So they, they, they need that right. Technology. Okay. >>Verified is required for sovereign. Yes. >>Okay. Cloud verified is the required technology stack for sovereign. So they've got vSphere vs. A NSX in there. Okay. A lot of these partners are also offering a multitenant cloud with VMware cloud director on top of that, which is great. That's the starting point. But then we've, we've set a list of standards above and beyond that, in addition to the technology, they've gotta meet certain jurisdiction requirements, certain local compliance requirements and certifications. They've gotta be able to address the data re data residency requirements of their particular jurisdiction. So it's going above and beyond. But to your point, it does vary by country. >>Okay. So, so in this hypothetical example, this is this country. You a stand, I love it. When people talk about Stan, people talk about EMIA and you know, I, I love AMEA food. Isn't AIAN food. One. There's no such thing as a European until you have an Italian, a Britain, a German yep. In Florida arguing about how our beer and our coffee is terrible. Right. Right. Then they're all European. They go home and they don't like each other. Yeah. So, but let's just pretend that there's a thing called Europe. So this, so there's this, so we've got a border, we know residency, right. Because it physically is here. Yep. But what are the things in terms of sovereignty? So you're talking about a lot of kind of certification and validation, making sure that, that everything maps to those existing rules. So is, this is, this is a lot of this administrative and I mean, administrative in the, in the sort of state administrative terminology, >>I I'm let's build on your example. Yeah. So we were talking about food and obviously we know the best food in the world comes from England. >>Of course it does. Yeah. I, no doubt. I agree. I Don not get that. I do. I do do agree. Yeah. >>So UK cloud, fantastic partner for us. Okay. Whether they're one of our first sovereign cloud providers in the program. So UK cloud, they satisfied the requirements with the local UK government. They built out their cloud verified. They built out a stack specifically that enables them to satisfy the requirements of being a sovereign cloud provider. They have local data centers inside the UK. The data from the local government is placed into those data centers. And it's managed by UK people on UK soil so that they know the privacy, they know the security aspects, the compliance, all of that wrapped up on top of a secure SDDC platform. Okay. Satisfies the requirements of the UK government, that they are managing that data in a sovereign way that, that, that aligns to the jurisdictional control that they expect from a company like UK cloud. Well, >>I think to build on that, a UK cloud is an example of certain employees at UK, UK cloud will have certain levels of clearance from the UK government who can access and work on certain databases that are stored within UK cloud. So they're, they're addressing it from multiple fronts, not just with their hardware, software data center framework, but actually at the individual compliance level and individual security clearance level as to who can go in and work on that data. And it's not just a governmental, it's not a public sector thing. I mean, any highly regulated industry, healthcare, financial services, they're all gonna need this type of data protection and data sovereignty. >>Can this work in a hyperscaler? So you've got you, have, you have VMC AVS, right? GC V C >>O >>CVAs O CVS. Thank you. Can it be, can, can a sovereign cloud be created on top of physical infrastructure that is in one of those hyperscalers, >>From our perspective, it's not truly sovereign. If, if it's a United States based company operating in Germany, operating in the UK and a local customer or organization in Germany, or the UK wants to deploy workloads in that cloud, we wouldn't classify that as totally sovereign. Okay. Because by virtue of the cloud act in the United States, that gives the us government rights to request or potentially view some of that data. Yeah. Because it's, it's coming out of a us based operator data center sitting on foreign soil so that the us government has some overreach into that. And some of that data may actually be stored. Some of the metadata may reside back in the us and the customer may not know. So certain workloads would be ideally suited for that. But for something that needs to be truly sovereign and local data residency, that it wouldn't be a good fit. I think that >>Perspectives key thing, going back to residency versus sovereignty. Yeah. It can be, let's go to our UK example. It can be on a hyperscaler in the UK now it's resident in the UK, but some of the metadata, the profiling information could be accessible by the entity in the United States. For example, there now it's not sovereign anymore. So that's the key difference between a, what we view as a pro you know, a pure sovereign cloud play and then maybe a hyperscaler that's got more residency than sovereignty. >>Yeah. We talk a lot about partnerships. This seems to be a unique opportunity for a certain segment of partners yeah. To give that really is an opportunity for them to have a line of business established. That's unique from some of the hyperscale cloud providers. Yeah. Where, where sort of the, the modesty of your size might be an advantage if you're in a local. Yes. You're in Italy and you are a service provider. There sounds like a great fit, >>That's it? Yeah. You've always had the, the beauty of our program. We have 4,500 cloud providers and obviously not, all of them are able to provide a data, a sovereign cloud. We have 20 in the program today in, in the country. You you'd expect them to be in, you know, the UK, Italy, Italy, France, Germany, over in Asia Pacific. We have in Australia and New Zealand, Japan, and, and we have Canada and Latin America to, to dovetail, you know, the United States. But those are the people that have had these long term relationships with the local governments, with these regulated industries and providing those services for many, many years. It's just that now data sovereignty has become more important. And they're able to go that extra mile and say, Hey, we've been doing this pretty much, you know, for decades, but now we're gonna put a wrap and some branding around it and do these extra checks because we absolutely know that we can provide the sovereignty that's required. >>And that's been one of the beautiful things about the entire initiative is we're actually, we're learning a lot from our partners in these countries to Jeff's point have been doing this. They've been long time, VMware partners they've been doing sovereignty. And so collectively together, we're able to really establish a pretty robust framework from, from our perspective, what does data sovereignty mean? Why does it matter? And then that's gonna help us work with the customers, help them decide which workloads need to go and which type of cloud. And it dovetails very, very nicely into a multi-cloud that's a reality. So some of those workloads can sit in the public sector and the hyperscalers and some of 'em need to be sovereign. Yeah. So it's, it's a great solution for our customers >>When you're in customer conversations, especially as, you know, data sovereign to be is becomes a global problem. Where, who are you talking to? Are you talking to CIOs? Are you talking to chief data officers? I imagine this is a pretty senior level conversation. >>Yeah. I it's, I think it's all of the above. Really. It depends. Who's managing the data. What type of customer is it? What vertical market are they in? What compliance regulations are they are they beholden to as a, as an enterprise, depending on which country they're in and do they have a need for a public cloud, they may already be all localized, you know? So it really depends, but it, it could be any of those. It's generally I think a fair, fairly senior level conversation. And it's, it's, it's, it's consultancy, it's us understanding what their needs are working with our partners and figuring out what's the best solution for them. >>And I think going back to, they've probably having those conversations for a long time already. Yeah. Because they probably have had workloads in there for years, maybe even decades. It's just that now sovereignty has become, you know, a more popular, you know, requirements to satisfy. And so they've gone going back to, they've gone the extra mile with those as the trusted advisor with those people. They've all been working with for many, many years to do that work. >>And what sort of any examples you mentioned some of the highly regulated industries, healthcare, financial services, any customer come to mind that you think really articulates the value of what VMware's delivering through its service through its cloud provider program. That makes the obvious why VMware an obvious answer? >>Wow. I, I, I get there's, there's so many it's, it's actually, it's each of our different cloud providers. They bring their win wise to us. And we just have, we have a great library now of assets that are on our sovereign cloud website of those win wires. So it's many industries, many, many countries. So you can really pick, pick your, your choice. There. That's >>A good problem >>To have, >>To the example of UK cloud they're, they're really focused on the UK government. So some of them aren't gonna be referenced. Well, we may have indication of a major financial services company in Australia has deployed with AU cloud, one of our partners. So we we've also got some semi blind references like that. And, and to some degree, a lot of these are maintained as fairly private wins and whatnot for obvious security reasons, but, and we're building it and building that library up, >>You mentioned the number 4,500, a couple of times, you, you referencing VMware cloud provider partners or correct program partners. So VCP P yes. So 45, 4500 is the, kind of, is the, is the number, you know, >>That's the number >>Globally of our okay. >>Partners that are offering a commercial cloud service based at a minimum with vSphere and they're. And many of 'em have many more of our technologies. And we've got little under 10% of those that have the cloud verified designation that are running that full STDC, stack >>Somebody, somebody Talli up, all of that. And the argument has been made that, that rep that, that would mean that VMware cloud. And although some of it's on IAS from hyperscale cloud providers. Sure. But that, that rep, that means that VMware has the third or fourth largest cloud on the planet already right now. >>Right. Yep. >>Which is kind of interesting because yeah. If you go back to when, what 2016 or so when VMC was at least baned about yeah. Is that right? A lot of people were skeptical. I was skeptical very long history with VMware at the time. And I was skeptical. I I'm thinking, nah, it's not gonna work. Yeah. This is desperation. Sorry, pat. I love you. But it's desperation. Right. AWS, their attitude is in this transaction. Sure. Send us some customers we'll them. Yeah. Right. I very, very cynical about it. Completely proved me wrong. Obviously. Where did it go? Went from AWS to Azure to right. Yeah. To GCP, to Oracle, >>Oracle, Alibaba, >>Alibaba. Yep. Globally. >>We've got IBM. Yep. Right. >>Yeah. So along the way, it would be easy to look at that trajectory and say, okay, wow, hyperscale cloud. Yeah. Everything's consolidating great. There's gonna be five or six or 10 of these players. And that's it. And everybody else is out in the cold. Yeah. But it turns out that long tail, if you look at the chart of who the largest VCP P partners are, that long tail of the smaller ones seem to be carving out specialized yes. Niches where you can imagine now, at some point in the future, you sum up this long tail and it becomes larger than maybe one of the hyperscale cloud providers. Right. I don't think a lot of people predicted that. I think, I think people predicted the demise of VMware and frankly, a lot of people in the VMware ecosystem, just like they predicted the demise of the mainframe. Sure. The storage area network fill in the blank. I >>Mean, Jeff and I we've oh yeah. We've been on the, Jeff's been a little longer than I have, but we've been working together for 10 plus years on this. And we've, we've heard that many times. Yeah. Yeah. Our, our ecosystem has grown over the years. We've seen some consolidation, some M and a activity, but we're, we're not even actively recruiting partners and it's growing, we're focused on helping our partners gain more, share internally, gain, more share at wallet, but we're still getting organic growth in the program. Really. So it, it shows, I think that there is value in what we can offer them as a platform to build a cloud on. >>Yeah. What's been interesting is there's there's growth and there's some transition as well. Right? So there's been traditional cloud providers. Who've built a cloud in their data center, some sovereign, some not. And then there's other partners that are adopting VCP P because of our SA. So we've either converted some technology from product into SA or we've built net new SA or we've acquired companies that have been SA only. And now we have a bigger portfolio that service providers, cloud providers, managed service providers are all interested in. So you get resellers channel partners. Who've historically been doing ELAs and reselling to end customers. They're transitioning their business into doing recurring revenue and the only game in town where you really wanna do recurring revenues, VCP P. So our ecosystem is both growing because our cloud providers with their data center are doing more with our customers. And then we're adding more managed service providers because of our SA portfolio. And that, that, that combo, that one, two punch is creating a much bigger VCP P ecosystem overall. >>Yeah. >>Impressive. >>Do you think we have a better idea of what sovereign cloud means? Yes. I think we do. >>It's not Royal. >>It's all about royalty, >>All royalty. What are some of the things Jeff, as we look on the horizon, obviously seven to 10,000 people here at, at VMwares where people really excited to be back. They want to hear it from VMware. They wanna hear from its partner ecosystem, the community. What are some of the things that you think are on the horizon where sovereign cloud is concerned that are really opportunities yeah. For businesses to get it right. >>Yeah. We're in the early days of this, I think there's still a whole bunch of rules, regulatory laws that have not been defined yet. So I think there's gonna be some more learning. There's gonna be some top down guidance like Gaia X in Europe. That's the way that they're defining who gets access and control over what data and what's in. And what's out of that. So we're gonna get more of these Gaia X type things happening around the world, and they're all gonna be slightly different. Everyone's gonna have to understand what they are, how to interpret and then build something around them. So we need to stay on top of that, myself and Jay, to make sure that we've got the right cloud providers in the right space to capitalize on that, build out the sovereign cloud program over time and make sure that what they're building to support aligns with these different requirements that are out there across different countries. So it's an evolving landscape. That's >>Yeah. And one of the things too, we're also doing from a product perspective to better enable partners to, to address these sovereign cloud workloads is where we have, we have gaps maybe in our portfolio is we're partner partnering with some of our ISVs, like a, Konic like a Forex vem. So we can give our partners object storage or ransomware protection to add on to their sovereign cloud service, all accessible through our cloud director consult. So we're, we're enhancing the program that way. And to Jeff's point earlier, we've got 20 partners today. We're hoping to double that by the end of our fiscal year and, and just take a very methodical approach to growth of the program. >>Sounds great guys, early innings though. Thank you so much for joining Dave and me talking about what software and cloud is describing it to us, and also talking about the difference between that data residency and all the, all of the challenges and the, in the landscape that customers are facing. They can go turn to VMware and its ecosystem for that help. We appreciate your insights and your time. Guys. Thank >>You >>For >>Having us. Our >>Pleasure. Appreciate it >>For our guests and Dave Nicholson. I'm Lisa Martin. You've been watching the cube. This is the end of day, two coverage of VMware Explorer, 2022. Have a great rest of your day. We'll see you tomorrow.

