(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)

>> Presenter: From around the globe, it's theCUBE with digital coverage of IBM think2021 brought to you by IBM. >> Well, good to have you here on theCUBE. We continue our conversations here as part of the IBM Think initiative. I'm John Walls, your host here on theCUBE joined today by Mirko Novakovic, who is the co-founder and CEO of Instana which is an IBM company. Is specialized in enterprise observability for cloud native applications. And Mirko joins us all the way from Germany, near Cologne, Germany. Mirko, good to see it today. How are you doing? >> I'm good. Hi, John. Nice to meet you. >> You bet yeah. Thank you for taking the time today. First off, let's just give some definitions here. Enterprise observability. What is that? What are we talking about here? >> Yes observability is basically the next generation of monitoring, which means it provides data from a system, from an application to the outside, so that people from the outset can basically judge what's happening inside of an application. So think about you're a big e-commerce provider and you have your shop application and it doesn't work. Observability gives you the ability to really deep dive and see all the relevant metrics, logs and application flows to understand why something is not working as you would expect. >> So if I'm, or just listening to this, I think, okay, I'm monitoring my applications already right. I've got to APM and enforce and and I kind of know what things are going on. What's happening, where the hiccups are, all that. How, what is the enhancement here then in terms of observability taking, it sounds like you're kind of taking APM to a much higher level. >> Absolutely. I mean that's essentially how you can think about it. And we see three things that really make us Instana and enterprise observability different. And number one is automation. So the way we gather this information is fully automated. So you don't have to configure anything. We get inside of your code. We analyze the flow up the clarification we get the arrows, the logs and the metrics fully automatic. And the second is getting context. One of the problems with monitoring is if you have all these monitoring data silos so you have metrics on the one side locks into different tool. What we built is a real context. So we tie those data automatically together so that you get real information out of all the data. And the third is that we provide actions. So basically we use AI to figure out what the problem is and then automate things. Is it a problem resolution, restarting container or resizing your cloud? That's what we suggest automatically out of all the context and data that we gathered. >> So you're talking about automation, context, intelligence you'd combine all of that into one big bundle here then basically, that's a big bundle, right? I'm not a giant vacuum. If you will, you're ingesting all this information. You're looking for, you know, performance metrics. So you're trying to find problems. What's the complexity of tying all that together instead of keeping those functions separate you know, what are what's the benefit to having all that kind of under one roof then? >> Yeah. So from the complexity point of view for the end customer it's really easy because we do it automated. For us as a vendor building this it's super complex but we wanted to make it very easy for the user and I would say the benefit is that you get, we call it the meantime to repair like the time from a problem to resolve the problem gets significantly reduced because normally you have to do that correlation of data manually. And now with that context you get this automated by a machine and we even suggest you these intelligent actions to fix the problem. >> So, I'm sorry, go ahead. >> Yeah. And by the way, one of the things why IBM acquired us and why we are so excited working together with IBM is the combination of that functionality with something like Watson AIOps, because as I said we are suggesting an action and the next step is really fully automating this action with something like Watson AIOps and the automation functionality that IBM has. So that the end user not only gets the information what to do the machine even does and fix the problem automatically. >> Well, and I'm wondering too, just about the kind of the volume that we're dealing with these days in terms of software capabilities and data. You've got obviously a lot more inputs, right? A lot more interaction going on a lot more capabilities. You've got apps they're kind of broken down into microservices now. So, I mean, you've got you've got a lot more action, basically, right? You got a lot more going on and what's the challenge to not only keeping up with that but also building for the future for building for different kinds of capabilities and different kinds of interactions that maybe we can't even predict right now. >> Absolutely. Yeah. So I'm 20 years in that space. When I started, as you said it was a very simple system, right? You had an application server like WebSphere maybe a DB2 database so that was your application. It's like today applications are broken down into hundreds of little services that communicate with each other. And you can imagine if something breaks down in a system where you have two or three components it's maybe not easy, but it's handled by a human to figure out what the problem is. If you have a thousand pieces that are somehow interconnected and something is broken it is really hard to figure that out. And that's essentially the problem that we had to solve with the contacts, with the automation, with AI to figure out how all these things are tied together and then analyze automatically for the user where issues are happening. And by the way, that's also when you look into the future I think things will get more and more complicated. You can see now that people break down from microservice into functions, we get more server less. We get more into a hybrid cloud environment where you operate on premise and in multiple clouds. So things get more complex not less complex from an architectural perspective. >> You bring up clouds too. Is this agnostic, I mean, or do you work with an exclusive cloud provider or are you open for business basically? >> We are open for business but we have to support the different cloud technologies. So we support all the big public cloud vendors from IBM to Amazon, Google, Microsoft. But on the other hand, we see with enterprises maybe there's 10, 20% of the workload in the public cloud but the rest is still on premises. And there's also a lot of legacy. So you have to bring all this together in one view and in one context, and that's one of the things we do. We not only support the modern cloud native applications we also support the legacy on premise world so that we can bring that together. And that helps customer to migrate, right? Because if they understand the workload in the on-premise world it's easier to transform that into a cloud native world but it also gives an end to end view from the end user to we always say from mobile to mainframe, right? From a mobile app down to the mainframe application we can give you an end to end view. >> Yeah, you talk about legacy. In this case, you may be cloud services that people use but they're, but that, you know a lot of these legacy applications, right, too that are running, that are they're still very useful and still highly functional but at some point they're not going to be so would it be easier for you or what do you do in terms of talking with your clients in terms of what do they leave behind? What are they bringing with them? How, what kind of transition timeframe should they be thinking about? Because I don't think you want to be supporting forever, right? I mean, you want to be evolving into newer more efficient services and solutions. And so you've got to bring them along too, I would think. Right? >> Yeah. But to be really honest I think there are two ways of thinking. One is as a vendor you would love to support only the new technologies and don't have to support all the legacy technologies. But on the other hand, the reality is especially in bigger enterprises you will find everything in every word. And so if you want to give a holistic D view into the application stacks you have to support also the older legacy parts because they are part of the business critical systems of the customer. And yes, we suggest to upgrade and go into a cloud native world, but being realistic I think for the next decade we will have to live with a world where you have legacy and new things working together. I think that's just the reality. And in 10 years, what is new today is legacy then, right? >> John: Right exactly. >> So we will always live in a kind of hybrid world between legacy and new things. >> Yeah, you've got this technological continuum going on right? That you know, what's new and shiny today's is going to be, you know old hat in five years. But that's the beauty of it all obviously >> Yes. >> Now talk about AIOps. I mean, go into that relationship a little bit if you would , I mean eventually what is observability set you up to do in terms of your artificial intelligence operations and what are the capabilities now that you're providing in terms of the observability solutions that AIOps can benefit from? >> Yeah, so the way I think about these two categories is that observability is the system of record. That's where all the data is collected and put into context. So that's what we do as Instana is we take all the data metrics, logs, traces, profiles and put it into our system of record by the way in very high granularity, it's very important. So we do not sample, we have second granularity metrics. So very high quality data in that system of record where AIOps is the system of action. This is the system where it takes the data that we have, applies machine learning, statistical analytics et cetera, on it, to figure out, for example root cause of problems or even predict problems in the future, and then suggests actions, right? What the next thing that AI does is it suggests or automates an action that you need to do to to for example, scale up the system, scale down the system scaling down because you want to save costs for example these are all things that are happening in the system of action, which is the AIOps space. >> When I think about what you're talking about in terms of observability, I think, well, who needs it? Everybody is probably the answer to that. Can you give us maybe just a couple of examples of some clients that you've worked with in terms of particular needs that they had, and then how you applied your observability platform to provide them with these kinds of solutions? >> Yeah. I remember a big e-commerce vendor in the US approaching us last October. They were approaching the black Friday, right? Where they sell a lot of goods and they had performance issues but they only had issues with certain types of customers and with their existing APM solution, they couldn't figure out where the problem is because existing solutions sample which means if you have a thousand customers you only see one of them as an example because the other 999 are not in your sample. And so they used us because we don't sample. With us, if you have, they have more than a billion requests today you see every of the 1 billion requests and after a few days they had all the problems figured out. And that's what, that was one of the things that we really do differently is providing all the needed data, not sampling and then giving the context around the problem so that you can solve issues like performance issues on your e-commerce system easily. So they switched and you can imagine switching assistant before black Friday, you only do that if it's really needed. So they were really under pressure and so they switched their APM tool to Instana to be able to fulfill the big demand they have on these black Friday days. >> All right, before I let you go you were just saying they had a high degree of confidence. How were you sweating that one out? Because that was not a small thing at all I would assume. >> Yes. It's not a small thing and to be honest, also it's very hard to predict the traffic on black Fridays. Right? And in this case, I remember our SRE team. They had almost 20 times the traffic of a normal day during that black Friday. And because we don't sample, we need to make sure that we can handle and process all these traces but we did we did pretty well. So I have a high confidence in our platform that we can really handle a big amounts of data. We have one of the biggest companies in the world. The biggest companies in these worlds they use our tool to monitor billions of requests. So I think we have proven that it works. >> Yeah, I would say you're smiling too about it. So I think it, obviously it did work. >> It did work, but yeah, I'm sweating still. Yeah. (laughs) >> Never let them see you, sweat Mirko. I think you're very good at that. And obviously very good at enterprise observability. It's an interesting concept. Certainly putting it well under practice. And thanks for the time today to talk about it here as part of IBM thing to share your company's success story. Thank you Mirko. >> Thanks for having me John. >> All Right. We've been talking about enterprise observability here. IBM Think, The initiative continues here on theCUBE. I'm John Walls and thank you for joining us. (soft music)

(melodious music) >> Voiceover: From around the globe. It's theCUBE with digital coverage of IBM Think 2021. Brought to you by IBM. >> Hi and welcome back to theCUBE's coverage of IBM Think 2021 virtual. I'm John Furrier, host of theCUBE. We're a virtual this year. But we'll be in real life soon, right around the corner, as we come out of COVID. We got a great guest, a CUBE alumni, Jerry Cuomo, IBM Fellow VP, CTO for IBM automation. Jerry, great to see you. Been on since almost since the early days of theCUBE. Good to see you >> Yeah, John. Thrilled to be back again. Thank you. >> What I love about our conversations, one is you're super technical. You've got patents under your belt. You're on the cutting edge. You've been involved in web services and web technologies for a long, long time. You're constantly riding the wave. And also you're a creator of a great podcast called "The Art of Automation", which is the subject of this discussion. As automation becomes central in cloud operations and Hybrid Cloud, which is the main theme of this event this year and the industry. So great to see you. First give us a little background for the folks that may not know you, about your history with IBM and who you are. >> Yeah. So thanks John. So I'm Jerry Cuomo. I've been with IBM for about three decades and I started my career at IBM research in Yorktown at the dawn of the internet. And I've been incredibly fortunate as you mentioned, to be on the forefront of many technology trends over the last three decades, internet software, middleware, including being one of the founding fathers of WebSphere software. I recently helped launch the IBM blockchain initiative and now all about AI powered automation. Which actually brings me back to my roots of studying AI in graduate school. So it's kind of come full circle for me, really enjoying the topic. >> It's funny you mentioned AI in graduate school. I was really kind of into AI when I was an undergraduate and get a master's degree in Computer Science. I kind of went the MBA route. But if you think about what was going on in the eighties during those systems times, a lot of the concepts of systems programming and cloud operations kind of gel well together. So you got this confluence of computer science and engineering AKA now DevOps, DevSecOps, coming together. This is actually a really unique time to bring back the best of the best concepts. Whether it's AI and systems and computer science and engineering into automation. Could you share your view on this? Because you're in a unique position, you've been there done that, now you're on the cutting edge. What's your thoughts? >> Yeah, absolutely John. And just when you think of automation and time, automation is not new. That literally, if you go into Wikipedia and you look up automation, you see patents and references to like steam engine regulators at the dawn of the industrial era, right? So automation has been around and in its simplest form, automation whether it was back then, whether it was in the eighties or today it's about applying technology that uses technology software to perform tasks that were once exclusively done by us, humans. But now what we're seeing is AI coming into the picture and changing the landscape in an interesting way. But I think at its essence, automation is this two-step dance of both eliminating repetitive mundane tasks that help reduce errors and free up our time. So we get back the gift of time, but also helps. It's not about taking jobs away at that point, it's a sentence of two-step dance. That's step one. But if you stop there, you're not getting the full value. Step two is to augment our skills. And to use automation, to help augment our skills. And we get speed, we get quality, we get lower costs, we get improved user experience. So whether it was back in the steam engine times or today with AI, automation is evolving with technology. >> And it's interesting too, as a student of the history of the computer industry, as you are and now a creator with your podcast, which we'll get to in a second. You're starting to see the intersection of these concerts and not bespoke as much as they used to be. You got transformation, digital transformation and innovation are connected and scale. If you think about those three concepts, they don't stand alone anymore. They can stand alone, but they work better together. Transformation. And it is the innovation, innovation provides cloud scale. So if