(upbeat music) >> Okay, welcome back everyone. CUBE's coverage here in Boston, Massachusetts, AWS re:inforce 22, security conference. It's AWS' big security conference. Of course, theCUBE's here, all the reinvent, reese, remars, reinforced. We cover 'em all now and the summits. I'm John Furrier, my host Dave Vellante. We have IDC weighing in here with their analysts. We've got some great guests here, Jay Bretzmann research VP at IDC and Philip Bues research manager for Cloud security. Gentlemen, thanks for coming on. >> Thank you. >> Appreciate it. Great to be here. >> Appreciate coming. >> Got a full circle, right? (all laughing) Security's more interesting than storage, isn't it? (all laughing) >> Dave and Jay worked together. This is a great segment. I'm psyched that you guys are here. We had Crawford and Matt Eastwood on at HPE Discover a while back and really the data you guys are getting and the insights are fantastic. So congratulations to IDC. You guys doing great work. We appreciate your time. I want to get your reaction to the event and the keynotes. AWS has got some posture and they're very aggressive on some tones. Some things that we didn't hear. What's your reaction to the keynote? Share your assessment. >> So, you know, I manage two different research services at IDC right now. They are both Cloud security and identity and digital security, right? And what was really interesting is the intersection between the two this morning, because every one of those speakers that came on had something to say about identity or least privileged access, or enable MFA, or make sure that you control who gets access to what and deny explicitly. And it's always been a challenge a little bit in the identity world because a lot of people don't use MFA. And in RSA, that was another big theme at the RSA conference, MFA everywhere. Why don't they use it? Because it introduces friction and all of a sudden people can't get their jobs done. And the whole point of a network is letting people on to get that data they want to get to. So that was kind of interesting, but as we have in the industry, this shared responsibility model for Cloud computing, we've got shared responsibility for between Philip and I. (Philip laughing) I have done in the past more security of the Cloud and Philip is more security in the Cloud. >> So yeah. >> And now with Cloud operation Super Cloud, as we call it, you have on premises, private Cloud coming back, or hasn't really gone anywhere, all that on premises, Cloud operations, public Cloud, and now edge exploding with new requirements. It's really an ops challenge right now. Not so much dev. So the sec and op side is hot right now. >> Yeah, well, we've made this move from monolithic to microservices based applications. And so during the keynote this morning, the announcement around the GuardDuty Malware Protection component, and that being built into the pricing of current GuardDuty, I thought was really key. And there was also a lot of talk about partnering in security certifications, which is also so very important. So we're seeing this move towards filling in that talent gap, which I think we're all aware of in the security industry. >> So Jake, square the circle for me. So Kirk Coofell talked about Amazon AWS identity, where does AWS leave off, and companies like Okta or Ping identity or Cybertruck pickup, how are they working together? Does it just create more confusion and more tools for customers? We know the overused word of seamless. >> Yeah, yeah. >> It's never seamless, so how should we think about that? >> So, identity has been around for 35 years or something like that. Started with the mainframes and all that. And if you understand the history of it, you make more sense to the current market. You have to know where people came from and the baggage they're carrying, 'cause they're still carrying a lot of that baggage. Now, when it comes to the Cloud Service providers, they're more an accommodation from the identity standpoint. Let's make it easy inside of AWS to let you single sign on to anything in the Cloud that they have, right? Let's also introduce an additional MFA capability to keep people safer whenever we can and provide people with tools, to get into those applications somewhat easily, while leveraging identities that may live somewhere else. So there's a whole lot of the world that is still active, directory-centric, right? There's another portion of companies that were born in the Cloud that were able to jump on things like Okta and some of the other providers of these universal identities in the Cloud. So, like I said, if you understand where people came from in the beginning, you start to say, "Yeah, this makes sense." >> It's interesting you talk about mainframe. I always think about Rack F, you know. And I say, "Okay, who did what, when, where?" And you hear about a lot of those themes. So what's the best practice for MFA, that's non-SMS-based? Is it you got to wear something around your neck, is it to have sort of a third party authenticator? What are people doing that you guys would recommend? >> Yeah, one quick comment about adoption of MFA. If you ask different suppliers, what percent of your base that does SSO also does MFA, one of the biggest suppliers out there, Microsoft will tell you it's under 25%. That's pretty shocking. All the messaging that's come out about it. So another big player in the market was called Duo, Cisco bought them. >> Yep. >> And because they provide networks, a lot of people buy their MFA. They have probably the most prevalent type of MFA, it's called Push. And Push can be a red X and a green check mark to your phone, it can be a QR code, somewhere, it can be an email push as well. So that is the next easiest thing to adopt after SMS. And as you know, SMS has been denigrated by NIST and others saying, it's susceptible to man and middle attacks. It's built on a telephony protocol called SS7. Predates anything, there's no certification either side. The other real dynamic and identity is the whole adoption of PKI infrastructure. As you know, certificates are used for all kinds of things, network sessions, data encryption, well, identity increasingly. And a lot of the consumers and especially the work from anywhere, people these days have access through smart devices. And what you can do there, is you can have an agent on that smart device, generate your private key and then push out a public key and so the private key never leaves your device. That's one of the most secure ways to- >> So if our SIM card gets hacked, you're not going to be as vulnerable? >> Yeah, well, the SIM card is another challenge associated with the older ways, but yeah. >> So what do you guys think about the open source connection and they mentioned it up top. Don't bolt on security, implying shift left, which is embedding it in like sneak companies, like sneak do that. Very container oriented, a lot of Kubernetes kind of Cloud native services. So I want to get your reaction to that. And then also this reasoning angle they brought up. Kind of a higher level AI reasoning decisions. So open source, and this notion of AI reasoning. or AI reason. >> And you see more open source discussion happening, so you have your building maintaining and vetting of the upstream open source code, which is critical. And so I think AWS talking about that today, they're certainly hitting on a nerve, as you know, open source continues to proliferate. Around the automated reasoning, I think that makes sense. You want to provide guide rails and you want to provide roadmaps and you want to have sort of that guidance as to, okay, what's a correlation analysis of different tools and products? And so I think that's going to go over really well, yeah. >> One of the other key points about open source is, everybody's in a multi-cloud world, right? >> Yeah. >> And so they're worried about vendor lock in. They want an open source code base, so that they don't experience that. >> Yeah, and they can move the code around, and make sure it works well on each system. Dave and I were just talking about some of the dynamics around data control planes. So they mentioned encrypt everything which is great and I message by the way, I love that one. But oh, and he mentioned data at rest. I'm like, "What about data in flight? "Didn't hear that one." So one of the things we're seeing with SuperCloud, and now multi-cloud kind of as destinations of that, is that in digital transformation, customers are leaning into owning their data flows. >> Yeah. >> Independent of say the control plane aspects of what could come in. This is huge implications for security, where sharing data is huge, even Schmidt on stage said, we have billions and billions of things happening that we see things that no one else sees. So that implies, they're sharing- >> Quad trillion. >> Trillion, 15 zeros. (Jay laughs) >> 15 zeros. >> So that implies they're sharing that or using that pushing that into something. So sharing is huge with cyber security. So that implies open data, data flows. How do you guys see this evolving? I know it's kind of emerging, but it's becoming a nuanced point, that's critical to the architecture. >> Well, yeah, I think another way to look at that is the sharing of intelligence and some of the recent directives, from the executive branch, making it easier for private companies to share data and intelligence, which I think strengthens the cyber community overall. >> Depending upon the supplier, it's either an aggregate level of intelligence that has been anonymized or it's specific intelligence for your environment that everybody's got a threat feed, maybe two or three, right? (John laughs) But back to the encryption point, I mean, I was working for an encryption startup for a little while after I left IBM, and the thing is that people are scared of it. They're scared of key management and rotation. And so when you provide- >> Because they might lose the key. >> Exactly. >> Yeah. >> It's like shooting yourself in the foot, right? So that's when you have things like, KMS services from Amazon and stuff that really help out a lot. And help people understand, okay, I'm not alone in this. >> Yeah, crypto owners- >> They call that hybrid, the hybrid key, they don't know how they call the data, they call it the hybrid. What was that? >> Key management service? >> The hybrid- >> Oh, hybrid HSM, correct? >> Yeah, what is that? What is that? I didn't get that. I didn't understand what he meant by the hybrid post quantum key agreement. >> Hybrid post quantum key exchange. >> AWS never made a product name that didn't have four words in it. (John laughs) >> But he did reference the new NIST algos. And I think I inferred that they were quantum proof or they claim to be, and AWS was testing those. >> Correct, yeah. >> So that was kind of interesting, but I want to come back to identity for a second. So, this idea of bringing traditional IAM and Privileged Access Management together, is that a pipe dream, is that something that is actually going to happen? What's the timeframe, what's your take on that? >> So, there are aspects of privilege in every sort of identity. Back when it was only the back office that used computers for calculations, right? Then you were able to control how many people had access. There were two types of users, admins and users. These days, everybody has some aspect of- >> It's a real spectrum, really. >> Yeah. >> Granular. >> You got the C-suite, the finance people, the DevOps people, even partners and whatever. They all need some sort of privileged access, and the term you hear so much is least-privileged access, right? Shut it down, control it. So, in some of my research, I've been saying that vendors who are in the PAM space, Privilege Access Management space, will probably be growing their suites, playing a bigger role, building out a stack, because they have the expertise and the perspective that says, "We should control this better." How do we do that, right? And we've been seeing that recently. >> Is that a combination of old kind of antiquated systems meets for proprietary hyper scale, or kind of like build your own? 'Cause I mean, Amazon, these guys, Facebook, they all build their own stuff. >> Yes, they do. >> Then enterprises buy services from general purpose identity management systems. >> So as we were talking about knowing the past and whatever, Privileged Access Management used to be about compliance reporting. Just making sure that I knew who accessed what? And could prove it, so I didn't fail at all. >> It wasn't a critical infrastructure item. >> No, and now these days, what it's transitioning into, is much more risk management, okay. I know what our risk is, I'm ahead of it. And the other thing in the PAM space, was really session monitor. Everybody wanted to watch every keystroke, every screen's scrape, all that kind of stuff. A lot of the new Privileged Access Management, doesn't really require that. It's a nice to have feature. You kind of need it on the list, but is anybody really going to implement it? That's the question, right. And then if you do all that session monitoring, does anybody ever go back and look at it? There's only so many hours in the day. >> How about passwordless access? (Jay laughs) I've heard people talk about that. I mean, that's as a user, I can't wait but- >> Well, it's somewhere we want to all go. We all want identity security to just disappear and be recognized when we log in. So the thing with passwordless is, there's always a password somewhere. And it's usually part of a registration action. I'm going to register my device with a username password, and then beyond that I can use my biometrics, right? I want to register my device and get a private key, that I can put in my enclave, and I'll use that in the future. Maybe it's got to touch ID, maybe it doesn't, right? So even though there's been a lot of progress made, it's not quote, unquote, truly passwordless. There's a group, industry standards group called Fido. Which is Fast Identity Online. And what they realized was, these whole registration passwords, that's really a single point of failure. 'Cause if I can't recover my device, I'm in trouble. So they just did new extension to sort of what they were doing, which provides you with much more of like an iCloud vault that you can register that device in and other devices associated with that same identity. >> Get you to it if you have to. >> Exactly. >> I'm all over the place here, but I want to ask about ransomware. It may not be your wheelhouse. But back in the day, Jay, remember you used to cover tape. All the backup guys now are talking about ransomware. AWS mentioned it today and they showed a bunch of best practices and things you can do. Air gaps wasn't one of them. I was really surprised 'cause that's all every anybody ever talks about is air gaps and a lot of times that air gap could be a guess to the Cloud, I guess, I'm not sure. What are you guys seeing on ransomware apps? >> We've done a lot of great research around ransomware as a service and ransomware, and we just had some data come out recently, that I think in terms of spending and spend, and as a result of the Ukraine-Russia war, that ransomware assessments rate number one. And so it's something that we encourage, when we talk to vendors and in our services, in our publications that we write about taking advantage of those free strategic ransomware assessments, vulnerability assessments, as well and then security and training ranked very highly as well. So, we want to make sure that all of these areas are being funded well to try and stay ahead of the curve. >> Yeah, I was surprised to not see air gaps on the list, that's all everybody talks about. >> Well, the old model for air gaping in the land days, the novel days, you took your tapes home and put them in the sock drawer. (all laughing) >> Well, it's a form of air gap. (all laughing) >> Security and no one's going to go there and clean out. >> And then the internet came around and ruined it. >> Guys, final question we want to ask you, guys, we kind of zoom out, great commentary by the way. Appreciate it. We've seen this in many markets, a collection of tools emerge and then there's its tool sprawl. So cyber we're seeing the trend now where mon goes up on stage of all the ecosystems, probably other vendors doing the same thing where they're organizing a platform on top of AWS to be this super platform, for super Cloud capability by building a more platform thing. So we're saying there's a platform war going on, 'cause customers don't want the complexity. I got a tool but it's actually making it more complex if I buy the other tool. So the tool sprawl becomes a problem. How do you guys see this? Do you guys see this platform emerging? I mean tools won't go away, but they have to be easier. >> Yeah, we do see a consolidation of functionality and services. And we've been seeing that, I think through a 2020 Cloud security survey that we released that was definitely a trend. And that certainly happened for many companies over the last six to 24 months, I would say. And then platformization absolutely is something we talk and write about all the time so... >> Couple of years ago, I called the Amazon tool set an erector set because it really required assembly. And you see the emphasis on training here too, right? You definitely need to go to AWS University to be competent. >> It wasn't Lego blocks yet. >> No. >> It was erector set. >> Yeah. >> Very good distinction. >> Loose. >> And you lose a few. (chuckles) >> But still too many tools, right? You see, we need more consolidation. It's getting interesting because a lot of these companies have runway and you look at sale point at stock prices held up 'cause of the Thoma Bravo acquisition, but all the rest of the cyber stocks have been crushed especially the high flyers, like a Sentinel-1 one or a CrowdStrike, but just still M and A opportunity. >> So platform wars. Okay, final thoughts. What do you, think is happening next? What's your outlook for the next year or so? >> So, in the identity space, I'll talk about, Philip can cover Cloud for us. It really is more consolidation and more adoption of things that are beyond simple SSO. It was, just getting on the systems and now we really need to control what you're able to get to and who you are. And do it as transparently as we possibly can, because otherwise, people are going to lose productivity. They're not going to be able to get to what they want. And that's what causes the C-suite to say, "Wait a minute," DevOps, they want to update the product every day. Make it better. Can they do that or did security get in the way? People, every once in a while call security, the Department of No, right? >> They ditch it on stage. They want to be the Department of Yes. >> Exactly. >> Yeah. >> And the department that creates additional value. If you look at what's going on with B2C or CIAM, consumer oriented identity, that is all about opening up new direct channels and treating people like their old friends, not like you don't know them, you have to challenge them. >> We always say, you want to be in the boat together, it sinks or not. >> Yeah. Exactly. >> Philip I'm glad- >> Okay, what's your take? What's your outlook for the year? >> Yeah, I think, something that we've been seeing as consolidation and integration, and so companies looking at from built time to run time, investing in shift left infrastructure is code. And then also in the runtime detection, makes perfect sense to have both the agent and agent lists so that you're covering any of the gaps that might exist. >> Awesome, Jay Phillip, thanks for coming on "theCUBE" with IDC and sharing your- >> Oh, our pleasure- >> Perspective, commentary and insights and outlook. Appreciate it. >> You bet. >> Thank you. >> Okay, we've got the great direction here from IDC analyst here on the queue. I'm John Furrier, Dave Vellante. Be back more after this short break. (bright upbeat music)