you think about automation, automation is powering this dynamic of taking all that undifferentiated heavy lifting and moving the creativity and the skillset into higher integrated areas. Can you share your thoughts? >> Yeah, no, right on there. When you talk about transformation, jeez, look around us. The pandemic has made, transformation and specifically digital transformation, the default. So everything is digital. Whether it's ordering a pizza, visiting a doctor through telemedicine, or this zoom WebEx based workplace that we live in. But picture a telemedicine environment, talking about transformation and going digital. With 10 X more users, they can't hire 10 X more support staff. And think about it. I forgot my password, does this work on my version of the Apple iPhone or all of that kind of stuff? So their support desks are lit up, right? So as they scale digitally, automation is the relief that that comes into play, which is just in time. So the digital transformation needs automation. And John, I think about it like this, businesses like cars have become computers. So they're programmable. So automation software just like in the cars, it makes the car self-driving. I think about the Tesla model three, which I recently test drove. So with this digital acceleration, digital opens the door for automation. And now we can muse about self-driving business. We can muse about maybe that's step one, right? That's the remove repetitive work, but maybe we can actually augment business to have an autopilot. So it doesn't need us there all the time to drive. And that's the scale that you talked about. That's the scale we need. So automation is really like the peanut butter and chocolate. Digital is the peanut butter automation is the chocolate. They go well together and they produce amazing tastes. >> Yeah. That's a really interesting insight. And I was just put an exclamation point on that because you mentioned self-driving business you're implying, you said the business is a computer. So if you just think about that mind blowing concept for a second. If it's a computer, what's the operating system and what's the suite of applications that are on top of it? So, okay. Let's go in the old days you had a windows machine and you had office, which was a system software, applications software construct. If you map that to the entire company, you're talking about Red Hat and IBM will kind of come working together. Kind of connects the dots a little bit on what Red Hat could, because they're not breaking system company. So if Hybrid Cloud is the system, edge, hybrid, then you got the application suite is all software for the business. >> That's right. That's right. And if you listen to anything these days about what IBM stands for, it's Hybrid Cloud and think Red Hat as kind of the core element of that with OpenShift and AI. And both of those really matter in terms of automation and maybe I'll come back to the Hybrid Cloud or Red Hat thing in a second, but let's just talk about Watson and AI, which is the application. You mentioned scale, which I'm so glad you did. AI could help scale automation. And the trick is, is that automation sometimes gets stuck. It gets stuck when it's working with data that is noisy or unstructured. So there's a lot of structured data in your organization. With that, we can breeze through automation. But if there is more ambiguous data, unstructured, noisy, you need a human in the loop. And when you get a human in the loop, it slows things down. So what AI can start to do, AI and its subordinates, machine learning, natural language processing, computer vision. We can start to make sense of both unstructured and structured data together and we can make a big deal going forward. So that's the AI part. You mentioned Red Hat and, and Hybrid Cloud Park. Well, think about it this way, when you shop, how many stores do you... You don't just shop in one store, right? You go to specialty stores to pick up that special catsup, I don't know or mustard. (audio cuts) In one store and maybe do shopping in another store. Customers using clouds John, aren't very different. They have their specialty places to go. Maybe they're going to be running workloads in Google, involving search and AI related to search. And they're going to be using other clouds for more specialty things. From that perspective, that's a view of hybrid. Customers today, take that shopping analogy. They're going to be using Salesforce or Servicenow, IBM cloud, they have a private cloud. So when you think about automating that world, it's the real world. It's how we shop, whether it's for groceries or for cloud. The Hybrid Cloud is a reality. And how do you make sense of that? Because when an average customer has five clouds, how do you deal with five things? How do you make it easy, normalize? And that's what Red hat really does. >> It's interesting. I'll just share with you though. When I interviewed Arvin, who is now the CEO of IBM when he was at Red Hat summit 2019 in San Francisco. Before he made the acquisition, I was peppering him with questions. Like, you need to get this cloud and he loves cloud, you know, he loves cloud. So he was smiling. He just wanted to say it, he wanted to just say it. And I think Red hat brings that operating kind of mindset where the clouds are just subsystems in the OS of the middleware, which is now software which is software defined business. And this kind of is the talk of your views. Now you have a podcast called "Art of Automation". We want to get that in there, for the folks watching. Search for the podcast, "Art of Automation". This is the stories that you tell. Tell us some stories, from this phenomena. What's the impact of automation for the holistic picture? >> Well, it starts with a lot of, I guess it starts with customers. The stories start with the customer. So we're hearing from customers that AI and automation is where they're investing in 2021. For all the reasons we briefly mentioned, and IBM has a lot to offer there. So we've made AI powered automation a priority. But John, in the pursuit of making it a priority, I've started talking with many of our subject matter experts and was floored by their knowledge, their energy, their passion, and their stories. And I said, we can't keep this to ourselves. We can't keep this locked away. We have to share it. We have to let it out. So basically this is what started the podcast around that. And since then, we've had many industry luminaries from IBM and outside. Starting with customers. We had Klaus Jensen who is the CIO of Memorial Clones Kettering Hospital to talk about automation in healthcare. And he shared great stories. You need to listen to them, about automation is not going to take the place of doctors. But automation will help better read x-rays and look at those shades of gray on the x-ray and interpret it much better than we can. And be able to ingest all of the up-to-date medical research to provide pointers and make connections that the human may not be able to do in that moment. So the two working together are better than any individual. Carol Polson recently joined me to talk, and she's the CIO for Cooperators, to talk about automation and insurance. And she had some great stories too. So John, with that, a bunch of IBM, great IBM fellows like Rama Akkiraju, who is one of Forbes top 20 women in AI research. Talking about AI ops. And also Ruchir Puri talking, and Ruchir has been working on Watson since jeopardy to tell stories about ultimately now how we're teaching AI to code and all the modern programming languages. And really automating application modernization and the like. Four keyed episodes in, we have those under our belt. About 6,000 downloads so far. So it's coming along pretty well. Thanks for asking, John. >> The key is you're a content creator now, as well as a fellow. And this is the democratization, as we say direct to audience, share those stories. Also here, I think you released an ebook. Tell us a little quickly about that. We've got one minute left, give a quick plug for the ebook. >> The book echoes the podcast. Chapters relate to the episodes of the book. We're dropping the first five chapters plus forward for free on the IBM website. Other chapters will become available and drop as they become available. The book makes the content searchable on the internet. We go into more detail with advice on how to get started. You get to hear the topics and the voice of those subject matter experts. And I really suggest you go out and check it out. >> All right, Jerry Cuomo. IBM fellow VP, CTO, IBM automation. Also a content creator, podcast "Art of Automation." Jerry, we're going to list it out on our Silicon angle and our cube sites, gets you some extra love on that. Love the podcast, love the focus on sharing from experts in the field. Thanks for coming on. >> Yeah. Thank you so much for having me again, John. >> Okay, I'm John Furrier with theCUBE. Here for IBM Think 2021. Thanks for watching.

from the cube studios in Palo Alto in Boston connecting with thought leaders all around the world this is a cube conversation hello everybody welcome to the cubes exclusive coverage of IBM thanks 2020 digital event experience the cube covering wall-to-wall we've got a number of interviews planned for you going deep my name is Dave Volante I'm here with stoom in ament's - how you doing doing great Dave so we're socially distant as you can see in the studio and mohab row everybody's you know six feet apart got our masks on took them off for this for this segment so Stu let's get into it so a very interesting time obviously for IBM Arvind Krishna doing the big keynote Jim Whitehurst new president so you got a new leadership a lot of talk about resilience agility and flexibility you know which is kind of interesting obviously a lot of their clients are thinking about kovat 19 in that context iBM is trying to provide solutions and capabilities we're going to get into it but really the linchpin of all this is open shift and RedHat and we're gonna talk about what that means for the vision that Arvind Krishna laid out and let's get into it your your thoughts on think 2020 yeah so Dave of course you know last week we had Red Hat summit so Red Hat is still Red Hat you and I had a nice discussion going into Red Hat summit yes thirty four billion dollar acquisition there now under IBM Jim white her slides over in that new role as president but you know one of the questions we've had fundamentally Dave is does an acquisition like this will it change IBM will it change the cloud landscape openshift and Red Hat are doing quite well we definitely have seen some some of the financials and every audience that hasn't seen your analysis segment of IBM should really go in and see that because the Red Hat of course is one of the bright spots in the financials they're you know good growth rate on the number of customers and what they're doing in cloud and underneath a lot of those announcements you dig down and oh yeah there's openshift and there's Red Hat Enterprise Linux rel so you know I long partner for decades between IBM and Red Hat but is you know how will the IBM scale really help the Red Hat pieces there's a number of announcements underneath you know not just you know how does the entire world work on you know Z and power and all of the IBM platforms but you know I believe it's arvind says one of the enduring platforms needs to be the hybrid cloud and you heard a Red Hat summit the entire week it was the open hybrid cloud was the discussion well yes so that actually is interesting you brought up Arvin's sort of pillars there were three enduring platforms that he cited then the fourth of course is I guess open hybrid cloud but the first was mainframes the second was and I'm not sure this is the right order the second was services and then the third was middleware so basically saying excuse me we have to win the day for the architecture of hybrid cloud what's that mean to you then I'd like to chime in yeah so so Dave first of all you know when when we did our analysis when IBM bought red Hatton says you know my TL DR was does this change the cloud landscape my answer is no if I'm a Amazon I'm not sitting there saying oh geez you know the combination of IBM and Red Hat well they're partners and they're they're gonna be involved in it does IBM have huge opportunities in hybrid cloud multi cloud and edge computing absolutely one of the questions is you know how will I be M services really be transformed you know Dave we've watched over the last decade some of the big service organizations have really shrunk down cloud changed the marginal economics you've done so much discussion of this over the last handful of years that you need to measure yourself against the hyper scalars you need to you know see where you can add value and the question is Dave you know when and where do we think of IBM in the new era well so coming back to sort of your point about RedHat and services is it about cloud is a developer's near-term I've said it's it's more about services than it is about cloud longer-term I think it is about cloud but but IBM's definition of cloud is maybe a little different than 10 hours but when Jeannie when on the roadshow - after the redhead acquisitions you said this is gonna be a creative - free cash flow within one year and the reason why I always believe that is because they were gonna plug Red Hat and we've talked about this an open shift right into their services business and start modernizing applications right away they've actually achieved that so I think they had pretty good visibility and that was kind of a mandate so IBM's huge services organization is in a good position to do that they've got deep industry expertise we heard Arvind Krishna on his keynote talking about that Jim Whitehurst talking more about services you really didn't hear Jim you know previously in his previous roles talk a lot about services other than as part of the ecosystem so it's an interesting balancing act that that iBM has to do the real thing I want to dig into Stu is winning the day with the with with the architecture of hybrid cloud so let's start with with cloud talk about how IBM defines cloud IBM on its earning earnings call we talked about this on our Red Hat Summit analysis the cloud was you know 23 billion you know growing it whatever 20 20 plus percent when my eyes have been bleeding reading IBM financial statements in ten case for the last couple of weeks but when you go in there and you look at what's in that cloud and I shared this on my braking analysis this week a very small portion of that cloud revenue that what last year 21 billion very small portion is actually what they call cloud cloud and cognitive software it's only about 20 percent of the pie it's really services it's about 2/3 services so that is a bit of a concern but at the same time it's their greatest opportunity because they have such depth and services if IBM can increase the percentage of its business that's coming from higher margin software a business which was really the strategy go back 20 years ago it's just as services became this so big it's so pervasive that that software percentage you know maybe it grew maybe it didn't but but that's IBM's opportunities to really drive that that that software based revenues so let's talk about what that looks like how does OpenShift play in that IBM definition of cloud which includes on Prem the IBM public law everybody else's public cloud multi-cloud and the edge yeah well first of all Dave right the question is where does IBM technologies where do they live so you know look even before the Red Hat piece if we looked at IBM systems there's a number of times that you're seeing IBM software living on various public clouds and that it's goodness you know one of the things we've talked about for a number of years is you know how can you become more of a software company how can you move to more of the you know cloud consumption models you go in more op X and capex so IBM had done some of that and Red Hat should be able to help supercharge that when we look at some of the announcements the one that of course caught my other most Dave is the you know IBM cloud satellite would would say the shorthand of it it's IBM's version of outposts and underneath that what is it oh it's open shift underneath there and you know how can I take those pieces and we know open ship can live across you know almost any of the clouds and you know cannot live on the IB cloud IBM cloud absolutely can it be open ship be in the data center and on virtualization whether it be open source or VMware absolutely so satellite being a fundamental component underneath of open ship makes a lot of sense and of course Linux yeah Linux underneath if you look at the the one that we've heard IBM talking about for a while now is cloud packs is really how are they helping customers simplify and build that cloud native stack you start with Red Hat Enterprise Linux you put openshift on top of that and then cloud packs are that simple toolset for whether you're doing data or AI or integration that middleware that you talked about in the past iBM has way the ways that they've done middleware for decades and now they have the wonderful open source to help enable that yeah I mean WebSphere bluemix IBM cloud now but but OpenShift is really that pass layer that that IBM had coveted right and I was talking to some of IBM's partners getting ready for this event and they say if you dig through the 10k cloud packs is one of those that you know there are thousands of customers that are using this so it's good traction not just hey we have this cloud stuff and it's wonderful and we took all of these acquisitions everything from SoftLayer to software pieces but you know cloud packs is you know a nice starter for companies to help really move forward on some of their cloud native application journey yes so what whatever we talked about this past week in the braking analysis and certainly David floor has been on this as well as this notion of being able to run a Red Hat based let's call it a stack everywhere and Jim White has talked about that essentially really whether it's on Prem at the edge in the clouds but the key there stew is being able to do so natively so every layer of you know it began call it the stack IT services the data plane the control plane the management plane all the planes being able to the networking the transport etc being natively able to run wherever it is so that you can take fine-grain advantage and leverage the primitives on respective clouds the advantage that IBM has in my view would love your thoughts on this is that Red Hat based platforms it's open source and so I mean it's somebody gonna trust Amazon to be the the cloud native anybody's cloud yeah you know solution well if you're part of the Amazon stack I mean I Amazon frankly an Oracle have similar kind of mindset you know redstack Amazon stack make it all