>>Okay, welcome back everyone. Cube's coverage here in Boston, Massachusetts, AWS reinforced 22, the security conference. It's ADOS big security conference. Of course, the cubes here, all the reinvent res re Mars reinforce. We cover 'em all now and the summits. I'm John. Very my host, Dave ante have IDC weighing in here with their analysis. We've got some great guests here, Jay Brisbane, research VP at IDC and Philip who research managed for cloud security. Gentlemen, thanks for coming on. Thank you. Appreciate it. Great >>To, to be here. I appreciate the got the full >>Circle, right? Just, security's more interesting >>Than storage. Isn't it? >>Dave, Dave and Jay worked together. This is a, a great segment. I'm psyched that you guys are here. We had Crawford and Matt Eastwood on at HPE discover a while back and really the, the, the data you guys are getting and the insights are fantastic. So congratulations to IDC. You guys doing great work. We appreciate your time. I wanna get your reaction to the event and the keynotes. AWS has got some posture and they're very aggressive on some tones. Some things that they didn't, we didn't hear. What's your reaction to the keynote, share your, your assessment. >>So, you know, I managed two different research services at IDC right now. They are both cloud security and identity and, and digital security. Right. And what was really interesting is the intersection between the two this morning, because every one of those speakers that came on had something to say about identity or least privileged access, or, you know, enable MFA, or make sure that you, you know, control who gets access to what and deny explicitly. Right? And it's always been a challenge a little bit in the identity world because a lot of people don't use MFA. And in RSA, that was another big theme at the RSA conference, right? MFA everywhere. Why don't they use it because it introduces friction and all of a sudden people can't get their jobs done. Right. And the whole point of a network is letting people on to get that data they want to get to. So that was kind of interesting, but, you know, as we have in the industry, this shared responsibility model for cloud computing, we've got shared responsibility for between Philip and I, I have done in the ke past more security of the cloud and Philip is more security in the cloud, >>So yeah. And it's, and now with cloud operation, super cloud, as we call it, you have on premises, private cloud coming back, or hasn't really gone anywhere, all that on premises, cloud operations, public cloud, and now edge exploding with new requirements. Yeah. It's really an ops challenge right now. Not so much dev. So the sick and op side is hot right now. >>Yeah. Well, we've made this move from monolithic to microservices based applications. And so during the keynote this morning, the announcement around the guard duty malware protection component, and that being built into the pricing of current guard duty, I thought was, was really key. And there was also a lot of talk about partnering in security certifications. Yeah. Which is also so very important. So we're seeing this move towards filling in that talent gap, which I think we're all aware of in the security industry. >>So Jake square, the circle for me. So Kirk, Coel talked about Amazon AWS identity, where does AWS leave off and, and companies like Okta or ping identity or crock pickup, how are they working together? Does it just create more confusion and more tools for customers? We, we have, we know the over word overused word of seamless. Yeah. Yeah. It's never seamless. So how should we think about that? >>So, you know, identity has been around for 35 years or something like that started with the mainframes and all that. And if you understand the history of it, you make more sense to the current market. You have to know where people came from and the baggage they're carrying, cuz they're still carrying a lot of that baggage. Now, when it comes to the cloud service providers, they're more an accommodation from the identity standpoint, let's make it easy inside of AWS to let you single sign on to anything in the cloud that they have. Right. Let's also introduce an additional MFA capability to keep people safer whenever we can and, you know, provide people the tools to, to get into those applications somewhat easily, right. While leveraging identities that may live somewhere else. So, you know, there's a whole lot of the world that is still active directory centric, right? There's another portion of companies that were born in the cloud that were able to jump on things like Okta and some of the other providers of these universal identities in the cloud. So, you know, like I said, you, if you understand where people came from in the beginning, you start to, to say, yeah, this makes sense. >>It's, it's interesting. You talk about mainframe. I, I always think about rack F you know, and I say, okay, who did what, when, where, yeah. And you hear about a lot of those themes. What, so what's the best practice for MFA? That's, that's non SMS based. Is it, you gotta wear something around your neck, is it to have sort of a third party authenticator? What are people doing that is that, that, that you guys would recommend? >>Yeah. One quick comment about adoption of MFA. You know, if you ask different suppliers, what percent of your base that does SSO also does MFA one of the biggest suppliers out there Microsoft will tell you it's under 25%. That's pretty shocking. Right? All the messaging that's come out about it. So another big player in the market was called duo. Cisco bought them. Yep. Right. And because they provide networks, a lot of people buy their MFA. They have probably the most prevalent type of MFA it's called push. Right. And push can be, you know, a red X and a green check mark to your phone. It can be a QR code, you know, somewhere, it can be an email push as well. So that is the next easiest thing to adopt after SMS. And as you know, SMS has been denigrated by N and others saying, you know, it's susceptible to man and middle attacks. >>It's built on a telephony protocol called SS seven. Yep. You know, predates anything. There's no certification, either side. The other real dynamic and identity is the whole adoption of PKI infrastructure. As you know, certificates are used for all kinds of things, network sessions, data encryption, well identity increasingly, and a lot of the, you know, consumers and especially the work from anywhere, people these days have access through smart devices. Right. And what you can do there is you can have an agent on that smart device, generate your private key and then push out a public key. And so the private key never leaves your device. That's one of the most secure ways to, so if your >>SIM card gets hacked, you're not gonna be as at vulnerable >>Or as vulnerable. Well, the SIM card is another, you know, challenge associated with the, the older waste. But yeah. Yeah. >>So what do you guys think about the open source connection and, and they, they mentioned it up top don't bolt on security implying shift left, which is embedding it in like sneak companies, like sneak do that, right. Container oriented, a lot of Kubernetes kind of cloud native services. So I wanna get your reaction to that. And then also this reasoning angle, they brought up kind of a higher level AI reasoning decisions. So open source and this notion of AI reasoning >>Automation. Yeah. And, and you see more open source discussion happening, right. So you, you know, you have your building maintaining and vetting of the upstream open source code, which is critical. And so I think AWS talking about that today, they're certainly hitting on a nerve as, you know, open source continues to proliferate around the automated reasoning. I think that makes sense. You know, you want to provide guiderails and you want to provide roadmaps and you wanna have sort of that guidance as to okay. What's the, you know, a correlation analysis of different tools and products. And so I think that's gonna go over really well. >>Yeah. One of the other, you know, key points of what open source is, everybody's in a multi-cloud world, right? Yeah. And so they're worried about vendor lockin, they want an open source code base so that they don't experience that. >>Yeah. And they can move the code around and make sure it works well on each system. Dave and I were just talking about some of the dynamics around data control planes. So yeah. They mentioned encrypt everything, which is great. And I message, by the way, I love that one, but oh. And he mentioned data at rest. I'm like, what about data in flight? Didn't hear that one. So one of the things we're seeing with super cloud, and now multi-cloud kind of, as destinations of that, is that in digital transformation, customers are leaning into owning their data flows. >>Yeah. >>Independent of say the control plane aspects of what could come in. This is huge implications for security, where sharing data is huge. Even Schmidt on Steve said we have billions and billions of things happening that we see things that no one else else sees. So that implies, they're >>Sharing quad trillion, >>Trillion, 15 zeros trillion. Yeah. 15 >>Zeros, 15 zeros. Yeah. >>So that implies, they're sharing that or using that, pushing that into something. So sharing's huge with cyber security. So that implies open data, data flows. What do, how do you guys see this evolving? I know it's kind of emerging, but it's becoming a, a nuanced point that's critical to the architecture. >>Well, I, yeah, I think another way to look at that is the sharing of intelligence and some of the recent directives, you know, from the executive branch, making it easier for private companies to share data and intelligence, which I think strengthens the cyber community overall, >>Depending upon the supplier. Right? Yeah. It's either an aggregate level of intelligence that has been, you know, anonymized or it's specific intelligence for your environment that, you know, everybody's got a threat feed, maybe two or three, right. Yeah. But back to the encryption point, I mean, I was working for an encryption startup for a little while. Right after I left IBM. And the thing is that people are scared of it. Right. They're scared of key management and rotation. And so when you provide, >>Because they might lose the key. >>Exactly. Yeah. It's like shooting yourself in the foot. Right. So that's when you have things like, you know, KMS services from Amazon and stuff, they really help out a lot and help people understand, okay, I'm not alone in this. >>Yeah. Crypto >>Owners, they call that hybrid, the hybrid key, they call the, what they call the, today. They call it the hybrid. >>What was that? The management service. Yeah. The hybrid. So hybrid HSM, correct. >>Yeah. What is that? What is that? I didn't, I didn't get that. I didn't understand what he meant by the hybrid post hybrid, post quantum key agreement. Right. That still notes >>Hybrid, post quantum key exchange, >>You know, AWS never made a product name that didn't have four words in it, >>But he did, but he did reference the, the new N algos. And I think I inferred that they were quantum proof or the claim it be. Yeah. And AWS was testing those. Correct. >>Yeah. >>So that was kind of interesting, but I wanna come back to identity for a second. Okay. So, so this idea of bringing traditional IAM and, and privilege access management together, is that a pipe dream, is that something that is actually gonna happen? What's the timeframe, what's your take on that? >>So, you know, there are aspects of privilege in every sort of identity back when, you know, it was only the back office that used computers for calculations, right? Then you were able to control how many people had access. There were two types of users, admins, and users, right? These days, everybody has some aspect of, >>It's a real spectrum, really >>Granular. You got the, you know, the C suite, the finance people, the DevOps, people, you know, even partners and whatever, they all need some sort of privileged access. And the, the term you hear so much is least privileged access. Right? Shut it down, control it. So, you know, in some of my research, I've been saying that vendors who are in the Pam space privilege access management space will probably be growing their suites, playing a bigger role, building out a stack because they have, you know, the, the expertise and the, and the perspective that says we should control this better. How do we do that? Right. And we've been seeing that recently, >>Is that a combination of old kind of antiquated systems meets for proprietary hyperscale or kind of like build your own? Cause I mean, Amazon, these guys, they Facebook, they all build their own stuff. >>Yes. They >>Do enterprises buy services from general purpose identity management systems. >>So as we were talking about, you know, knowing the past and whatever privileged access management used to be about compliance reporting. Yeah. Right. Just making sure that I knew who accessed what and could prove it. So I didn't fail in art. It wasn't >>A critical infrastructure item. >>No. And now these days, what it's transitioning into is much more risk management. Okay. I know what our risk is. I'm ahead of it. And the other thing in the Pam space was really session monitor. Right. Everybody wanted to watch every keystroke, every screen's scrape, all that kind of stuff. A lot of the new privilege access Mon management doesn't really require that it's nice to have feature. You kind of need it on the list, but is anybody really gonna implement it? That's the question. Right. And then, you know, if, if you do all that session monitor, does anybody ever go back and look at it? There's only so many hours in the day. >>How about passwordless access? You know? Right. I've heard people talk about that. Yeah. I mean, that's as a user, I can't wait, but >>It's somewhere we want to all go. Yeah. Right. We all want identity security to just disappear and be recognized when we log in. So the, the thing with password list is there's always a password somewhere and it's usually part of a registration, you know, action. I'm gonna register my device with a username password. And then beyond that, I can use my biometrics. Right. I wanna register my device and get a private key that I can put in my enclave. And I'll use that in the future. Maybe it's gotta touch ID. Maybe it doesn't. Right. So even though there's been a lot of progress made, it's not quote unquote, truly passwordless, there's a group industry standards group called Fido. Right. Which is fast identity online. And what they realized was these whole registration passwords. That's really a single point of failure. Cuz if I can't recover my device, I'm in trouble. Yeah. So they just did a, a new extension to sort of what they were doing, which provides you with much more of a, like an iCloud vault, right. That you can register that device in and other devices associated with that same iPad that you can >>Get you to it. If you >>Have to. Exactly. I had >>Another have all over the place here, but I, I want to ask about ransomware. It may not be your wheelhouse. Yeah. But back in the day, Jay, remember you used to cover tape. All the, all the backup guys now are talking about ransomware. AWS mentioned it today and they showed a bunch of best practices and things you can do air gaps. Wasn't one, one of 'em. Right. I was really surprised cuz that's all, every anybody ever talks about is air gaps. And a lot of times that air gaps that air gap could be a guess to the cloud. I guess I'm not sure. What are you guys seeing on ransomware >>Apps? You know, we've done a lot of great research around ransomware as a service and ransomware and, and you know, we just had some data come out recently that I think in terms of spending and, and spend and in as a result of the Ukraine, Russia war, that ransomware assessments rate number one. And so it's something that we encourage, you know, when we talk to vendors and in our services, in our publications that we write about taking advantage of those free strategic ransomware assessments, vulnerability assessments, right. As well, and then security and training ranked very highly as well. So we wanna make sure that all of these areas are being funded well to try and stay ahead of the curve. >>Yeah. I was surprised that not the air gaps on the list, that's all everybody >>Talks about. Well, you know, the, the old model for air gaping in the, the land days, the Noel days, you took your tapes home and put 'em in the sock drawer. >>Well, it's a form of air gap security and no one's gonna go there >>Clean. And then the internet came around >>Guys. Final question. I want to ask you guys, we kind zoom out. Great, great commentary by the way. Appreciate it. As the, we've seen this in many markets, a collection of tools emerge and then there's it's tool sprawl. Oh yeah. Right? Yeah. So cyber we're seeing trend now where Mon goes up on stage of all the E probably other vendors doing the same thing where they're organizing a platform on top of AWS to be this super platform. If you super cloud ability by building more platform thing. So we're saying there's a platform war going on, cuz customers don't want the complexity. Yeah. I got a tool, but it's actually making it more complex if I buy the other tool. So the tool sprawl becomes a problem. How do you guys see this? Do you guys see this platform emerging? I mean, tools won't go away, but they have to be >>Easier. Yeah. We do see a, a consolidation of functionality and services. And we've been seeing that, I think through a 20, 20 flat security survey that we released, that that was definitely a trend. And you know, that certainly happened for many companies over the last six to 24 months, I would say. And then platformization absolutely is something we talk 'em right. About all the time. So >>More M and a couple of years ago, I called the, the Amazon tool set in rector set. Yeah. Because it really required assembly. Yeah. And you see the emphasis on training here too, right? Yeah. You definitely need to go to AWS university to be competent. It >>Wasn't Lego blocks yet. No, it was a rector set. Very good distinction rules, you know, and, and you lose a few. It's >>True. Still too many tools. Right. You see, we need more consolidation. That's getting interesting because a lot of these companies have runway and you look, you look at sale point, its stock prices held up cuz of the Toma Bravo acquisition, but all the rest of the cyber stocks have been crushed. Yeah. You know, especially the high flyers, like a Senti, a one or a crowd strike, but yeah, just still M and a opportunity >>Itself. So platform wars. Okay. Final thoughts. What do you thinks happening next? What's what's your outlook for the, the next year or so? >>So in the, in the identity space, I'll talk about Phillip can cover cloud force. You know, it really is more consolidation and more adoption of things that are beyond simple SSO, right. It was, you know, just getting on the systems and now we really need to control what you're able to get to and who you are and do it as transparently as we possibly can because otherwise, you know, people are gonna lose productivity, right. They're not gonna be able to get to what they want. And that's what causes the C-suite to say, wait a minute, you know, DevOps, they want to update the product every day. Right. Make it better. Can they do that? Or did security get in the way people every once in a while I'll call security, the department of no, right? Yeah. Well, >>Yeah. They did it on stage. Yeah. They wanna be the department of yes, >>Exactly. And the department that creates additional value. If you look at what's going on with B to C or C IAM, consumer identity, that is all about opening up new direct channels and treating people like, you know, they're old friends, right. Not like you don't know 'em you have to challenge >>'em we always say you wanna be in the boat together. It sinks or not. Yeah. Right. Exactly. >>Phillip, >>Okay. What's your take? What's your outlook for the year? >>Yeah. I think, you know, something that we've been seeing as consolidation and integration, and so, you know, companies looking at from built time to run time investing in shift left infrastructure is code. And then also in the runtime detection makes perfect sense to have both the agent and agentless so that you're covering any of the gaps that might exist. >>Awesome. Jerry, Phillip, thanks for coming on the queue with IDC and sharing >>Your oh our pleasure perspective. >>Commentary, have any insights and outlook. Appreciate it. You bet. Thank you. Okay. We've got the great direction here from IDC analyst here on the queue. I'm John for a Dave, we're back more after this shirt break.

(upbeat music) >> Okay, we're kicking off the program with our first segment. Jay Henderson is the vice president of product management at Alteryx. And we're going to talk about the trends and data where we came from, how we got here, where we're going. We got some launch news. Hello, Jay, welcome to theCUBE. >> Great to be here. Really excited to share some of the things we're working on. >> Yeah, thank you. So look, you have a deep product background, product management, product marketing. You've done strategy work. You've been around software and data your entire career, and we're seeing the collision of software, data, cloud, machine intelligence. Let's start with the customer and maybe we can work back from there. So if you're an analytics or a data executive at an organization, Jay, what's your north star? Where are you trying to take your company from a data and analytics point of view? >> Yeah, I mean, look, I think all organizations are really struggling to get insights out of their data. I think one of the things that we see is you've got digital exhaust creating large volumes of data. Storage is really cheap, so it doesn't cost them much to keep it. And that results in a situation where the organization's drowning in data, but somehow still starving for insights. And so I think, you know, when I talk to customers, they're really excited to figure out how they can put analytics in the hands of every single person in their organization, and really start to democratize the analytics and you know, let the business users and the whole organization get value out of all that data they have. >> And we're going to dig into that throughout this program. And data, I like to say is plentiful. Insights, not always so much. Tell us about your launch today, Jay. And thinking about the trends that just highlighted, the direction that your customers want to go, and the problems that you're solving. What role does the cloud play, and what is what you're launching, how does that fit in? >> Yeah, we're really excited today we're launching the Alteryx analytics cloud. That's really a portfolio of cloud-based solutions that have all been built from the ground up to be cloud native, and to take advantage of things like browser based access. So that it's really easy to give anyone access including folks on a Mac. It also lets you take advantage of elastic compute, so that you can do, you know, in database processing and cloud native solutions that are going to scale to solve the most complex problems. So we've got a portfolio of solutions, things like designer cloud, which is our flagship designer product in a browser and on the cloud. We've got Alteryx machine learning which helps up-skill, regular, old analyst, with advanced machine learning capabilities. We've got auto insights, which brings business users into the fold and automatically unearths insights using AI and machine learning. And we've got our latest edition which is Trifacta, that helps data engineers do data pipelining, and really, you know, create a lot of the underlying data sets that are used in some of this downstream analytics. >> So let's dig into some of those roles, if we could a little bit. I mean, traditionally Alteryx has served the the business analysts, and that's what designer cloud is fit for, I believe. And you've explained kind of the scope. Sorry, you've expanded that scope into the to the business user with Hyper Anna. And in a moment, we're going to talk to Adam Wilson and Suresh, about Trifacta. And that recent acquisition takes you as you said into the data engineering space and IT, but in thinking about the business analyst role, what's unique about designer cloud and how does it help these individuals? >> Yeah, I mean, really I go back to some of the feedback we've had from our customers which is, you know, they oftentimes have dozens or hundreds of seats of our designer desktop product. Really as they look to take the next step, they're