homogeneous and it'll run just fine IBM's coming at it from an open source perspective so they they in some ways will have more credibility but it's gonna take a lot of investment to really Shepherd those standards they're gonna have to put a lot of commitments in committers and they're gonna have to incent people to actually adhere to those standards yeah I mean David's the idea of pass the platform as a service that we've been chasing as an industry for more than a decade what's interesting if you listen to IBM what's underneath this well it's you know taking advantage of the container based architecture with kubernetes underneath so can I run kubernetes anywhere yeah pretty much every cloud has their own service OpenShift can live everywhere the question is what David floors rightly putting out okay if I bake to a single type of solution can i really take advantage of the native offerings so the discussion we've always had for a long time as dua virtualize something in which case I'm really abstract away I get to you know I can't take advantage of the all various pieces do I do multi cloud in which case I have some least common denominator way of looking at cloud because I what I want to be able to do is get the value in differentiation out of each cloud I use but not be stuck on any cloud and yes Dave Red Hat with openshift and based with kubernetes and the open source community is definitely a leading way to do that what you worry about is saying okay how much is this stuck on containerization will it be able to take advantage of things like serverless you talk to IBM and say okay underneath it's going to have all this wonderful components Dave when I talked to Andy Jesse and he says if I was rebuilding AWS today it would all be service underneath so what is that underlying construct you know is it flexible and can it be updated Red Hat and IBM are going to bridge between the container world and the serverless world with things like a native but absolutely we are not yet at the Nirvana that developers can just build their apps and know that it can run anywhere and take advantage of anything so you know some things we know we need to keep working so a couple other things there so Jim Weider has talked about ingesting innovation that the nature of innovation is such that it comes from a lot of different places open source obviously is a you know fundamental you know component of that he talked about the telco edge he gave an example of Vodafone Arvind Krishna talked about anthem kind of redefining healthcare post kovat so you're seeing some examples of course that's good that IBM puts forth some really you know proof points it's not just you know slide where which is good I think the the interesting thing you know you can't just put you know containers out there and expect the innovation to find its way into those containers it's gonna take a lot of work to make sure that as those different layers of the stack that we were talking about before are actually going to come to fruition so there's there's the there's some other announcements in this regard to these Edgecumbe edge computing application manager let's say the telco edge a lot of automation focused you mentioned IBM satellite there's the financial services cloud so we're seeing IBM actually you know sprinkle around some investments there as I said in my breaking in houses I'd like to see them dial up those investments a little bit more maybe dial down the return of cash at least for the next several years to shareholders yeah I mean Dave the concern you would talk to most customers and you say well if you try to even optimize your own data center and turn it into a cloud how can you take advantage of the innovation that the Amazon Microsoft Google's and IBM's are Tait are putting out there in the world you want to be able to plug into that you want to be able to leverage those those new services so that is where it's definitely a shift Dave you think about IBM over a hundred years usually they're talking about their patent portfolio I I think they've actually opened up a lot of their patent portfolio to help attack you know the kovat 19 so it is definitely a very different message and tenor that I hear under Arvind Krishna you know in very early days than what I was used to for the last decade or two from IBM yeah well at the risk of being a little bit repetitive one of the things that I talked about in my breaking the analysis I highlighted that arvind said he wants to lead with a technical story which I really like Arvin's a technical visionary his predecessors his three predecessors were not considered technical visionaries and so I think that's one of the things that's been lacking inside of IBM I think it's one of the reason why why Services has been such a dominant component so look Lou Gerstner too hard to argue with the performance of the company but when he made the decision and IBM made the decision to go all-in on services something's got to give and what gave and I've said this many many times in the cube was was product leadership so I'd like to see IBM get back to that product leadership and I think Red Hat gives them an opportunity to do that obviously Red Hat Linux you know open source is a leader the leader and this is jump all as we've talked about many times in this multi hybrid cloud edge you know throwing all the buzzwords but there's some interesting horses on the track you got you got VMware we throw in AWS just because they're there you can talk about cloud without talking about AWS certainly Microsoft has designs there Cisco Google everybody wants a piece of that pie and I would say that you know Red Hat with with with OpenShift is in a good position if in fact they can make the investments necessary to build out those stacks yeah it's funny Dave because IBM for the history the size that they are often can get overlooked you talk about you know we've probably spent more air time talking about the VMware Amazon relationship than almost any in the last few years well we forget we were sitting at vmworld and two months before VMware announced the Amazon partnership who was it that was up on the main stage with Pat Gelson der it was IBM because IBM was the first partner I I believe that I saw numbers that IBM was saying that they have more hosted VMware environments than anyone out there I'd love to see the data on it to understand there because you know IBM plays in so many different places they just often are not you know aggregated and counted together you know when you get outside of some of the you know middleware mainframe some of the pieces that you talked about earlier Dave so IBM does have a strong position they just haven't been the front center leader too often but they have a broad portfolio and very much services led so they they kind of get forgotten you know off on the sides so IBM stated strategy is to bring those mission critical workloads into the cloud they've said that 80% of the workloads remain on Prem only 20% have been been clarified you know when you when you peel the onions on that there's just is so much growth and cloud native workloads so you know there's there is a somewhat of a so what in that but I will say this so where are the mission critical workloads where do they live today they live on Prem we can but but but whose stacks are running those it's IBM and it's Oracle and and David floor has done some research that suggests that if you're gonna put stuff into the cloud that's mission-critical you're probably better off staying with those those stacks that are going to allow you to a lower risk move not have to necessarily rip and replace and so you know migrating mission-critical Oracle database into AWS or db2 you know infrastructure into AWS is is gonna be much more challenging than than going same-same into the IBM cloud or the respective Oracle cloud so I guess my question to you Stu is why do people want to move those mission critical workloads into the cloud do they well first of all it's unlocking innovation that you talked about Dave so you know we've looked at from a VMware standpoint versus a red hat standpoint if you talk about building new apps doing containerization having that cloud native mindset do I have a bimodal configuration not so not a word that we talk about as much anymore because I want to be able to modernize it modernizing those applications doing any of those migrations we know or super challenging you know heck David Flair has talked about it for a long long time so you bring up some great points here that you know Microsoft might be the best at meeting customers where they are and giving people a lot of options IBM lines up in many ways in a similar ways my biggest critique about VMware is they don't have tight ties to the application it's mostly you know virtual eyes it or now we have some cloud native pieces but other than the pivotal group they didn't do a lot with modernization on applications IBM with their middleware history Red Hat with everything that they do with the developer communities are well positioned to help customers along those digital journeys and going through those transformations so it's you know applications need to be updated you know if anybody that's used applications that are long in the tooth know that they don't have the features that I want they don't react the way they want heck today Dave everybody needs to be able to access things where they are on the go you know it's not a discussion anymore about you know virtual desktop it's about you know work anywhere have access to the data where I need it and be much more flexible and agile and those are some of the configurations that you know iBM has history and their services arm can help customers move along those journeys yeah so you know I think one of the big challenges iBM has it's got a it's got a its fingers in a lot of pies AI you know they talk a lot about blockchain they're about quantum quantum is not gonna be here for a while it's very cool