trying to figure out, how do I give access to that, those types of analytics to thousands of people within the organization. And designer cloud is really great for that. You've got the browser based interface. So if folks are on a Mac, they can really easily just pop open the browser and get access to all of those prep and blend capabilities to a lot of the analysis we're doing. It's a great way to scale up access to the analytics and start to put it in the hands of really anyone in the organization, not just those highly skilled power users. >> Okay, great. So now then you add in the Hyper Anna acquisition. So now you're targeting the business user, Trifacta comes into the mix, that deeper IT angle that we talked about. How does this all fit together? How should we be thinking about the new Alteryx portfolio? >> Yeah, I mean, I think it's pretty exciting. When you think about democratizing analytics and providing access to all these different groups of people, you've not been able to do it through one platform before. It's not going to be one interface that meets the needs of all these different groups within the organization, you really do need purpose built specialized capabilities for each group. And finally today with the announcement of the Alteryx analytics cloud, we brought together all of those different capabilities, all of those different interfaces into a single end to end application. So, really finally delivering on the promise of providing analytics to all. >> How much of this have you been able to share with your customers and maybe your partners? I mean, I know all this is fairly new but have you been able to get any feedback from them? What are they saying about it? >> Yeah, I mean, it's pretty amazing. We ran early access and limited availability program, that let us put a lot of this technology in the hands of over 600 customers. >> Oh, wow. >> Over the last few months. So we have gotten a lot of feedback. I tell you, it's been overwhelmingly positive. I think organizations are really excited to unlock the insights that have been hidden in all this data they've got. They're excited to be able to use analytics in every decision that they're making so that the decisions they have are more informed and produce better business outcomes. And this idea that they're going to move from, you know, dozens to hundreds or thousands of people who have access to these kinds of capabilities, I think has been a really exciting thing that is going to accelerate the transformation that these customers are on. >> That's good. Those are good numbers for a preview mode. Let's talk a little bit about vision. So if democratizing data is the ultimate goal, which frankly has been elusive for most organizations. Over time, how's your cloud going to address the challenges of putting data to work across the entire enterprise? >> Yeah, I mean, I tend to think about the future and some of the investments we're making in our products and our roadmap across four big themes. And these are really kind of enduring themes that you're going to see us making investments in over the next few years. The first is having cloud centricity. The data gravity has been moving to the cloud. We need to be able to provide access, to be able to ingest and manipulate that data, to be able to write back to it to provide cloud solutions. So, the first one is really around cloud centricity. The second is around big data fluency. Once you have all of that data you need to be able to manipulate it in a performant manner. So, having the elastic cloud infrastructure and in-database processing is so important. The third is around making AI a strategic advantage. So, you know, getting everyone involved in accessing AI and machine learning to unlock those insights, getting it out of the hands of the small group of data scientists, putting it in the hands of analysts and business users. And then the fourth thing is really providing access across the entire organization, IT and data engineers, as well as business owners and analysts. So, cloud centricity, big data fluency, AI as a strategic advantage, and personas across the organization, are really the the four big themes you're going to see us working on over the next few months and coming years. >> That's good, thank you for that. So on a related question, how do you see the data organizations evolving? I mean, traditionally you've had, you know monolithic organizations, very specialized, or I might even say hyper specialized roles. And your mission, of course, as the customer, you and your customers, they want to democratize the data. And so, it seems logical that domain leaders are going to take more responsibility for data life cycles, for data ownerships, low code becomes more important. And perhaps there's kind of challenges the historically highly centralized and really specialized roles that I just talked about. How do you see that evolving, and what role will Alteryx play? >> Yeah, I think we'll see sort of a more federated system start to emerge. Those centralized groups are going to continue to exist, but they're going to start to empower in a much more decentralized way, the people who are closer to the business problems and have better business understanding. I think that's going to let the centralized highly skilled teams work on problems that are of higher value to the organization. The kinds of problems where one or 2% lift in the model result in millions of dollars a day for the business. And then by pushing some of the analytics out closer to the edge and closer to the business, you'll be able to, you know, apply those analytics in every single decision. So I think you're going to see both the decentralized and centralized model start to work in harmony in a little bit more of a, almost a federated sort of way. And I think the exciting thing for us at Alteryx is, you know, we want to facilitate that. We want to give analytic capabilities and solutions to both groups and types of people. We want to help them collaborate better, and drive business outcomes with the analytics they're using. >> Yeah, I mean, I think my take on it, I wonder if you could comment is, to me the technology should be an operational detail. And it has been the dog that wags the tail or maybe the other way around. You mentioned digital exhaust before. I mean, essentially it's digital exhaust coming out of operational systems that then it somehow eventually end up in the hand of the domain users. And I wonder if increasingly we're going to see those domain users, those line of business experts get more access, that's your goal. And then even go beyond analytics, start to build data products that could be monitized. And that maybe it's going to take a decade to play out, but that is sort of a new era of data. Do you see it that way? >> Absolutely. We're actually making big investments in our products and capabilities to be able to create analytic applications, and to enable somebody who's an analyst or a business user to create an application on top of the data and analytics layers that they have, really to help democratize the analytics, to help pre-package some of the analytics that can drive more insights. So I think that's definitely a trend we're going to see more of. >> Yeah, and to your point, if you confederate the governance and automate that... >> Yep. Absolutely. >> Then that can happen. I mean, that's a key part of it, obviously, so... >> Yep. >> All right, Jay, we have to leave it there. Up next, we take a deep dive into the Alteryx recent acquisition of Trifacta with Adam Wilson, who led Trifacta for more than seven years, and Suresh Vittal, who is the chief product officer at Alteryx, to explain the rationale behind the acquisition, and how it's going to impact customers. Keep it right there. You're watching theCUBE, your leader in enterprise tech coverage. (upbeat music)

(upbeat music) >> Okay, we're back at AWS re:Invent 2021. You're watching theCUBE. My name is Dave Vellante, and we're here with Jay Theodore who's the CTO of Enterprise and AI at Esri and he's joined by Dave Cardella, who's the Principal Product Manager for Developer Technologies also at Esri. Guys, thanks for coming on. Welcome to theCUBE. >> Thanks, Dave. >> Thanks, Dave. >> Jay, maybe you could give us a little background on Esri. What do you guys do? What are you all about? >> Sure. Esri is an old timer, we are a 50-year old software company. We are the pioneers in GIS and the world leader in GIS - geographic information system. We build geospatial infrastructure that's built for the cloud, built for the edge, built for the field also, you can say. So, we do mapping and analytics. We help our customers solve very complex challenges by bringing location intelligence into the mix. Our customers sort of like run the world, transform the world and we sort of like empower them with the technology we have. So, that's what we do. >> The original edge, and now of course, AWS is coming to you. >> Yeah. (both interviewees chuckling) >> Who are your customers, your main customers? Maybe share that. >> Yeah. We've got over 350,000 customers in... (Dave Cardella chuckling) Yeah. We're all- >> Dave Vellante: Scale. >> Yeah. (Dave Vellante laughing) In the public sector, especially, commercial businesses, non-profit organizations, and that really represents tens of millions of users globally. >> So, let's talk a little bit more about how things are changing. As they say, the edge is coming to you. Maybe AI, you know, 50 years ago... Actually, 50 years ago is probably a lot of talk about AI. When I came into the business, you know, it was a lot of chatter about it. But now, it's real. All this data that we have and the compute power, the cost is coming down. So, AI is in your title? >> Jay: Yes. >> Tell us more about that. >> I think that AI's come to age. When I went to grad school, AI was still in theory because we didn't have the compute and of course we didn't have all the data that was collected, right? Now, there's a lot of observation data coming in through IOT and many senses and so on. So, what do you do with that? Like, human interpretation is pretty challenged, I would say. So, that's where AI comes in, to augment the intelligence that we have in terms of extracting information. So, geospatial AI, specifically which we focus on, is to try to take location that's embedded with this kind of information and sort of like extract knowledge and information out of them, right? Intelligence out of them. So, that's what we focus on: to compliment location intelligence with AI, which we call geospatial AI. >> So, you can observe how things are changing, maybe report on that and that's got to be a huge thing that we can talk about. So, maybe talk about some of the big trends that are driving your business. What are those? >> Yeah, that's a great question. So, I was listening to Sandy Carter's 'Keynote' yesterday and she really emphasized the importance of data. And, data is crucial to what we do as a technology company, and we curate data globally and we get our data from best of breed sources, and that includes commercial data providers, it includes natural mapping agencies, and also a community maps program where we get data from our customers, from our global network of distributors and partners, and we take that data, we curate it, we host it and we deliver it back. And so, just recently for example, we're really excited 'cause we released the 2020 Global Land Cover. And so, Esri is the first company to release this data at 10 meter resolution for the entire planet, and it's made up of well over 400,000 earth observations from various satellites. So, you know data is a... It's not only a nice-to-have anymore, it's actually a must-have. And so, so is location when we talk about data. They go hand in hand. >> 10 meters so I can look at the hole in the roof of my barn... >> Well... (Dave Cardella chuckling) >> Dave Vellante: Pretty much. >> It depends on what you're trying to do, right? So, I think you know, to talk about it, it's within context. GIS is all about context, right? It's bringing location into context in your decision-making process. It's sort of like the where along with the when, what, how and why. That's what GIS brings in. So, a lot of problems are challenging because we need to bring these things together. It's sort of like you're tearing various layers of data that you have and then bringing them within context. Very often, the context that human minds understand and reflected in the physical world is geographic location, right? So, that's what you bring in. And I would say that there's various kinds of data, also. Various types of data, formats of data: structured data, unstructured data, data captured from extraterrestrial, you know, like, you can say, satellite imagery from drones, from IOT. So, it's like on the ground, above the ground, under the ground. All these sensors are bringing in data, right? So, what GIS does is try of map that data to a place on the earth at very high precision, if you're looking at it locally, or at a certain position if it's regionally, trying to find patterns, trying to understand what's emerging, and then, as you take this and infuse geospatial layer into this, you can even predict what is going to happen based on the past. So, that's sort of like... You could say GIS being used for real world problems, like if you take some examples, COVID... The pandemic is one example. Being able to first discover where it happened, where it's spreading, you know, that's the tracking aspect and then how you respond to that and then how you recover, you know, recovering as humans, as businesses and so on. So, we have widespread use of that. The most popular would be the John Hopkins' Dashboard, >> Dave Vellante: Board, yeah. >> that everyone's seen. >> Vellante: We all use it... >> It's gotten trillions of hits and so on, right? That's one example. Another example is addressing racial equity by using location information. Similarly, social justice. Now, these are all problems that we face today, right? So, GIS is extensively used by our customers to solve such problems. And then of course, you have the climate change challenge itself, right? Where you're hovering all kinds of complex data that we can't comprehend because you have to go back decades and try to bring all that together to compute. So, all of this together comes in the form of a geospatial cloud that we have as an offering. >> So, okay. That's amazing. I mean, you're building a super cloud, we call it. You know, and... So, how do you deal with... How do you work with AWS? What's the relationship there? Where do developers fit in? Maybe you can talk about a little bit. >> Yeah. Yeah, that's a great question. So, we've got two main integration points with AWS. A lot of our location services that we expose data and capabilities through are built on AWS. So, we use storage, we use cloud caching and AWS's various data sets across the world quite heavily. So, that's one integration point. The other is a relatively new product that Amazon has released called Amazon Location Service. And so, what it does is it brings location and spatial intelligence directly into a developer's AWS dashboard. So, the experience that they're already used to, they now get the power of Esri services and location intelligence right at their fingertips. >> So, you're .. We started talking about the edge, your data architecture is very distributed, right? But, of course, you're bringing it back. So, how does that all work? You process it locally and then sending some data back? Are you sending all data back? What does that flow look like? >> I think the key thing is that our customers work with data of all kinds, all formats, all sizes and some are in real-time, some are big data and archive, right? So, most recently, just to illustrate that point, this year, we released RGS Enterprise on Kubernetes. It's the entire geospatial cloud made available for enterprise customers, and that's made available on AWS, on EKS. Now, when it's available on EKS, that means all these capabilities are microservices, so, they can be massively scaled. They're DevOps friendly and you've got the full mapping and analytics system that's made available for this. >> Dave Vellante: Oh. >> And we sort of like built it, you know, cloud native from the ground up and the more important thing that we have now is connectivity with Redshift. Why is that important? Because a lot of our customers have geospatial data in these cloud data warehouses. Redshift is very important for them. And so, you can connect to that, you can discover these massive petabytes of data sets and then you can set up what we call the query layer. It's basically pushing analytics into Redshift and being able to bring out that data for mapping, visualization, for AI workflows and so on. It's pretty amazing and it's pretty exciting at this time. >> And, I mean... So much data. And then... What, do you tear it down into glacier of just to save some cost, or is it going to all stay in S3 or is it... >> So, we already work with S3, we've worked with RDS, we support Amazon Aurora, our customers are very happy with that. So, Redshift is a new offering for us to connect to Redshift. >> Dave Vellante: AOK. >> So, the way the query layer works is all of your observation data is in Redshift, your other kinds of data... Your authoritative data sets could come from various other sources including in Amazon Aurora, for example, okay? And then, you overlay them and use them. Now, the data in Redshift is usually massive, so, when you run the analytic query, we let you cache that as a materialized view or as a snapshot that you can refresh and you can work against that. This is really good because it compliments our ability to actually take that data, to put it on a map image which we render service side, it's got very complex cartographic ready symbology and rendering and everything in there. And you get these beautiful rendering of maps that comes out of Redshift data. >> And you're pushing AI throughout your stack, is that, you know? >> Yeah. AI is just like infused, right? I mean, it's... I would say, human intelligence augmented for data scientists, for everyone, you know. Whether you're using it through notebooks or whether you're using it through applications that we have or the developer APIs themselves. >> So, what are some of the big initiatives you're working on near-term, mid-term? >> Yeah. So, you mentioned what's really driving innovation and it's related to the question that you just asked right now and I really believe developers drive innovation. They're force multipliers in the solutions that they build. And so, that's really the integration point that Esri has with AWS, it's developers. And earlier this year, we released the RGS platform which is our platform as a service offering that exposes these powerful location services that Jay just explained. There's a set of on-demand services that developers can bring in their applications as they want and they can bring in one, they can bring in two or three, whatever they need, but they're there when they need them. And also, developers have their client API of choice. So, we have our own client APIs that we offer but you're not pigeonholed into that when you're working with RGS platform. A developer can bring their own API. >> Okay, so he called the platform as a service. Are you making your data available as well? Your data, your tooling and then selling that as a service? >> Our data has always been available as a service, I would say. >> Okay, yeah. >> Everything that we do, our GIS tools, are accessible as a web service. >> Vellante: Is that new, or... that's always been the way? >> No, that's always been there. That's always been that way. The difference now is everything is built from the ground up to be cloud native. >> Dave Vellante: Okay. >> From the ground up to be connected to every data set that's available on AWS, every compute that can be exploited from small to massive in terms of compute, and also reaching out to bring all the apps and the developer experiences, pushing out to customers. >> So, 50 years ago, you weren't obviously using the cloud, but so, you were running everything on-prem now you're all in the cloud, or you're kind of got a mix? What is the clearer picture of that? >> So, we have two major offerings. There's RGS Online, where obviously it's offered as a service and it's GIS as a service provider for everyone. And that's available everywhere. The other offering we have is actually RGS Enterprise where some customers run them on premises, some run it in the cloud, especially AWS. Many run it on the edge, some in the field and there's connectivity between this. A lot of our customers are hybrid. So, they make the best of both. Depending on the kinds of data- >> Dave Vellante: You give them a choice. >> the kinds of workflows... Giving them the choice, exactly. And I would say, you know, taking Werner's 'Keynote' this morning, he talked about what's the next frontier, right? The next frontier could very well be when AWS gets to space and makes compute available there. It's sitting alongside the data that's captured and we've always, like I said, for 50 years, worked with satellite imagery, >> Dave Vellante: Yeah. >> or worked with IOT, or worked with drone data. It's just getting GIS closer to where the data is. >> So, the ultimate edge space. >> Yes. >> All right, I'll give you guys... Give us a quick wrap if you would. Final thoughts. >> I think its... Go ahead. >> Go, ahead Dave. >> Yeah. I really resonate with data and content. We're a technology company- there's no doubt about that- but without good data, not only supplied by ourselves, but our customers, Jay mentioned it earlier, our customers bring their own data to our platform and that's really what drives the analytics and the accuracy in the answers to the problems that people are trying to solve. >> Bring their first-party data with your data and then one plus one is... >> Yes. Yeah, and the key thing about that (Cardella chuckling) is not some of the data, it's all of the data that you have. You don't more need to be constrained. >> Yeah, you're not sampling. >> Yes, exactly. >> Yeah. >> All right, guys. Thanks so much. Really interesting story. Congratulations. >> Thank you, Dave. >> Dave, thank you. >> Nice meeting you. >> Thank you for watching. This is Dave Vellante for theCUBE, the leader in global tech coverage. We'll be right back. (upbeat music)