we have an interview coming up with with Jamie Thomas and you know she's all over the quantum we've talked to her in the past about it but I think you know if you think about IBM's business in terms of services and product you know it's whatever it is a 75 you know billion dollar organization 2/3 or and maybe not quite 2/3 maybe 60 Plus percent is services services are not an R&D intensive business you look at a company like Accenture Stu I think Accenture spent last year 800 million on R&D they're a forty five billion dollar forty six billion dollar company so if you really isolate the IBM you know company to two products whatever its call it 25 30 billion they spend a large portion of that that revenue on R&D to get to the six billion but my argument is it's it's not enough to really drive the type of innovation that they need just another again Accenture data point because they're kind of a gold standard along with IBM you.why and others and and a couple of others in services they return seventy six percent of their cash to shareholders iBM has returned consistently 50 to 60 percent to its shareholders so arvind stated he wants to return IBM to growth you know every every IBM CEO says that Ginni I used to talk about has to shrink to grow as I said unfortunately so you should run out of time and now it's up to Arvind to show that but to me growth has got to come from fueling Rd whether it's organic or inorganic I'd like to see you know organic as the real driver for obvious reasons and I don't think just open source in and of itself obviously is going to attract that it'll attract innovation but whether or not IBM will be able to harness it to his advantage is the real challenge unless they're making huge huge commitments to that open source and in a microcosm you know it's a kind of a proxy we saw what happened to Hortonworks and cloud era because they had to had to fund that open source commitment you know IBM we're talking about much much with the hybrid multi-cloud edge much much bigger opportunity but but requirement and we haven't even talked about AI you know bringing you know I think I think you have a quote on you know data is the fuel what was that quote yes it was Jim Whitehurst he said data is the fuel cloud is the platform AI is accelerant and then security my paraphrase is the mission control there so sounds a lot like your innovation cocktail that you've been talking about for the last year or so Dave but iCloud but so okay but AI is the accelerant and I agree by the way applying AI to all this data that we have you know over the years automating it and scaling it in the cloud it's critical and if IBM wants to define cloud as you know the cloud experience anywhere I'm fine with that I'm not a fan of the way they break down their cloud business I think it's bogus and I've called them on that but okay fine so maybe we'll get by that I'll get over it but but but really that is the opportunity it's just it's got to be funded yeah no Dave absolutely iBM has a lot of really good assets there they've got strong leadership as you said can Arvind do another Satya Nadella transformation there's the culture there's the people and there's the product so you know IBM you know absolutely has a lot of great resources and you know smart people and some really good products out there as well as really good ecosystem partnerships it's you know Amazon is not the enemy to IBM Microsoft is a partner for what they're doing and even Google is somebody that they can work with so you know I always say back in the ten years I've been working for you Dave I think the first time I heard the word coopertition I thought it was like an IBM trademark name because they were the ones that really you know lead as to have a broad portfolio and work with everybody in the ecosystem even though you don't necessarily agree or partner on every piece of what you're doing so in a multi cloud AI you know open ecosystem IBM's got a real shot yeah I mean a Satya Nadella like move would be awesome of course Satya had a much much larger you know of cash hoard to play with but but I guess the similarity stew are you you're notwithstanding that now we have three prominent companies run by Indian native born leaders which is pretty astounding when you think about it but notwithstanding that there are some similarities just in terms of culture and emphasis and getting back to sort of the the technical roots the technical visionaries so I'm encouraged but I'm watching very closely stew as I'm sure you are kind of where those investments go how how it plays in the marketplace but but I think you're right I think people underestimate IBM and and but the combination of IBM Red Hat could be very dangerous yeah Dave how many times do we write the article you know has the sleeping giant of IBM been awoken so I think it's a different era now and absolutely there's IBM has the right cards to be able to play at some of these new tables and it's a different IBM for a different era somebody said to me the other day that and probably you've probably heard this you have to but it was first I heard of it is that within five years IBM had better be a division of Red Hat versus the other way around so all right Stu thanks for for helping to set up the IBM think 2020 digital event experience what coming at you wall-to-wall coverage I think we've got over 40 interviews lined up Stu you you have been doing a great job both last week with the Red Hat summit and helping out with IBM thanks so thanks for that Dave no no rainy week at the new Moscone like we had last year a really good content from the comfort of our remote settings yeah so keep it right there buddy this is Dave a lot a force to Minutemen go to Silicon angle calm you'll check out all the news the the cube net we'll have all of our videos will be running wall-to-wall wiki bong calm has some some of the research action this day Volante force too many we'll be right back right after this short break [Music]

>> From the KIPP studios in Palo Alto in Boston, connecting with thought leaders all around the world, this is a CUBE conversation. >> IBM's new CEO has an opportunity to reset the direction of the company. Outgoing CEO Ginni Rometty, inherited a strategy that was put in place over two decades. It became fossilized in a lower-margin services-led model that she helped architect. Ginni spent a large portion of her tenure, shrinking the company so it could grow. But unfortunately, she ran out of time. For decades, IBM has missed opportunities to aggressively invest in the key waves that are now powering the tech economy. Instead, IBM really tried to balance investing innovation with placating Wall Street. We believe IBM has an opportunity to return to the Big Blue status that set the standard for the tech industry. But several things have to change, some quite dramatically. So we're going to talk about what it's going to take for IBM to succeed in this endeavor. Welcome to this special Wikibon CUBE Insights powered by ETR. In this breaking analysis, we're going to address our view of the future of IBM and try to accomplish three things. First, I want to review IBM's most recent earnings, the very first one under new CEO Arvind Krishna, and we'll discuss IBM's near-term prospects. Next, we'll look at how IBM got to where we are today. We want to review some of the epic decisions that it has made over the past several years and even decades. Finally, we'll look at some of the opportunities that we see for IBM to essentially remake itself and return to that tech titan that was revered by customers and feared by competitors. First, I want to look at the comments from new CEO Arvind Krishna. And let's try to decode them a bit. Arvind in the first earnings call that he held, and in interviews as well, and also internal memos, he's given some clues as to how he's thinking. This slide addresses a few of the key points. Arvind has clearly stated that he's committed to growing the IBM company, and of course, increasing its value. This is no surprise, as you know, every IBM CEO has been under pressure to do the same. And we'll look at that further a little later on in the segment. Arvind, also stated that he wants the company, he said it this way, "To lead with a technical approach." Now as we reported in January when Krishna was appointed to CEO. We're actually very encouraged that the IBM board chose a technical visionary to lead the company. Arvind's predecessors did not have the technical vision needed to make the bold decisions that we believe are now needed to power the company's future. As a technologist, we believe his decisions will be more focused on bigger tactical bets that can pay bigger returns, potentially with more risk. Now, as a point of just tactical commentary, I want to point out that IBM noted that it was doing well coming into the March month, but software deals especially came to a halt as customers focused on managing the pandemic and other parts of the business were okay. Now, this chart pulls some of the data from IBM's quarter. And let me make a few comments here. Now, what was weird here, IBM cited modest revenue growth on this chart, this was pulled from their slides. But revenue was down 2% for the quarter relative to last year. So I guess that's modest growth. Cloud revenue for the past 12 months, the trailing 12 months, was 22 billion and grew 23%. We're going to unpack that in a minute. Red Hat showed good growth, Stu Miniman and I talked about this last week. And IBM continues to generate a solid free cash flow. Now IBM, like many companies, they prudently suspended forward guidance. Some investors bristled at that, but I really have no problem with it. I mean, just way too much uncertainty right now. So I think that was a smart move by IBM. And basically, everybody's doing it. Now, let's take a look at IBM's business segments and break those down and make a few comments there. As you can see, in this graph, IBM's 17 plus billion dollar quarter comprises their four reporting segments. Cloud and cognitive software, which is, of course, its highest margin and highest growth business at 7%. You can see its gross margin is really, really nice. But it only comprises 30% of the pie. Services, the Global Business Services and GTS global technology services are low-growth or no growth businesses that are relatively low margin operations. But together they comprise more than 60% of IBM's revenue in the quarter and consistently throughout the last several years. Systems, by the way, grew nicely on the strength of the Z15 product cycles, it was up by 60% and dragged storage with it. But unfortunately power had a terrible quarter and hence the 4% growth. But decent margins compared to services of 50%. IBM's balance sheet looks pretty good. It took an advantage of some low rates recently and took out another $4 billion in corporate debt. So it's okay, I'm not too concerned about its debt related to the Red Hat acquisition. Now, welcome back to cloud at 22 billion for the past 12 months and growing at 23%. What, you say? That sounds very large, I don't understand. It's understandable that you don't understand. But let me explain with this next graphic. What this shows is the breakdown of IBM's cloud revenue by segment from fiscal year 19. As you can see, the cloud and cognitive segments, or segment which includes Red Hat comprises only 20% of IBM's cloud business. I know, kind of strange. Professional services accounts for 2/3 of IBM's Cloud revenue with systems at 14%. So look, IBM is defining cloud differently than most people. I mean, actually, that's 1% of the cloud business of AWS, Azure and Google Cloud come from professional services and on-prem hardware. This just doesn't have real meaning. And I think frankly, it hurts IBM's credibility as it hides the ball on cloud. Nobody really believes this number. So, I mean, it's really not much else I can say there. But look, why don't we bring in the customer angle, and let's look at some ETR data. So what this chart shows is the results of an ETR survey. That survey ran, we've been reporting on this, ran from mid March to early April. And more than 1200 respondents and almost 800 IBM customers are in there. If this chart shows the percentage of customers spending more on IBM products by various product segments that we chose with three survey samples April last year, January 2020, and the most recent April 2020 survey. So the good news here is the container platforms, OpenShift, Ansible, the Staples of Red Hat are showing strength, even though they're notably down from previous surveys. But that's the part of IBM's business that really is promising. AI and machine learning and cloud, they're right there in the mix, and even outsourcing and consulting and really across the board, you can see a pretty meaningful and respectable number or percent of customers are actually planning on spending more. So that's good, especially considering that the survey was taken right during the middle of the COVID-19 pandemic. But, if you look at the next chart, the net scores across IBM's portfolio, they're not so rosy. Remember, net score is a measure of spending momentum. It's derived by essentially subtracting the percent of customers that are spending less from those that are spending more. It's a nice simple metric. Kind of like NPS and ETR surveys, every quarter with the exact same methodology for consistency so we can do some comparisons over time series, it's quite nice. And you can see here that Red Hat remains the strongest part of IBM's portfolio. But generally in my experience as net scores starts to dip below 25% and kind of get into the red zone, that so called danger zone. And you can see many parts of IBM's portfolio are showing softness as we measure in net score. And even though you see here, the outsourcing and consulting businesses are up relative to last year, if you slice the data by large companies, as we showed you with Sagar Kadakia last week, that services business is showing deceleration, same thing we saw for Accenture, EY, Deloitte, etc. So here's the takeaway. Red Hat, of course, is where all the action is, and that's where IBM is going to invest in our opinion, and we'll talk a little bit more about that and drill into that kind of investment scenario a bit later. But what I want to do now is I want to come back to Arvind Krishna. Because he has a chance to pull off a Satya Nadella like move. Maybe it's different, but there are definite similarities. I mean, you have an iconic brand, a great company, that's in many technology sectors, and yes, there are differences, IBM doesn't have the recurring software revenue that Microsoft had, it didn't have the monopoly and PCs. But let's move on. Arvind has cited four enduring platforms for IBM, mainframes, services, middleware, and the newest hybrid cloud. He says that IBM must win the architectural battle for hybrid cloud. Now, I'm going to really share later what we think that means. There's a lot in that statement, including the role of AI in the edge. Both of which we'll address later on in this breaking analysis. But before we get there, I want to understand from a historical perspective where we think Arvind is going to take IBM. And to do that, we want to look back over the modern history of IBM, modern meaning of the post mainframe dominance era, which really started in 1993 when Louis Gerstner took over. Look, it's been well documented how Louis Gerstner pivoted into services. He wrote his own narrative with the book, "Who Says Elephants Can't Dance". And you know, look, you can't argue with his results. The graphic here shows IBM's rank in the fortune 500, that's the green line over time. IBM was sixth under Gerstner, today it's number 38. The blue area chart on the Insert, it shows IBM's market cap. Now, look, Gerstner was a hero to Wall Street. And IBM's performance under his tenure was pretty stellar. But his decision to pivot to services set IBM on a path that to this day marks company's greatest strength, and in my view, its greatest vulnerability. Name a product under the mainframes in which IBM leads. Again, middleware, I guess WebSphere, okay. But you know, IBM used to be the leader in the all important database market, semiconductors, storage servers, even PCs back in the day. So, I don't want to beat on this too much, I can say it's been well documented. And I said earlier, Ginni essentially inherited a portfolio that she had to unwind, and hence the steep revenue declines as you see here, and it's 'cause she had to jettison the so called non-strategic businesses. But the real issue is R&D, and how IBM has used it's free cash. And this chart shows IBM's breakdown of cash use between 2007 and 2019. Blue is cash return to shareholders, orange is research and development, and gray is CapEx. Now I chose these years because I think we can all agree that this was the period of tech defined by cloud. And you can see, during those critical early formative years, IBM consistently returned well over 50%, and often 60% plus of its free cash flow to shareholders in the form of dividends and stock buybacks. Now, while the orange appears to grow, it's because of what you see in this chart. The point is the absolute R&D spend really didn't change too much. It pretty much hovered, if you look back around 5 1/2 to $6 billion annually, the percentage grew because IBM's revenue declined. Meanwhile, IBM's competitors were spending on R&D and CapEx, what were they doing? Well, they were building up the cloud. Now, let me give you some perspective on this. In 2007 IBM spent $6.2 billion on R&D, Microsoft spent 7 billion that same year, Intel 5.8 billion, Amazon spent 800 million, that's it. Google spent 2.1 billion that year. And that same year, IBM returned nearly $21 billion to shareholders. In 2012 IBM spent $6.3 billion on R&D, Microsoft that year 9.8 billion, Intel 10 billion, Amazon 4.6 billion, less than IBM, Google 6.1 billion, about the same as IBM. That year IBM returned almost $16 billion to shareholders. Today, IBM spends about the same 6 billion on R&D, about the same as Cisco and Oracle. Meanwhile, Microsoft and Amazon are spending nearly $17 billion each. Sorry, Amazon 23 billion, and IBM could only return $7 billion to shareholders last year. So while IBM was returning cash to its shareholders, its competitors were investing in the future and are now reaping the rewards. Now IBM suspended its stock buybacks after the Red Hat deal, which is good, in my opinion. Buybacks have been a poor use of cash for IBM, in my view. Recently, IBM raised its dividend by a penny. It did this so it could say that it has increased its dividend 25 years in a row. Okay, great, not expensive. So I'm glad that that investors were disappointed with that move. But since 2007, IBM has returned more than $175 billion to shareholders. And somehow Arvind has to figure out how to tell Wall Street to expect less while he invests in the future. So let's talk about that a little bit. Now, as I've reported before, here is the opportunity. This chart shows data from ETR. It plots cloud landscape and is a proxy for multi-cloud and hybrid cloud. It plots net score or spending momentum on the y-axis, and market share, which really isn't market share, as we've talked about, it's a measure of pervasiveness in the data set, that's plotted on the x-axis. So, the point is, IBM has presence, it's pervasive in the marketplace, Red Hat and OpenShift, they have relevance, they have momentum with higher net scores. Arvind's opportunity is to really plug OpenShift into IBM's, large install base, and increase Red Hat's pervasiveness, while at the same time lifting IBM momentum. This, in my view, as Stu Miniman and I reported last week at the Red Hat Summit, puts IBM in a leading position to go after multi and hybrid cloud and the edge. So let's break that down a little bit further. When Arvind talks about winning the architectural battle for hybrid cloud, what does