(upbeat music) >> Welcome back to Las Vegas everybody. You're watching theCUBE coverage of AWS reinvent 2021. I tell you this place is packed. It's quite amazing here, over 20,000 people, I'd say it's closer to 25, maybe 27,000, and it's whole overflow, lots going on in the evenings. It's quite remarkable and we're really happy to be part of this. Jay Turner is here, he's the Vice President of Development and Operations, at PCCW Global. He's joined by Garrett Lowell, Vice President of Ecosystem Partnerships for the Americas at PCCW Global. Guys, welcome to theCUBE. Thanks for coming on. >> Thank you. >> Thank you so much. Jay, maybe you could take us through, for those people who aren't familiar with your company, what do you guys do, what are you all about? >> PCCW Global is the international operating wing of Hong Kong telecom. If it's outside of Hong Kong, it's our network. We've got about 695,000 kilometers of diverse cable, we've got about 43, 44 terabit of capacity came into business in 2005, if my brain is serving me correctly right now. We have a very diverse and vast portfolio ranging all the way from satellite teleports, all the way to IP transit. We're a Tier 1 service provider from that perspective as well. We do one of everything when it comes to networking and that's really, what was the basis of Console Connect, was inventing a platform to really enable our users to capitalize on our network and our assets. >> Okay. 2005, obviously you predated Cloud, you laid a bunch of fibers struck it in the ocean, I mean, global networks. There was a big trend to do that you had to think, you had to go bigger, go home in that business, (laughing) all right. Console Connect is your platform, is that right? >> Jay: Yes. >> So explain- >> Yeah, sorry, Console Connect is a software defined interconnection platform. We built a user self-service portal. Users can allocate ports, they get the LOAs issued to them directly from the platform. And then once they've got an active port or they've come in via one of our partnerships, they can then provision connectivity across our platform. That may be extending to their data centers or extending to their branch office, or it could be building a circuit into the Cloud via direct connect, could be building a circuit into an internet exchange. All of those circuits are going to be across that 685,000 kilometers of diverse fiber rather than going across the public internet. >> When you started, it took some time obviously to build out that infrastructure and then the Cloud came into play, but it was still early days, but it sounds like you're taking the AWS Cloud model and applying that to your business, eliminate all that undifferentiated heavy lifting, if you will, like the visioning in management. >> Yeah, we've heard many people, and that's kind of the impetus of this was, I want to be directly connected to my end point. And how do I do that? AWS, yes, they had direct connect, but figuring out how to do that as an enterprise was challenging. So we said, hey, we'll automate that for you. Just tell us what region you want to connect to. And we'll do all the heavy lifting and we'll just hand you back a villain tag. You're good to go. So it's a classic case, okay. AWS has direct connect. People will go, oh, that's directly competitive, but it's now you're adding value on top of that. Right? >> Yeah. >> Describe where you fit, Garrett, inside of the AWS ecosystem. You look around this hall and it's just a huge growing ecosystem, where you fit inside of that ecosystem and then your ecosystem. What's that like? >> Where we fit into the AWS ecosystem, as Jay alluded to, we're adding value to our partners and customers where they can come in, not only are they able to access the AWS platform as well as other Cloud platforms, but they're also able to access each other. We have a marketplace in our platform, which allows our customers and partners to put a description of their services on the marketplace and advertise their capabilities out to the rest of the ecosystem of PCCW Global and Console Connect. >> And you're doing that inside of AWS, is that right or at least in part? >> No, that's not inside of AWS. >> So your platform is your platform. >> Yes. >> Your relationship with AWS is to superpower direct connect. Is that right or? >> So we're directly connected to AWS throughout the globe. And this allows our customers and partners to be able to utilize not only the PCCW global network, but also to expand that capability to the AWS platform in Cloud. >> So wherever there's a Cloud, you plug into it, okay? >> Garrett: That's correct. >> Jay: Yeah. And then another advantage, the customer, obviously doesn't have to be directly co-located with AWS. They don't have to be in the same geographical region. If for some reason you need to be connected to U.S. west, but you're in Frankfurt, fine, we'll back all the traffic for you. >> Dave: Does that happen a lot? >> It actually does. >> How come? What's the use case there. >> Global diversity is certainly one of them just being able to have multiple footprints. But the other thing that we're seeing more of late is these Cloud-based companies are beginning to be attracted to where their customers are located. So they'll start seeing these packets of views and they'll go, well, we're going to go into that region as well, stand up a VPC there. We want our customers then being able to directly connect to that asset that's closest to them. And then still be able to back call that traffic if necessary or take it wherever. >> What's the big macro trends in your business? Broadly you see cost per bit coming down, you see data consumption and usage going through the roof. How does that affect you? What are some of the big trends that you see? >> I think one of the biggest ones and one that we targeted with Console Connect, we were hearing a lot of customers going, the world's changing so dynamically. We don't know how to do a one-year forecast of bandwidth, much less a three-year, which is what a lot of contracts are asking us for. So we said, hey, how about one day? Can you do one day? (Dave laughs) Because that's what our granularity is. We allow for anything from one day up to three years right now, and then even within that term, we're dynamic. If something happens, if suddenly some product goes through the roof and you've suddenly got a spike in traffic, if a ship drags its anchor through a sub sea cable, and suddenly you're having to pivot, you just come into the platform, you click a couple of buttons, 20 seconds later, we've modified your bandwidth for you or we've provisioned a new circuit for you, we've got your backup going, whatever. Really at the end of the day, it's the customer paying for their network, so the customer should be the one making those decisions. >> How's that affect pricing? I presume or so, I can have one day to a three-year term, for example if I commit to three years, I get a better deal. Is that right, or? >> You do, but at the end of the day, it's actually pretty much a moderate, a better deal. We don't want to force the hand of the customer. If you signed a 12 month contract with us, we're going to give you a 3% discount. >> So it's not really, that's not a motivation to do it. It's just (indistinct) reduce the transaction complexity. And that's why you will sign up for a longer term not to get the big discount. >> Correct. And then, like I said, even within a longer contract, we're still going to allow you to flex and flow and modify if you need to, because it's your network. >> What kind of constraints do you put on that? Do I have to commit to a flow? And then everything above that is, I can flex up. Is that how it works? >> Yeah. >> Okay. And then, the more I commit to, the better the deal is, or not necessarily? >> No, it's pretty much flat rate. >> Okay, I'm going to commit and I'm going to say, all right, I know I'm going to use X, or sign up for that and anything over it, you're pretty flexible, I might get a few points if I sign up for more, somebody might want to optimize that if they're big enough. >> And another really neat advantage, the other complaint we heard from customers, they go, I need three different direct connect, I need to be connected to three different parties, but I don't want to run three different cross-connects and I don't want to have three different ports. That's just an expense and I don't want. And we, fine, take your one gig port run one gig of services on it. If that's 20 different services, we're fine. We allow you to multiplex your port and provision as- >> So awesome. I love that model. I know some software companies who I would recommend to take a look at that pricing model. So Garrett, how do you segment the ecosystem? How do you look at that? Maybe you could draw and paint a picture of the idea of partners and what they look like. I know there's not just one category, but, >> Sure. Our ideal partners are internet exchangers, Cloud partners and SAS providers, because a big piece of our business is migration to the Cloud, and the flexibility of our platform allows and encourages our SAS providers and SI partners to perform migration to the Cloud much easier in a flexible format for their customers. >> What can you tell us, any kind of metrics you can give us around your business to give a sense of the scope, the scale? >> Well, of our business, (Dave laughs) one of the driving factors here, Gardner says that about 2023, I think, 40% of the enterprise workloads will be deployed in the Cloud, which is all fine and dandy, except in my head, you're just trading one set of complexities for another. Instead of having everything in a glass house and being able to understand that, now you're going, it's in the Cloud, now I need to manage my connectivity there. wait a minute, are my security policies still the same? Do they apply if I'm going across the public internet? What exposure have I just bought into myself to try to run this? The platform really aims at normalizing that as much as possible. If you're directly connected to AWS, at the end of the day, that's a really long ethernet cable. So your a glass house just got a lot bigger, but you're still able to maintain and use the exact same policies and procedures that you've been using. That's really one of our guiding principles, is to reduce that complexity and make it very simple for the user. >> I understand that, cause in the early days of Cloud, a lot of enterprises, the CIOs, they were concerned about security, then I think they realized, ah, AWS has pretty good security. CIA is using it. But still people would say to me, it's not that it's best security, it's just different. You know, we move slow, Dave. How do you accommodate, there's that diversity, I mean, AWS is obviously matured, but are you suggesting that you can take my security edicts in my glass house and bring those into your networks and ultimately into the Cloud? Is that how it works? >> That's the goal. It's not going to be a panacea more than likely, but the more edicts that we can allow you to bring across and not have to go back and revamp and, the better for you as a customer and the better really for us, because it normalizes things, it makes it much easier for us to accommodate more and more users. >> And is it such now in the eco, is all the diversity in the ecosystem, is it such that there's enough common patterns you guys can accommodate most of those use cases? >> Yeah, absolutely. One of the key components is the fact that the platform runs on our MPLS network, which is inherently secure. It's not on the public internet anywhere. We do have internet on demand capability. So in the event that a customer wants access to the internet, no problem. We can accommodate this. And we also have 5G capability built into the platform to allow flexibility of location and flexibility of, I would say, standing up new customer locations. And then the other component of the security is the fact that the customers can bring their own security and apply anywhere. We're not blocking, we don't have any port filters or anything of this nature. >> If would think 5G actually, I could see people arguing both sides, but my sense is 5G is going to be a huge driver for your business cause it's going to just create so much more demand for your services, I think. I can see somebody arguing the counter about it. What's your point of view on that? >> No, I think that's a fair assessment. I think it's going to drive business for everyone here on the show floor and it's pushing those workloads more toward the edge, which is not an area that people were typically concerned with. The edge was just the door that they walked through. That's becoming much different now. We're also going to start seeing, and we're already seeing it, huge trends of moving that data at the edge rather than bringing it all the way back to a central warehouse and help ending it. The ability to have a dynamic platform where you can see exactly what your network's doing and in the push of a button, modify that, or provision new connectivity in response to how your business is performing. >> Yeah, ultimately it's all about the applications that are going to be driving demand for more data. That's just a tailwind for you guys. >> Yeah. You look at, some of the car companies are coming on, Tesla, you're drive around with like eight CPUs and I think communicating back over the air. >> Dave: Yeah, right. >> You start scaling that and you start getting into some some real bottlenecks. >> Amazing business you guys having obviously capital intensive, but once you get in there, you got a big moat. That is a matter of getting on a flywheel and innovating. Guys, congratulations on all the progress and so much for coming on theCUBE. >> Thanks for the time. >> Thank you very much. >> Great to meet you guys. Good luck. All right, thank you for watching. This is Dave Vellante for theCUBE, the leader in High-Tech Coverage. We'll be right back. (upbeat music)

(upbeat music) >> Welcome back to Las Vegas everybody. You are watching theCube's coverage of AWS reinvent 2021. I'll tell you this place is packed. It's quite amazing here over 20,000 people, I'd say it's closer to 25, maybe 27,000. And there's a little overflow, lots going on in the evenings. It's quite remarkable. And we're really happy to be part of this. Jay Turner is here, he's the vice president of development and ops at PCCW Global. He's joined by Garrett Lowell, vice-president of ecosystem partnerships for the Americas at PCCW Global. Guys, welcome to theCube. Thanks for coming on. >> Thank you so much. >> So, Jay, maybe you could take us through for those people who aren't familiar with your company, what do you guys do? What do you all about? >> Yes, so PCCW Global is the international operating wing of Hong Kong Telecom. So if it's outside of Hong Kong, it's our network. We've got about 695,000 kilometers of diverse cable. We've got about 43, 44 terabit of capacity. Came into business in 2005 if my brain is serving me correctly right now. So we have a very diverse and vast portfolio ranging all the way from satellite teleports, all the way to IP transit. We're a tier one service provider from that perspective as well. So we do one of everything when it comes to networking and that's really what was the basis of Console Connect, was inventing a platform to really enable our users to capitalize on that our network and our assets. >> Okay, so 2005, obviously you predated cloud, you laid a bunch of fibers, it's getting in the ocean, I mean, global networks, I mean, there was a big trend to do that and you had to think, you had to go bigger or go home and that business. >> Jay: Yes you had to do. >> So and Console Connect is your platform, is that right? So explain. >> Yeah, sorry. Yeah, Console Connect is our software defined interconnection platform. So we built a user self-service portal. Users can allocate ports, they get the LOAs issue to them directly from the platform. And then once they've got an active port or they've come in via one of our partnerships, they can then provision connectivity across our platform. And that may be extending to their data centers or extending or their branch office, or it could be building a circuit into the cloud via direct connect, could be building a circuit into an internet exchange. And all of those circuits are going to be across that 685,000 kilometers of diverse fiber rather than going across the public internet. >> So, when you started, it took some time obviously to build out that infrastructure and then the cloud came into play, but it was still early days, but it sounds like you're taking the cloud model, AWS Cloud model and applying that to your business, eliminate all that undifferentiated, heavy lifting, if you will, the visioning and management. >> Yeah, we've heard many people and that's kind of the impetus of this was, I want to be directly connected to my end point. And how do I do that? And AWS, yes, they had direct connect, but figuring out how to do that as an enterprise was challenging. So we said, hey, we'll automate that for you. Just tell us what region you want to connect to. And we'll do all the heavy lifting, and we'll just hand you back a villain tag. You're good to go. >> So it's a classic case of, okay, AWS has direct connect, people they go, "Ah, that's directly competitive, but it's not, you're adding value on top of that." Right. So describe where you fit Garrett inside of the AWS ecosystem. You look around this hall and it's just a huge growing ecosystem, where you fit inside of that ecosystem and then your ecosystem, what's that like? >> Okay, so where we fit into the AWS ecosystem, as Jay alluded to, we're adding value to our partners and customers where they can come in, not only are they able to access the AWS platform as well as other cloud platforms, but they're also able to access each other. So we have a marketplace in our platform, which allows our customers and partners to put a description of their services on the marketplace and advertise their capabilities out to the rest of the ecosystem of PCCW Global and Console Connect. >> Okay, so and you're doing that inside of AWS? I that right? Or at least in part? >> No, that's not inside of AWS. >> Okay, so your platform is your platform. >> Yes. >> And then, so your relationship with AWS is to sort of superpower direct connect, is that right or? >> So we're directly connected to AWS throughout the globe. And this allows our customers and partners to be able to utilize not only the PCCW Global network, but also to expand that capability to the AWS platform in clouds. >> Wherever there's a cloud you plug into it? Okay. >> That's correct. >> And then another advantage there is the customer, obviously doesn't have to be directly co-located with AWS. They don't have to be in the same geographic region. If for some reason you need to be connected to US West, but you're in Frankfurt, fine, we'll back all the traffic for you. >> Does that happen a lot? >> It actually does. >> How come? Why, what's the use case there? >> Global diversity is certainly one of them, just being able to have multiple footprints. But the other thing that we're seeing more of late is these cloud-based companies are beginning to kind of be attracted to where their customers are located. So they'll start seeing these pockets of use and they'll go, well, okay, we're going to go into that region as well, stand up a VPC there. And so then we want to our customers then being able to directly connect to that asset, that's closest to them. And then still be able to back call that traffic if necessary or take it wherever. >> What are the big, sort of macro trends in your business? I mean, broadly you see cost per bit coming down, you see data consumption and usage going through the roof. How does that affect you? What are some of the big trends that you see? >> I think one of the biggest ones and one that we targeted with Console Connect, we were hearing a lot of customers going, the world's changing so dynamically. We don't know how to do a one-year forecast of bandwidth, much less a three-year, which is what a lot of contracts are asking us for. So we said, hey, how about one day? Can you do one day? (Dave laughing) Because that's what our granularity is. So we allow for anything from one day up to three years right now, and then even within that term, we're dynamic. So if something happens, suddenly some product goes through the roof and you've suddenly got a spike in traffic. If a ship drags its anchor through a sub sea cable, and suddenly you're having to pivot, you just come into the platform, you click a couple of buttons, 20 seconds later, we've modified your bandwidth for you, or we've provisioned a new circuit for you. We've got your backup going whatever. Really at the end of the day, it's the customer paying for their network, so the customer should be the one making those decisions. >> How's that affect pricing? I presume, so I can have one date or a three-year term. Presume if I commit to three years, I get a better deal, is that right or? >> You do, but I mean, at the end of the day, it's actually pretty much a moderate, a better deal. We don't want to force the hand of the customer. So yeah, if you signed a 12 month contract with us, we're going to give you a 3% discount. >> Yeah, so it's not really, that's not a motivation to do it. Is just you want to reduce the transaction complexity. And that's why you would sign up for a longer term not to get the big discount. >> Correct. And then, like I said, even within a longer contract, we're still going to allow you to flex and flow and modify if you need to because it's your network. >> What kind of constraints do you put on that? Do I have to commit to a floor and then everything above that is I can flex up? Is that how it works? Okay. And then the more I commit to the better the deal is, or not necessarily? >> No, it's pretty much flat, right. >> So, okay. So I'm going to come in and I'm going to say, all right, I know I'm going to use X, I'll sign up for that and anything over it. You're pretty flexible, I might get a few points if I sign up for more, somebody might want to optimize that if they're big enough. >> And another really neat advantage, and the other complaint we heard from customers, they go, I need three different direct connect, or I need to be connected to three different parties, but I don't want to run three different cross-connects and I don't want to have three different ports. That's just an expense I don't want. And we say, fine, take your one gig port, run one gig of services on it, if that's 20 different services, we're fine. So we allow you to multiplex your port and provision- >> It's awesome. I love that model. I know some software companies who I would recommend take a look at that pricing model. So, Garrett, how do you segment the ecosystem? How do you look at that way? Maybe you could draw paint a picture sort of the, the ideal partners and what they look like. I know there's not just one category, but. >> Sure, so our ideal partners are internet exchanges, cloud partners, and SAS providers, because a big piece of our business is migration to the cloud. And the flexibility of our platform allows and encourages our SAS providers and SI partners to perform migration to the cloud much easier and flexible in a flexible format for their customers. >> Yeah, so what can you tell us, any kind of metrics you can give us around your business to give a sense of the the scope, the scale. >> Well, of our business, kind of one of the driving factors here, Gardner says that about 2023, I think 40% of the enterprise workloads will be deployed in the cloud, which is all fine and dandy, except in my head, you're just trading one set of complexities for another. So now, instead of having everything in a glass house and being able to kind of understand that now you're going, well, okay, so it's in the cloud now I need to manage my connectivity there. And, oh, well, wait a minute, are my security policies still the same? Do they apply if I'm going across the public internet? What exposure have I just, bought into myself to try to run this? So the platform really aims at normalizing that as much as possible. If you're directly connected to AWS, at the end of the day, that's a really long ethernet cable. So you're a glass house just got a lot bigger, but you're still able to maintain and use the exact same policies and procedures that you've been using. So that's really one of our guiding principles is to reduce that complexity and make it very simple for the user. >> Well, I don't understand, 'cause in the early days of cloud, a lot of enterprises, CIO they were concerned about security. And I think they realized that AWS has pretty good security, well, CIA is using it. But still people would say to me, it's not that it's bad security, it's just different. We move slow, Dave. So how do you accommodate, now I don't know, does that diversity, I mean, AWS has obviously matured, but are you suggesting that you can take my security edicts in my glass house and bring those into your networks and ultimately into the cloud? Is that kind of how it works? >> That's the goal. It's not going to be a panacea more than likely, but the more edicts that we can allow you to bring across and not have to go back and revamp and the better for you as a customer and the better really for us, because it normalizes things, it makes it much easier for us to accommodate more and more users. >> It is such now in the eco, it was all the diversity in the ecosystem. Is it such that there's enough common patterns that you you guys can kind of accommodate most of those use cases? >> Yeah, absolutely. I think the, one of the key components is the fact that the platform runs on our MPLS network, which is inherently secure. It's not on the public internet anywhere. Now we do have internet on demand capability. So in the event that a customer wants access to the internet, no problem, we can accommodate this. And we also have 5G capability built into the platform to allow flexibility of location and flexibility of... I would say, standing up new customer locations. And then the other component of the security is the fact that the customers can bring their own security and apply anywhere. So we're not blocking, we don't have any port filters or anything of this nature. >> Well, I would think 5G actually, I mean, I could see people arguing both sides, but my sense is 5G is going to be a huge driver for your business, 'cause it's going to just create so much more demand for your services I think, I could see somebody arguing the counter, but what's your point of view on that? >> No. I think that's a fair assessment. I think it's going to drive business for everyone here on the show floor. And it's pushing those workloads more toward the edge, which is not an area that people were typically concerned with. The edge was just the door that they walked through. That's becoming much different now. And we're also going to start seeing, and we're already seeing it, huge trends of moving that data at the edge, rather than bringing it all the way back to a central warehouse in Hare pending it. So, again, the ability to have a dynamic platform where you can see exactly what your network's doing and in the push of a button, modify that, or provision new connectivity in response to how your business is performing. >> Yeah, and ultimately it's all about the applications that are going to be driving demand for more data. And that's just a tailwind for you guys. >> Yeah, yeah and then you look at some of the car companies are coming on, you know, Tesla, you're driving around with like eight CPU's in that thing, communicating back over the air. >> Dave: Yeah right. >> You start scaling that, and you start getting into some real bottleneck. >> Amazing business you guys having, obviously capital intensive, but once you get in there, you've got a big moat, and then it's a matter of getting on a flywheel and innovating. Guys, congratulations on all the progress and thanks so much for coming on theCube. >> Yeah. No, thanks for the time. >> Thank you very much. >> Yeah, great to meet you guys. Good luck. All right. Thank you for watching. This is Dave Vellante for theCube, the leader in high-tech coverage, right back. (upbeat music)

(bright upbeat music) >> Welcome to theCUBE's, continuous coverage of AWS re:Invent 2021. We're here live running one of the most important and largest technology events of the year. It's all about AWS and AWS's ecosystem partners. We are joined by Jay Mozo, Director of Transformation Services, TEKsystems Global Services, alumni of AWS, >> Yep. >> David: I got that, right? >> Yep. >> David: And Ted Swinyar, you're Director of Solutions 1Strategy. Who's going to tell me what the relationship is between 1Strategy and TEKsystems? Like I don't already know what it is since you came and essentially announced the magic, here on our stage in 2019. Ted, you want to start off with a little background since you were acquired. >> Ted: Yeah, I'll jump in. >> How did that go? >> So 1Strategy is a TEKsystems Global Services Company, and we're an AWS premier partner. We've got competencies and DevOps, migration, data and analytics, machine learning. And we're really excited this year to be focusing also on the security competency as well. >> So you've been laser focused on AWS forever? >> Ted: Day one. >> Day one. >> Ted: You know that's been our core focus, and together with TEKsystems Global Services, we're able to bring that dedicated and specialized focus on cloud transformation now at scale. And that's really exciting. >> So TEKsystems, you do it all? >> Yep. >> AWS laser-focused, sounds like a great combination. >> Ted And Jay: Yeah. >> And our focus is you know, how we bring that deep AWS specialized expertise together with proven methodologies, the proprietary deployment strategies to take the customer to the next step on their cloud journey. Whether they're just getting started, whether they're in a migration or whether they're already a veteran at AWS looking to take the next step. >> So Jay talk about the last two years. >> Jay: Yeah. >> You've been in this two years obviously very interesting times we've been living through. How has the combination gone? >> Oh it's been great again that expertise, that deep AWS expertise, that's what our customers (indistinct), they would expect from us, right? And we truly are passionate about accelerating business transformation for our customers, right? And our goal is really simple, we bring in real-world expertise, just like an AWS expertise that 1Strategy brought and we solve complex problems whether they're business, technology, or even just people talent, right? The whole talent around this whole ecosystem, we heard Adam talk about it even earlier today, right? Talent is a challenge. So we're very obsessed with technology, right? But we're even more than that we're obsessed with our customers, right? We're at 80% of the fortune 500, more than 6,000 customers, and that obviously grew with our 1Strategy partners here. And we really consider ourselves with 1Strategy as all in one kind of full stack integration partner, right? Well we meet our customers where they are and we work side by side with them to transform their business, again very passionate about that. >> So what do these engagements look like? Are you approaching the customer from an AWS perspective in partnership with AWS? So AWS services, AWS technology, bridging that divide specifically, or are you coming in from sort of a TEKsystems overall perspective and then identifying the areas where AWS is a fit and bringing in 1Strategy? Or is it a mixture of both? What does that look like? >> It's a mixture of both for sure. We do a lot of partnering with AWS, right? Especially with 1Strategy. And we come to the table a lot with AWS together and we have that kind of joint feeling with AWS. And when AWS isn't at the table in the beginning, if it makes sense to go on the AWS platform, we bring them to the table. But it's really around focusing on what you're bringing up, it's focusing on the customer and what they need. And again, we have our kind of business modernization framework that we lean on, that really drives that conversation, so we can figure out very quickly, you know, how to help them and which platform is going to help them. And obviously, you know, AWS more and more, right? They're coming out with all these services, even a higher level services. And the conversations with our customers are really along those lines, right? How do we kind of help them leverage these services, right? So they can really achieve the agility that they need. >> So in the last two years, aside from the pandemic, global economy, what are some of the things in cloud that maybe you didn't anticipate? Now you're coming in from a specialist perspective, Laser focused on AWS, more the generalist, let's take care of anything the customer might need. Are there areas where you are surprised by the pace or a lack of pace in terms of movement to cloud? What have the last two years looked like from that perspective? >> Well I'll say one of the big things has been the change in data. The data is a lifeblood of every organization and what looks like normal data today, would be alien for some businesses going back two years ago. And as the entire world has gone through a business transformation, there's been just more and more data coming at customers faster and faster, the acceleration there has been just tremendous. And one of the things we see, customers are just drowning in data, you know how they're able to leverage AWS from a technology standpoint to build a data strategy, has to be married with that data-driven culture. And we're seeing more and more customers really getting that. I thought Adam made an incredible point this morning, he called out 85% of the workers surveyed, in the past couple of years are saying, I need to understand technology more. And that's absolutely something we're seeing in the marketplace. That investment in your team, enablement training as well as having the solid foundation and an ability to move toward an agile approach is becoming more and more critical for our customers. >> So you mentioned Adam's keynote, one of the things that was called out, was the idea that there are 475 different kinds of instances available from AWS. So let's get tactical for a minute, pretend like I'm a CEO at a customer site. I know that I want to be in the cloud, I know I want to leverage what the cloud has to offer. How do you guys figure out which ones of these 475 instances I'm going to be leveraging? Do you have like multisided dungeons and dragons dice that you throw, (murmuring) or is there some science behind it? >> Oh man that and the dart board definitely the way to go. No, the idea for every engagement is always focused on what the outcome for the customer is at the end of the day and work backwards from that. So depending on whether they're focused on an ML workload, or whether they're focused on a more, business line application, working backwards to understand what is the outcome they're trying to drive and then building the right technology stack, working backwards to support that. Whether it's taking advantage of any number of the instance types, taking advantage of serverless or any of the really incredible container options that are available in the marketplace today. >> So we're obviously here at AWS re:Invent, 1Strategy is an AWS specialist, TEKsystems multicloud? >> Jay: Yep. >> Fair to say? >> Jay: Yep. >> The world is a multicloud place, I think it's okay to acknowledge that. So if I'm looking to engage with TEKsystems, I can count on AWS being brought in and AWS expertise being brought in when it's appropriate, because it's not the only thing you do? >> Jay: Right, that's right. >> How do you manage that? Who decides whether a workload is better suited for AWS and the 1Strategy folks versus say GCP or Azure? >> Yeah, definitely again, (indistinct) right on it, right? We start with what the customer needs and their outcomes, right. We take an approach around really helping them understand their value stream, right? So if we get our customers to understand their value stream, that really serves as a context, as I mentioned before for business and delivery agility, right? And when we focus there and work backwards from there, we can really figure out all the different pieces. And like you said, it's a multicloud world now, right? For with many of our customers demand their value streams and some of their value stream components or systems or processes, they might live on different things. But, we don't jump to those right out of the gate, right? We jump to understanding where they are in their journey, where they're at with their value stream. We do a lot of dive deep and aligned to really understand where they're at. And then we craft those things actually in partnership with our customer, right? Because they might have things going on in their organization that might lean towards, GCP for some things and AWS for some other things. So we take all of that in as we start to figure out, which platform really is best for them. But again, like Ted mentioned, we with that working backwards mentality. >> So how do you see the change that's happened over time, in I would call it the AWS posture or attitude towards the concept of hybrid cloud technology? I think there was a time when AWS would have said, you know what everything that matters, everything that's born now will be born in the cloud, all net new things will be in the cloud. All the legacy stuff, we'll just sort of let it wither on the vine. It was mentioned in the keynote today that maybe five to 15% of I.T spend is in the cloud today, that's 85% or so leftover. Do you find yourself working in more of an increasingly hybrid environment these days? What's your perspective on hybridity? I think I may have just made that word up. (chuckles) >> Yeah it's absolutely the reality, and it reflects where every customer is in their cloud journey. You know you've got some customers that are just born in the cloud startups, getting you know everything Greenfield, brand new in the cloud. Whereas you've got others, one of our customers just celebrated recently their hundredth birthday. Obviously they have a significant legacy domain and we always need to focus on meeting a customers where they're at. There's no exact match between customer and customer, it's all about understanding where they are, how we can help them get to the next step, whether that's taking advantage of something like outpost, you know the really cool 5G, the private 5G that was announced this morning. Really exciting. >> David: Very interesting. >> Ted And Jay: Yeah. >> We were talking about that beforehand, how that might support industry 4.0 and some of the really interesting opportunities in that regard. Wavelength, another great example, the reality is AWS has gone into the data center now with things like outposts. It's even gone into space with things like ground station, so it's everywhere that our customers are. >> You mentioned 5G from a TEKsystems perspective, what do you do? Do you spin up a 5G practice? Do you scour universities for 5G graduates? How do you keep up with the pace of developments that are coming from AWS let alone the rest of the tech sector? >> Yeah, and again that 5G is a good example, right? And we're going to kind of follow again where our customer are and where the trends going. But we instantly see with these higher level services, where some of these used cases, some of these solutions are going to go, right? We were even talking again that conversation about, the things we can do from an industry perspective, right? And really align all of these technologies to again be very innovative, right? Adam talked about pathfinders and again, we're going to seek out those pathfinders. And now with all of these services coming out of AWS, we're going to be able to do some incredible things in the future with them. >> Yeah it's amazing to see the things that have been unlocked and unshackled by advances in technology. Were there any things that surprised you Ted, coming out of the keynote today, announcements, some of these things are sort of telegraphed in advance. But hardware advances, we talked about 5G, anything that kind of took you off guard a bit or... >> I was really excited by all the move to serverless analytics, Redshift server lists, EMR with serverless MSK serverless, democratization of data. Again coming back to the pathfinders theme, going all the way back to the very beginning, how we can bring that data forward and lowering those bars. Whether you're focused on ML with the SageMaker announcements, and SageMaker canvas, being able to bring all these people together and empower them with data. I see that as again, a lifeblood of every organization and the more that you can bring that out and make it available, the more powerful and the more flexible every company is going to be. >> When you're an AWS services partner, it's a bit like being at a buffet, an endless buffet where new treats are piled on the table each year. I thought it was amazing that one of the important points had to do with the development of Silicon. There are a lot of folks who would say that the underlying hardware no longer matters, nobody cares. AWS realizes that as a foundation it is really important, it's up to folks like you to translate that technical value into business value obviously. If this whole tech thing doesn't work out for us, what if we opened a nightclub here in Vegas and we called it hybridity? >> (Jay laughing) I like >> Love it. >> I like the sound of it, I'm going to look it up and see if it's actually a word. >> Lets patent it. (murmuring) >> We got it all three of us. So anytime organizations come together, there are cultural issues. So you've got AWS specialist, more of a generalist organization and you're going out and you're engaging customers that are having their own cultural issues. What are some of the bigger obstacles that are in the way of leveraging technology? 'Cause you've mentioned it's all about the customer perspective it's not just the technology. What are the things that are still getting in the way now that might surprise people who think that everyone's already in cloud? >> Yeah, I can go first, Ted you can jump in. Yeah culture is, again, it's a big thing, that's why it's built into our business modernization program, culture, continuous learning and Adam mentioned that too. We see challenges obviously from a learning perspective. We really, really need to key in on, not just the technologies they have to learn, but also modern practices, right? And that's going to be a big part of all these things. And definitely these higher level services are going to abstract a lot of those issues for our customers which is great. But it's still not going to displace just the constant you brought up, the constant change and all these services that come out. So I think we focus on a culture and really understanding how to move an organization to the right mindsets and the right practices, right? And that's really the key in terms of their overall business transformation. >> So I think the headline for this segment is going to be awesome two years for TEKsystems and 1Strategy. Jay and Ted, thank you so much for being here on theCUBE with us. I hope you have a great rest of the week here in Las Vegas, it's amazing to be here in person, fantastic. They've done a really good job of keeping us all safe with the protocols in place. Hope to see you again, I guess we'll be shooting for a 2022 update to see how you guys are doing. With that I'd like to thank all of you for joining us on theCUBE here at AWS re:Invent 2021. I'm Dave Nicholson and again thanks for joining us on theCUBE. We are the leader in hybrid technology event coverage. (bright music)

>>from around the globe. It's the Cube with digital coverage of AWS reinvent 2020 sponsored by Intel, AWS and our community partners. >>Hello and welcome to the Cube virtual here with coverage of aws reinvent 2020. I'm your host, Justin Warren. And today I'm joined by J. Snyder, who is the chief chief customer officer at New Relic J. Welcome to the Cube. >>It is fantastic. Me back with the Cube. One of my favorite things to do has been for years. So I appreciate you having me. >>Yes, a bit of a cube veteran. Been on many times. So it's great to have you with us here again. Eso you've got some news about new relic and and Amazon away W s strategic collaboration agreement. I believe so. Maybe tell us a bit more about what that actually is and what it means. >>Yes. So we've been partners with AWS for years, but most recently in the last two weeks, we've just announced a five year strategic partnership that really expands on the relationship that we already had. We had a number of integrations and competencies already in place, but this is a big deal to us. and and we believe a big deal. Teoh A W s Aziz Well, so really takes all the work we've done to what I'll call the next level. It's joint technology development where were initially gonna be embedding new relic one right into the AWS management console for ease of use and really agility for anyone who's developing and implementing Ah cloud strategy, uh, big news as well from an adoption relative to purchase power so you can purchase straight through the AWS marketplace and leverage your existing AWS spend. And then we're gonna really be able to tap into the AWS premier partner ecosystem. So we get more skills, more scale as we look to drive consulting and skills development in any implementation for faster value realization and overall success in the cloud. So that's the high level. Happy to get into a more detailed level if you're interested around what I think it means to companies but just setting the stage, we're really excited about it as a company. In fact, I just left a call with a W S to join this call as we start to build out the execution plan for the next five years look like >>fantastic. So for those who might be new to new relic and aren't particularly across the sort of field of observe ability, could you just give us a quick overview of what new relic does? And and then maybe talk about what the strategic partnership means for for the nature of new relics business? >>Yes, so when I think about observe ability and what it means to us as opposed to the market at large, I would say our vision around observe ability is around one word, and that word is simplification. So, you know, I talked to a lot of customers. That's what I do all the time. And every time I do, I would say that there's three themes that come up over and over. It's the need to deliver a customer experience with improved up time and ever improving importance. It's the need to move more quickly to public cloud to embrace the scale and efficiency public cloud services have to offer. And then it's the need to improve the efficiency and speed of their own engineering teams so they can deliver innovation through software more quickly. And if you think about all those challenges And what observe ability is it's the one common thread that cuts across all those right. It's taking all of the operational data that your system admits it helps you measure improve the customer, experience your ability to move to public cloud and compare that experience before you start to after you get there. The effectiveness of your team before you deploy toe after you get there. And it's all the processes around that right, it helps you be almost able to be there before your there there. I mean, if that makes sense right, you'll be able to troubleshoot before the event actually happens or occurs. So our vision for this is like I talked about earlier is all about simply simplification. And we've broken this down into literally three piece parts, right? Three products. That's all we are. The first is about having a much data as you possibly can. I talked about admitting that transactional telemetry data, so we've created a telemetry data platform which rides on the world's most powerful database, and we believe that if we can take all of that data, all that infrastructure and application data and bring it into that database, including open source data and allow you to query it, analyze it and take action against it. Um, that's incredibly powerful, but that's only part one. Further, we have a really strong point of view that anybody who has the ability to break production should have the ability to fix production. And for us, that's giving them full stack observe ability. So it's the ability to action against all of that data that sits in the data platform. And then finally, we believe that you need to have applied intelligence because there's so many things that are happening in these complex environments. You wanna be able to cut through the noise and reduce it to find those insights and take action in a way that leverages machine learning. And that, for us, is a i ops. So really for us. Observe ability. When I talked about simplification, we've simplified what is a pretty large market with a whole bunch of products, just down to three simple things. A data platform, the ability to operationalize in action against that data and then layer on top in the third layer, that cake machine learning so it could be smarter than you can be so it sees problems before they occur. And that And that's what that's what I would say observe, ability is to us, and it's the ability to do that horizontally and vertically across your entire infrastructure in your entire stack. I hope that makes sense. >>Yeah, there's a lot of dig into there, So let's let's start with some of that operational side of things because I've long been a big believer in the idea of cloud is being a state of mind rather than a particular location on. A lot of people have been embracing Cloud Way Know that for we're about 10 or so years. And the and the size of reinvent is proven out how popular cloud could be. Eso some of those operational aspects that you were talking about there about the ability to react are particularly like that. You you were saying that anyone who could break production should be able to fix production. That's a very different way of working than what many organizations would be used to. So how is new relic helping customers to understand what they need to change about how they operate their business as they adopt some of these methods. >>Well, it's a great question. There's a couple of things we do. So we have an observe ability, maturity framework by which we employ deploy and that, and I don't want to bore the audience here. But needless to say, it's been built over the last year, year and a half by using hundreds of customers as a test case to determine effectively that there is a process that most companies go through to get to benefits realization. And we break those benefit categories into two different areas, one around operational efficiency and agility. The other is around innovation and digital experience. So you were talking about operational efficiency, and in there we have effectively three or four different ways and what I call boxes on how we would double, click and triple click into a set of actions that would lead you to an operational outcome. So we have learned over time and apply to methodology and approach to measure that. So depending on what you're trying to do, whether it's meantime to recover or meantime, to detect, or if you've got hundreds of developers and you're finding that they're ineffective or inefficient and you want to figure out how to deploy those resource is to different parts of the environment so you can get them to better use their time. It all depends on what your business outcome and business objective is. We have a way to measure that current state your effectiveness ply rigor to it and the design a process by using new relic one to fill in those gaps. And it can take on the burden of a lot of those people. E hate to say it because I'm not looking to replace any individual. It's really about freeing up their time to allow them to go do something in a more effective and more effective, efficient manner. So I don't know if that's answering the question perfectly, but >>e don't think there is a perfect answer to its. Every customer is a bit different. >>S So this is exactly why we developed the methodology because every customer is a little different. The rationale, though, is yeah, So the rationale there's a lot of common I was gonna say there's a lot of common themes, So what we've been able to develop over time with this framework is that we've built a catalog of use cases and experiences that we can apply against you. So depending on what your business objectives are and what you're trying to achieve, were able to determine and really auger in there and assess you. What is your maturity level of being able to deliver against these? Are you even using the platform to the level of maturity that would allow you to gain this benefit realization? And that's where we're adding a massive amount of value. And we see that every single day with our customers who are actually quite surprised by the power of the platform. I mean, if you think traditionally back not too far, two or even three years. People thought of new relic as an a P M. Company. And I think with the launch this summer, this past July with new relic one, we've really pivoted to a platform company. So while a lot of companies love new relic for a PM, they're now starting to see the power of the platform and what we can do for them by operationally operationalize ing. Those use cases around agility and effectiveness to drive cost and make people b'more useful and purposeful with their time so they can create better software. >>Yeah, I think that's something that people are realizing a lot more lately than they were previously. I think that there was a lot of TC analysis that was done on a replacement of FTE basis, but I think many organizations have realized that well, actually, that doesn't mean that those people go away. They get re tasked to do new things. So any of these efficiency, you start with efficiency. And it turns out actually being about business agility about doing new things with the same sort with the same people that you have who now don't have to do some of these more manual and fairly boring tasks. >>Yeah, just e Justin. If this if this cube interview thing doesn't work out for you were hiring some value engineers Right now it sounds like you've got the talk track down perfectly, because that's exactly what we're seeing in the market place. So I agree. >>So give us some examples, if you can, of maybe one or two off things that you've seen that customers have have used new relic where they've stripped out some of that make work or the things that they don't really need to be doing. And then they're turning that into new agility and have created something new, something more individual. Have you got an example you could share with us? >>You know, it's it's funny way were just I just finished doing our global customer advisory boards, which is, you know, rough and tough about 100 customers around the world. So we break it into the three theaters, and we just we were just talking with a particular customer. I don't want to give their name, but the session was called way broke the sessions into two different buckets, and I think every customer buys products like New Relic for two reasons. One is to either help them save money or to help them make money. So we actually split the sessions into those two areas and e think you're talking about how do we help them? How do we help them save money? And this particular company that was in the media industry talked at great length about the fact that they are a massive news conglomerate. They have a whole bunch of individual business units. They were decentralized and non standardized as it related to understanding how their software was getting created, how they were defining and, um, determining meantime to recover performance metrics. All these things were happening around them in a highly complex environment, just like we see with a lot of our customers, right? The complexity of the environments today are really driving the need for observe ability. So one of the things we did with them is we came in and we apply the same type of approach that we just discussed. We did a maturity assessment for them, and we find a found a variety of areas where they were very immature and using capabilities that existed within the platform. So we're able to light up a variety of things around. Insights were able to take more data in from a logging perspective. And again, I'm probably getting a little bit into the weeds for this particular session. But needless to say, way looked at the full gamut of metrics, events, logs and traces which was wasn't really being done in observe, ability, strategy, manner, and deploy that across the entire enterprise so created a standard platform for all the data in this particular environment. Across 5th, 14 different business units and as a byproduct, they were able to do a variety of things. One, the up time for a lot of their customer facing media applications improved greatly. We actually started to pivot from actually driving cost to showing how they could quote unquote make money, because the digital experience they were creating for a lot of their customers reduced the time to glass, if you will, for clicking the button and how quickly they could see the next page, the next page or whatever online app they were looking to get dramatically. So as a byproduct of this, they were about the repurpose to the point you made Justin. Dozens of resource is off of what was traditionally maintenance mode and fighting fires in a reactive capability towards building new code and driving new innovation in the marketplace. And they gave a couple of examples of new applications that they were able to bring to market without actually having to hire any net New resource is so again, I don't want to give away the name, the company, it maybe it was a little too high level, but it actually plays perfectly into exactly what what you're describing, Um, >>that is a good example of one of those that one of the it's always nice to have a specific concrete customer doing one of these kinds of things that you you describe in generic terms. Okay. No, this is this is being applied very specifically to one customer. So we're seeing those sorts of things more and more. >>Yeah, and I was gonna give you, you know, I thought about in advance of this session. You know, what is a really good example of what's happening in the world around us today? And I thought of particular company that we just recently worked with, which is check. I don't know if you're familiar with keg, if you've heard of them. But their education technology company based in California and they do digital and physical textbook rentals. They do online tutoring an online customer services. So, Justin, if you're like me or the rest of the world and you have kids who are learning at home right now, think about the amount of pressure and strain that's now being put on this poor company Check to keep their platform operational 24 77 days a week. So that students can learn at pace and keep up right. And it's an unbelievable success story for us and one that I love, because it touches me personally because I have three kids all doing online, learning in a variety of different manners right now. And, you know, we talked about it earlier. The complexity of some of the environments today, this is a company that you would never gas, but they run 500 micro services and highly complex, uh, technical architectural right. So we had to come in and help these folks, and we're able to produce their meantime to recover because they were having a lot of issues with their ability to provide a seamless performance experience. Because you could imagine the volume of folks hitting them these days on. Reduce that meantime to recover by five X. So it's just another example we're able to say, you know, it's a real world example. Were you able to actually reduce the time to recover, to provide a better experience and whether or not you want to say that saving money or making money? What I know for sure is is giving an incredible experience so that folks in the next generation of great minds aren't focused on learning instead of waiting to learn right, So very cool. >>That is very cool. And yes, and I have gone through the whole teaching kids >>about on >>which is, uh, which it was. It was disruptive, not necessarily in a good way, but we all we adapted and learned how to do it in a new way, which is, uh, it was a lot easier towards the end than it was at the beginning. >>I'd say we're still getting there at the Snyder household. Justin, we're still getting >>was practice makes perfect eso for organizations like check that who might be looking at JAG and thinking that that sounds like a bit of a success story. I want to learn more about how new relic might be able to help me. How should they start? >>Well, there's a lot of ways they can start. I mean, one of the most exciting things about our launch in July was that we have a new free tier. So for anybody who's interested in understanding the power of observe ability, you could go right to our website and you can sign up for free and you can start to play with new relic one. I think once you start playing for, we're gonna find the same thing that happens to most of the folks to do that. They're gonna play more and more and more, and they're gonna start Thio really embrace the power. And there's an incredible new relic university that has fantastic training online. So as you start to dabble in that free tier, start to see with the power and the potential is you'll probably sign up for some classes. Next thing you know, you're often running, so that is one of the easiest ways to get exposed to it. So certainly check us out at our website and you can find out all about that free tier. And what observe ability could potentially mean to you or your business. >>And as part of the AWS reinvent experience, are they able to engage with you in some way? >>It could definitely come by our booth, check us out, virtually see what we have to say. We'd love to talk to them, and we'd be happy to talk to you about all the powerful things we're doing with A. W. S. in the marketplace to help meet you wherever you are in your cloud journey, whether it's pre migration during migration, post migration or even optimization. We've got some incredible statistics on how we can help you maximize and leverage your investment in AWS. And we're really excited to be a strategic partner with them. And, you know, it's funny. It's, uh, for me to see how observe ability this platform can really touch every single facet of that cloud migration journey. And, you know, I was thinking originally, as I got exposed to this, it would be really useful for identity Met entity relationship management at the pre migration phase and then possibly at the post migration flays is you try to baseline and measure results. But what I've come to learn through our own process, of moving our own business to the AWS cloud, that there's tremendous value everywhere along that journey. That's incredibly exciting. So not only are we a great partner, but I'm excited that we will be what I call first and best customer of AWS ourselves new relic as we make our own journey to the cloud >>or fantastic and I'm I encourage any customers who might be interested in new relic Thio definitely gone and check you out as part of the show. Thank you. J. J. Snyder from New Relic. You've been watching the Cube virtual and our coverage of AWS reinvent 2020. Make sure that you check out all the rest of the cube coverage of AWS reinvent on your desktop laptop your phone wherever you are. I've been your host, Justin Warren, and I look forward to seeing you again soon.

>> Hi everybody, this is Dave Velante and on May 27th we're hosting a crowd chat brought to you by IBM. The focus of the crowd chat is on data ops. Go to crowdchat.net/dataops and you're going to learn about what real practitioners are doing not only to get started in data ops, but how they've succeeded. Jay Linbern is here. Jay, how you doing, thanks a lot. Tell us what you're seeing in terms of how clients are getting started. This is a complicated situation for a lot of people. Where should they start? >> Yeah, you're right, it really is a complicated situation. And if you look at the broad landscape of everything that encapsulates data ops it can be difficult to understand where to get started. In IBM we provide a data ops methodology which really helps clients break this down and understand each step of the process that they need to go through to provide clarity on where they can get initial value very, very quickly and where to get started. A lot of the clients I'm working with typically, that's been focusing on the data cataloging and the data governance base. Whereby if clients can get a view of all of their data and understanding where their data lives, who owns that data, what purpose it can be used for, then once they've got that picture and they've delivered value from that initial piece, it's then really easy to phase the pieces that come off of that. >> So check out the crowd chat on May 27th. crowdchat.com/dataops. It's not a bunch of marketing gobbledy gook. You're going to hear from real practitioners. I'll be there, hope you are too.

>> Hi, I'm Jay Limburn, Director of Offering Management from IBM DataOps. As an organization, we've been focusing on simplifying the data and AI life cycle, allowing you to discover and prepare data, and then use that data to build, deploy, govern, and manage your models for the range of capabilities that take advantage of machine and human intelligence. DataOps is a critical and complementary discipline to AI. The methodology enables agile data collaboration, driving speed and scale of operation, (audio distorts) throughout the data and AI life cycle. Learn more on May 27th when IBM and client leaders come together during the DataOps CrowdChat event online. I hope to see you then.

>>Hi. I'm Jalen Burn, director of offering management, IBM Data Ops. As an organization, we've been focusing on simplifying the data, and they are lifecycle allowing you to discover and prepare data and then use that data the build, deploy, govern and manage your models with a range of capabilities that take advantage of machine and human intelligence. Data Ops is a critical and complementary Dissident II. The methodology enables agile data collaboration, driving speed and scale of operations and throughout the data lifecycle learn more on May 27 when IBM and client leaders come together during the data Ops Crowdchat event online. I hope to see you then.

hi brother this is Dave Valentina May 27th we're hosting a crowd chat brought to you by IBM the focus of the crowd chat is on data ops go to crouch at NAT slash data ops and you're gonna learn about what real practitioners are doing not only to get started in data ops but how they've succeeded jaelyn Byrne is here Jay hey how you doin thanks a lot tell us what you're seeing in terms of how clients are getting started is a complicated situation for a lot of people where should they start yeah you're right it really is a complicated situation and if you look at the broad landscape of everything that encapsulates data ops it can be difficult to understand where they get started in IBM we provide a data table methodology which really helps clients break this down and understand each step of the process then they need to go through to provide clarity on where they can get an extra value very very quickly and whether get started a lot of clients I'm working with typically that's been focusing on the data cataloging and the data governance space whereby if clients can get a view of all of their data and understanding where the data lives who owns that data what a purpose it can be useful then once they've got that picture and they delivered value from that initial piece it's really really easy to phase the pieces that come up so check out the crowd shadow May 27th crowd chatting ed /data ops it's not a bunch of marketing gobbledygook you're gonna hear from real practitioners I'll be there hope you are too

(upbeat music) >> Narrator: From our studios in the heart of Silicon Valley, Palo Alto, California, this is a CUBE conversation. >> Hello and welcome to theCUBE studios in Palo Alto, California for another CUBE conversation, where we go in-depth with thought leaders driving innovation across the tech industry. I'm today's host, Peter Burris. Every business is talking about cloud transformation as a consequence of their effort to do a better job with digital business transformation. But cloud transformation too often is associated with just thinking about moving applications and data to some as yet undefined location. Whatever approach enterprises take, they will absolutely have to touch upon a couple of crucial steps along the way. At the center of those steps will be how do we think about the network transformation that's going to be required to achieve and attain our cloud objectives? How do we do it? Well to have that conversation, we're here today with Jay Chaudhry who's a CEO of Zscaler. Jay, welcome to theCUBE, welcome back to theCUBE. >> Thank you. >> So before we get into this very important conversation, give us an update on Zscaler. >> So Zscaler was designed as a cloud security platform for the world of cloud and mobility. When applications are in the cloud, users are everywhere, the traditional security that builds a castle and moat model no longer works. So I start with clean slate, 11 years ago to start this company. Today, some of the largest companies in the world are protected by Zscaler. We went public last year, on NASDAQ, the sales have done very well, our customers are very happy our employees are very happy, so we are having fun building this lasting company and making cloud and internet a safe place to do business. >> Now that's great. Now let's talk about that, 'cause you're talking to a lot of customers, about making the internet a safe place to do business. >> Yep. >> What are you encountering as you discuss their challenges? >> So with the mobility, with the desire to do digital transformation, CIOs and CTOs and CISOs, are trying to figure out, how do I get there? The biggest thing that's holding them back, is security. It's a new thing for them. If my data is sitting in the cloud somewhere, who is protecting it? How do my users access it while the bad guys don't? So security ends up being at the center of the whole discussion. In fact a few years ago, CISOs would talk to me and say, "Security is not getting enough attention, "it's being ignored." Now the same CISOs are complaining a little bit that I'm being asked to present to the board every quarter. >> Right >> So it's a good thing but the CISOs have a challenge of figuring out what solutions work for the cloud, what do not, because quite often, when the market changes, the incumbents, the legacy vendors, kind of whitewash the solutions overnight and everyone becomes a cloud security provider. >> We get a lot of marketing responses, I think one of the centerpieces of this whole thing is, digital business really places an emphasis on the value of data as an asset. >> Yep. >> And how it changes the way you engage your customers, how it changes the way they think about operations, how it impacts the way you govern the overall business. >> Yep. >> When data emerges as the asset, we move away from a focus especially in the security world, from securing devices to securing the new classes of data. >> Yep. >> Is that kind of solution direction that you're seeing companies taking, is how do I think about up leveling beyond perimeter to actually building security. >> Yeah. >> Embedded deep within my workings? >> To really understand how security came about. Earlier on it used to be, I protect my device with antivirus software, then we built networks and we expected users to be on the network and applications and data to be sitting in my data center on my network. So the easiest way to secure your enterprise was, to secure the network. >> Mm. By building a moat around your data center. That's why we call it network security, securing your network, it made sense for years but now, with applications sitting in Azure or AWS Office 365, Workday, the like. And the users being everywhere, at airport, coffee shops, at home and wherever. How do you protect the network? The users aren't even on your network and applications aren't even on your network. So the notion of network security is becoming irrelevant. At the end of the day, the sole purpose of IT is, that a user should be able to access an application, no matter where the application is and no matter where the user is. So all this network and security and all, are a byproduct of that. So when I start Zscaler, I said, what needs to be protected? Data. Where is data? Data is generally sitting with the application, behind the application. So rather than building this moat, rather than doing this network security, rather than trying to build an appliance and try to move it to the cloud, let's take a look at it totally different. Assume that we need a policy engine, a business policy engine that sits in, 100s of locations around the globe, a user connects to the policy engine, the policy engine looks and says, should this user have access to this application or not? Based on that, we connect a user to an application, internal or external, no matter where the user is coming from. So that's the approach that's needed and that's the approach Zscaler pioneered and that's why the biggest of the big companies from GE, to Siemens, to DHL, they all are becoming Zscaler customers. So we are helping them transform from this old world where network is a hub-and-spoke network, security is this castle and moat to the new world, where a user can go directly to the application over any network. And network is important, it's an important transport but it doesn't need to be secure. Security is about, securing the right user to a right application, irrespective of the location of the user or the application. >> So I want to build on this because, what a lot of companies are starting to recognize is that, they want to get their application and the services provided by the application and the data proximate to the commercial activity that generates, you know, that pays the rent so to speak. >> Yep, yep. >> And that means, an increase in distribution of function offer. >> Of course. >> So the notion of the cloud as a place where we're going to centralize things, is giving way to a notion of the cloud as a technique for further distributing. >> Yes. >> And that means ultimately that, the services that we're going to provide have to have security embedded in them, in policy so that the data, the security and all those services are moving to where they're required. >> Yes, so in my view, cloud was never meant to say, things must be centralized. Actually a data centers were highly centralized. >> Right. >> The cloud notion should be, it's a responsibility of the cloud provider to make sure that data and application can be pushed where there needs to be. So when Microsoft is offering Office 365, your emails aren't sitting at one place, it's Microsoft's job to make sure if your employees are in Singapore, some of these things move to Singapore so you can have faster access to it. So that's the application side or for the data side of it. A company like Zscaler, we sit between the user and the application as a check post. In fact, think of us as an international airport. >> mm >> When you go in and out, you need to make sure that, the person is authorized to do so and isn't carrying any guns and weapons that could cause damage to somebody out there. So a user going to Salesforce or user going to Office 365 or a user going to application Azure, they simply connect with us, the business defines a policy, says, this person is okay to go here and based on then, we are connecting those people securely. Now if you're in London, you want to go through Zscaler's check post in London, if you're in Tokyo, you want to go through a check post in Tokyo because you want the shortest path. The old approach where we built a hub-and-spoke network, you brought people back to the data center. >> Back to the hub. >> To a hub, to go out. It's very painful. Imagine flying from San Fran to Chicago, via Houston? It's very painful and that's what gets done in the old world of security appliances because you can build only so many moats and that's what Zscaler is making redundant or irrelevant. So with a 100 plus locations around the globe with multi-tenant technology, you fly to Paris tomorrow, as soon as you connect to the internet from your hotel or the airport, we automatically redirect your traffic through our Paris data center. Your policy and security magically shows up, gets enforced, you're getting localized content, you're getting amazing response time without having to do anything. >> You're getting the same services that you get anywhere else 'cause it's policy driven with a common infrastructure for ensuring that-- >> And-- >> The issue of distribution is not the determining consideration. >> So it is the heavy lifting we did. >> Right. >> To make sure your policy can automatically show up where it is. And to do that, you're to build some serious technology. The old technology was, policy needs to be pushed once in a while, let's do a batch push. That's what traditional security appliances like firewalls do, they're single tenant, we came with a concept policy on demand per user, it works beautifully and then logs. Any time you go through any check post, the logs are created just like when I go in a building, they have me sign that say Jay went to see Peter at this time, same colored logs are created and they must be secured. So, you may be going to our 50 data centers but your logs are created in 50 locations but in line in real time, without ever writing the disk locally, they get sent to one central logging cluster and they're available within seconds. That's really an example of a purpose-built security cloud as compared to what we are calling imitation clouds. >> Mm >> Where people take a stack of appliances, stick them as virtual machines in Google or AWS cloud and they become a cloud service. I was talking to a customer the other day, he said hey, here was a network security vendor making a pitch and he said, "I thought of it, "as if someone is trying to build a Netflix service "using a bunch of DVD appliances." >> Mm-hmm >> All right so, to do security right, one has to build it for the world of cloud, it's multi-tenant, it's distributed, have you seen it before? Think of Salesforce.com, think of Workday, these were young companies a few years ago like Siebel used to dominate CRM. >> Right. >> PeopleSoft used to dominate HR, what happened to them? Well the world moved to its cloud, the world move to SAS service and these companies tried to use that legacy technology, tried to move to the cloud, it just doesn't work and that's why all these investors and customers love Zscaler's platform. We like to call it born in the cloud for the cloud platform. >> One of the things you didn't mention is that, when you're not doing that huge amount of backhaul traffic, your costs are going to go down pretty dramatically. So if I kind of summarize what you've talked about, we're going to go through, we're in the midst of a cloud transformation. >> Mm-hmm >> We have to rethink applications in the context of improve security, bake it right in which is going to lead to a rethinking of network and finally a rethinking of security. >> That's correct. When your network changes from hub-and-spoke to direct to cloud, you can't have a direct path without security so it drives security transformation. So that's where a security platform like Zscaler comes in. So your traffic from any of your say, X 100 branches or from your mobile device or from your laptop, it simply goes through Zscaler to get the same policy, same protection. So Zscaler gets viewed as an enabler of cloud transformation because without us, you can't transform the network and then security has to be done right. >> Right, so you've had a lot of conversations with customers, give us some sense of what kinds of how it's changing the way they work, how it's changing their operations, how it's changing their cost profiles. >> You know three, four or five years ago, we had to do a fair amount of evangelism but when you're the pioneers, you expect to do that. Like three years ago, three CIOs will tell me, "I like cloud, I'm moving in that direction." Three will say, "I'm thinking about it." And remaining four will say, "Mm-hmm I don't think cloud will happen." Today, all of them want to embrace cloud because they've seen the benefits of it. It's making business more agile, more competitive. Now they're figuring out, how do we do security right, how do I do this transformation without, if I may say, messing it up? >> Mm-hmm >> And that's where, it all starts with thought leader, visionary customers. When I saw GE, Larry Biagini, a global CTO or global CISO driving cloud eight, nine years ago, seeing Siemens saying, I need to make my business more competitive and these are the type of leaders who actually help drive adoption because when they do this stuff, others followed. >> Yeah the recode system responds. >> Exactly, exactly >> Jay Chaudhry, talking about cloud transformation and the crucial role that security is going to play in that transformation. Thanks very much for being on theCUBE. >> Peter, thank you, I appreciate the opportunity. >> And once again we've been speaking with Jay Chaudhry who's the CEO of Zscaler. Thanks for joining us for another CUBE conversation, I'm Peter Burris, see you next time. (upbeat music)

>> Narrator: Live from Washington D.C., it's theCUBE. Covering AWS Public Sector Summit. Brought to you by Amazon Web Services. >> Welcome back, everyone, to Washington D.C. and theCUBE's live coverage of AWS Public Sector Summit. I'm your host, Rebecca Knight, alongside John Furrier. We are joined by Jay Carney. He is the senior vice president global corporate affairs Amazon and AWS. Thank you so much for coming on theCUBE. >> Thank you so much for having me. It's great to be here. >> You are just coming from a panel with Senator Mark Warner of Virginia, where the topic was regulation and tech. I want to hear what was talked about and what your thoughts were there. >> Sure, there were a lot of topics, including the HQ2, which as you know, we're locating in northern Virginia. Senator Warner has a very specific interest in that, and we talked about that a lot. One thing that he's involved in, he's the vice chairman of the Senate Intelligence Committee, the leading democrat on the committee, and he takes these issue very seriously. He's very focused on, especially social media, but tech in general and national security concerns, as well as issues around deep fake news and fake news and the like. Now, a lot of that isn't our territory as a business, but we think that where we do fall into scrutiny for regulation, we welcome the scrutiny. We're a big company, obviously, and we're very focused on serving our customers. Part of delivering for our customers means ensuring that we work with elected officials and regulators and pass that scrutiny well. We'll see what the future brings in different spaces. Our concern, or our hope in general, if it's around privacy or other areas of tech regulation, that uniformity is obviously preferable to having, say, 50 state laws, whether it's around facial recognition technology or broader privacy initiatives. Senator Warner's supportive of a federal legislation, as a lot of folks are both sides of the aisle. >> Jay one of the things that you guys live every day at Amazon, and following you guys for the past nine, ten years now for theCUBE, is you're willing to be misunderstood as a company to continue the long game. Jeff Bezos talked about the long game all the time. Doesn't look at stock prices, all those kind of quips, but the innovation engine has been very strong, and with digital transformation now at an all time high, new value is being created in new ways that some people don't understand. You guys are on a constant mission to educate. Here in D.C., what's clear to me is this awakening of this value proposition, and in some cases, it's not very good, the value. Weaponizing is a word we've heard. Big tech is kind of under a lot of conversations, but there's a lot of good things happening. You guys create a lot of value as a company-- >> Sure, and I think the industry at large creates a lot of value. I think we need to ensure, we, the American people, American citizenry, and on our behalf, those elected officials who ultimately make the decisions, that as we scrutinize and explore regulating some of these arenas, that we do it in a way that creates public benefit, that prevents, wherever possible, misuse of technology, but that continues to allow the kind of innovation that's made the United States the center of technological innovation over the last 30 or 40 years. That's not an easy job, but I think that folks in tech need to work with and collaborate with regulators and lawmakers to talk about how to do that because you wouldn't want, I mean, a good example, I think is technological innovation is value neutral, usually. It's a new service or a new product that can do something. It itself is just a product, so it doesn't have a conscience. It's self moral. How you use it is really what determines whether it's something that's good or bad. Many technologies can be used for good or for ill. We have a service at AWS, a facial recognition service. We're certainly not the only company that provides that service to customers. Thus far, since Amazon recognition has been around, we've had reports of thousands of positive uses, finding missing children, breaking up human sex trafficking, human trafficking rings, assisting law enforcement in positive ways. We haven't heard yet any cases of abuses by law enforcement, but we certainly understand that that potential exists, and we encourage regulators and lawmakers to look closely at that. We've put forth publicly guidelines that we think would be useful as they build a legislative, a regulatory framework. >> (mumbles) asking last night even was saying you guys are very open. He wasn't hiding behind any kind of stories. How do we talk to regulators? We want to embrace those conversations. He wasn't saying, "We want to be regulated." He didn't say that, but he wasn't hiding from the fact that these conversations we need to have. >> I think we understand that the potential misuse of some technology is real. We've seen it in other countries, for example, in ways that violate civil liberties. We want to make sure that in this democracy, that we have an infrastructure in place, a regulatory infrastructure, that continues to allow innovation to blossom but protects the civil liberties of people in the United States. We're a global company, but we started off, and we are an American company, and we care deeply about those issues as a company. >> I think that that's really the big question, is how would this regulatory process work? You're talking about having these conversations, particularly around unintended consequences of these new technologies and services. How would it work? Particularly, someone like you who was in government, now in the private sector, at what point are these conversations taking place, and how might it work? At the innovation stage? At the creation, you know what I mean? Just now that we're really getting into it. >> In some cases, there's real progress being made. On privacy for example, all of your viewers no GDPR in Europe was the first multinational comprehensive privacy regulation that's been implemented. In the United States, we don't have a federal law yet. California's taken steps, has passed a bill, and other states are looking at it. We think for U.S. competitiveness, one law is better than 50 laws. We think that we're fully compliant with GDPR, and it actually was not as complicated for us to meet the compliance requirements as it might've been for other tech companies because of the nature of our business in the European Union. There are aspects of GDPR that I think are unnecessarily bureaucratic or clunky, so there's ways to take that as a base and improve it so that the privacy concerns are rightfully addressed, but innovation continues at pace. >> How about antitrust? We had a conversation a couple years ago to reinvent around antitrust. You made a comment to me, we're faster, ship faster, lower cheaper price, lower prices, how are people harmed? There's been a lot of young academics who are challenging the old antitrust definition. Does digital recast itself in antitrust? This is a conversation that think tanks are starting to have now around what does that mean for the modern era, or modernizing government, including laws of regulation? Your thoughts on that. >> I'm not a lawyer. I'm careful to speak authoritatively where I don't know all the details. Consumer harm is the standard. For all the reasons that you described, our mission as a company is to reward the customer with more convenience, more selection, and lower prices. Certainly, we fulfill that mission and don't meet that standard when it comes to any way you might look at that competitively. Even more broadly, there's a misconception about Amazon. Because we're a consumer-facing business primarily, and because we are involved in a lot of different things, some more successfully than others, that we're perceived as bigger than we are. The fact is retail, our original business, our core business, is the biggest marketplace there is. In the United States, we're less than 4% of retail, and we're not even the biggest retailer in the United States. Cloud, AWS, we're here at the Public Sector Summit. >> You've got competition-- >> We have intense, high quality competition, and deep-pocketed competition. As you know, and your viewers know this, the cloud revolution is in its early stages. The opportunity there is enormous, and we're just getting started. There'll be plenty of winners in this space, so again, I don't see any way that you might look at it, that there would be competitive issues. Also, there's a perception that Amazon itself is singular, so that you buy from Amazon, therefore you're not buying from somebody else, but in fact, when we opened Marketplace, I think in 2001, we opened the website to other sellers. What used to be 100% Amazon product and inventory for sale on amazon.com, has now, 2019, risen to over 55% not being Amazon. Third-party sellers, small and medium sized businesses, more than a million of them in the United States, sell in our store and get access to all the customers we have through our store. That side of our business is growing much faster than the Amazon retail business, and I think it demonstrates the value proposition for all of the small and medium sized businesses. >> Yeah, we've got time for one more question, for Rebecca and I, one, you might have one. As Steve Jobs once said, technology, liberal arts, you've got the nice street signs kind of intersecting, I think that plays now more than ever societal impact has become a huge part of the conversation around tech, tech impact. You're a policy expert. You've been studying it. You're living in D.C. The policy game seems to be more important now than ever before around tech and the participation of technology companies in policy, not just hiring a policy firm, or a team to do it, actively engage and be, as an ingredient of the company. Is there enough people (laughs) that can actually do that, one, and what are some of the key policy opportunities are out there for either young individuals, like my daughter, or other young people coming out of college? Because it seems to me the game is shaping into a new direction. >> The space is fascinating because these issues really are front and center right now around questions around technology and how to ensure that as it continues to evolve that it does so in a way that allows for innovation but also protects private, civil liberties, and the like. You can't be in a more exciting space if you're going to be in the private sector engaging in policy. Even if you're in government, if you're on that side, it's a very interesting space to be in. All of it, tech has grown up, the internet has grown up, and there's no question that with that more attention is being paid. That's fine and appropriate. >> More responsibility and accountability. >> More responsibility, sure. >> I just have one more final thing in this. Because of your vantage point of someone who is in a famously tech savvy administration, the Obama Administration, and then we also see lawmakers questioning Mark Zuckerberg, seemingly not understanding how Facebook makes money, do lawmakers get it? >> I think a lot of lawmakers do. I was just with one, Mark Warner, from Virginia, U.S. senator, former telecomm executive and investor. He very much gets it. The caricature is, I think, exaggerated, but look, that's our job. It's our job, it's the press', it's everybody... One thing we do here with the team we have in D.C. is be a resource of information, try to explain, here's what's happening. Here's how our model works. Here's how the technology works. I think that can only help as regulators and lawmakers decide how they want to approach these problems. >> A lot of innovation opportunities. Just the CIA deal alone is set off from a gestation period, now growth around cloud acceleration. >> I think it demonstrates in a way we're very customer focused, and that is especially true when it comes to our national security agencies and defense agencies, but also that security's our first concern at AWS, as well as at broader Amazon. We're glad to have those customers. >> Thanks for coming by. >> Yup, thanks a lot. >> Yes, excellent. Thanks so much, Jay. >> Thank you. >> I'm Rebecca Knight for John Furrier. Please stay tuned for more of theCUBE AWS Public Sector. We will have Theresa Carlson coming up next. (upbeat music)