he mean by that? Here's our interpretation. We think IBM can create the de facto standard for cloud and hybrid cloud. And this includes on-prem, public cloud, cross clouds, or multi cloud, and importantly, the edge. Here's the opportunity, is to have OpenShift run natively, natively everywhere, on-premises in the AWS cloud, in the Azure Cloud, GCP, Alibaba, and the IBM Cloud and the Oracle Cloud, everywhere natively, so we can take advantage of the respective services within all those clouds. Same thing for on-prem, same thing for edge opportunities. Now I'll talk a little bit more about that in a moment. But what we're talking about here is the entire IT stack running natively, if I haven't made that point on OpenShift. The control plane, the security plane, the transport, the data management plane, the network plane, the recovery plane, every plane, a Red Hat lead stack with a management of resources is 100% identical, everywhere the same cloud experience. That's how IBM is defining cloud. Okay, I'll give them a mulligan on that one. IBM can be the independent broker of this open source standard covering as many use cases and workloads as possible. Here's the rub, this is going to require an enormous amount of R&D. Just think about all the startups that are building cloud native services and imagine IBM building or buying to fill out that IT stack. Now I don't have enough time to go in too deep to all other areas, but I do want to address the edge, the opportunity there and weave in AI. Beyond what I said above, which I want to stress, the points I made above about hybrid, multi-cloud include edge, the edge is a huge opportunity. But IBM and in many other, if not most other traditional players, we think are kind of missing the boat on that. I'll talk about that in a minute. Here's the opportunity, AI inference is going to run at the edge in real-time. This is going to be incredibly challenging. We think about this, a car running inference AI generates a billion pixels per second today, in five years, it'll be 15 times that. The pressure for real-time analysis at the edge is going to be enormous, and will require a new architecture with new processing models that are likely going to be ARM-based in our opinion. IBM has the opportunity to build end-to-end solutions powered by Red Hat to automate the data pipeline from factory to data center to cloud and everywhere. Anywhere there's instruments, IBM has an opportunity to automate them. Now rather than toss traditional Intel-based IT hardware over the fence to the edge, which is what IBM and most people are doing right now, IBM can develop specialized systems and make new silicon investments that can power the edge with very low cost and efficient systems that process data in real-time. Hey look, I'm out of time, but some other things I want you to consider, IBM transitioning to a recurring revenue model. Interestingly, Back to the Future, right? IBM used to have a massive rental revenue stream before it converted that base to sales. But if Arvind can recreate a culture of innovation and win the day with developers via its Red Hat relationships, as I said recently, he will be CEO of the decade. But he has to transform the portfolio by investing more in R&D. He's got to convince the board to stop pouring money back to investors for a number of years, not just a couple of quarters and do Whatever they have to do to protect the company from corporate raiders. This is not easy, but with the right leader, IBM, a company that has shown resilience through the decades, I think it can be done. All right, well, thanks for watching this episode of the Wikibon CUBE Insights powered by ETR. This is Dave Vellante. And don't forget, these episodes are available as podcasts, wherever you listen, I publish weekly on siliconangle.com, where you'll find all the news, I publish on wikibon.com which is our research site. Please comment on my LinkedIn posts, check out etr.plus, that's where all the data lives. And thanks for watching everybody. This is Dave Vellante for Breaking Analysis, we'll see you next time. (soft music)

>> Announcer: Live from San Diego, California, it's theCUBE covering KubeCon and CloudNativeCon. Brought to you by RedHat, the CloudNative Computing Foundation, and its ecosystem partners. >> Stu: Welcome back to theCUBE, I'm Stu Miniman. My cohost for three days of coverage is John Troyer. We're here at KubeCon CloudNativeCon in San Diego, over 12,000 in attendance and happy to welcome back a CUBE alumni and veteran of generations of the stacks that we've seen come together and change over the time, Sheng Liang, who is the co-founder and CEO of Rancher Labs. Thanks so much, great to see you. >> Shang: Thank you Stuart, is very glad to be here. >> All right, so you know Kubernetes, flash to the pan nobody's all that excited about it. I mean, we've seen all these things come and go over the years, Sheng. No but seriously, the excitement is palpable. Every year, you know, so many more people, so many more projects, so much more going on. Help set the stage for you, as to what you see and the importance today of kind of CloudNative in general and you know, this ecosystem specifically. >> Yeah you're so right though, Stuart. Community as a whole and Kubernetes has really come a long way. In the early days, Kubernetes was a uh, you know, somewhat of a technical community, lot of Linux people. But not a whole lot of end users. Not a whole lot of Enterprise customers. I walk in today and just the kind of people I've met, I've probably talked to fifty people already who are just really at the beginning of the show and uh there's a very very large number Enterprise customers. And this does feel like Kubernetes has crossed the chasm and headed in to the mainstream Enterprise market. >> Yeah it's interesting you know I've talked to you know plenty of the people here probably if you brought up things like OpenStack and CloudStack they wouldn't even know what we were talking about. The wave of containerization really seemed to spread far and wide. At Rancher you've done some surveys, give us some of the insight. What are you seeing? You've talked to plenty of customers. Give us where we are with the maturity. >> Definitely, definitely. Enterprise Kubernetes adoption is ready for prime time. You know the So what we're really seeing is some of the early challenges a few years ago a lot of people were having problems with just installing Kubernetes. They were literally just making sure to get people educated about container as a concept. Those have been overcome. Now, uh, we're really facing next generation of growth. And people solve these days solve problems like how do I get my new applications onboarding to Kubernetes. How do I really integrate Kubernetes into my multicloud and hybrid-Cloud strategy? And as Enterprise's need to perform computing in places beyond just the data centers and the cloud, we're also seeing tremendous amount of interest in running Kubernetes on the Edge. So those are some of the major findings of our survey. >> John: That's great. So Sheng I'd love for you to kind of elaborate or elaborate for us where Rancher fits into this. Right. Rancher is, you've been around, you've a mature stack of technology and also some new announcements today so I'd kind of love for you to kind of tell us how you fit in to that landscape you just described. >> Absolutely. This is very exciting and very very fast changing industry. So one of the things that Rancher is able to play very well is we're really able to take work with the community, take the latest and greatest open source technology and actually develop open source products on top this and make that technology useful and consumable for Enterprise at large. So the way we see it, to make Kubernetes work we really need to solve problems at three levels. At the lowest level, the industry need at lot of compliant and compatible certified Kubernetes distros and services. So that's table stakes now. Rancher is a leader in providing CNCF certified Kubernetes distro. We actually provide two of them. One of them is called RKE - Rancher Kubernetes Engine. Something we've been doing it for years. It's really one of the easiest to use and most widely deployed Kubernetes distributions. But we don't force our customers to only use our Kubernetes distribution. Rancher customers can use whatever CNCF certified Kubernetes distribution or Kubernetes services they want. So a lot of our customers use RKE(Rancher Kubernetes Engine) but they also use, when they go to the cloud, they use cloud hosted Kubernetes Services like GKE and EKS. There are really a lot of advantages in using those because cloud providers will help you run these Kubernetes clusters for free. And in many cases they even throw in the infrastructure it takes to run the Kubernetes masters and etcd databases for free. If you're in the cloud, there's really no reason not to be using these Kubernetes services. Now there's one area that Rancher ended up innovating at the Kubernetes distros, despite having these data center focus and cloud focus Kubernetes distros and services. And that is one of our, one of the two big announcements today. And that's called K3S. K3S is a great open source project. It's probably one of the most exciting open source projects in the Kubernetes ecosystem today. And what we did with K3S is we took Kubernetes that's been proven in data center and cloud and we brought it everywhere. So with K3S you can run Kubernetes on a Raspberry Pi. You can run Kubernetes in a surveillance camera. You can run Kubernetes in an ATM machine. You know, we have customers trying to run now Kubernetes in a uh, factory floor. So it really helps us realize our vision of Kubernetes as a new Linux and you run it everywhere. >> Well that's great 'cause you talk about that simplicity that we need and if you start talking about Edge deployment, I don't have the people, I don't have the skillset, and a lot times I don't have the gear, uh, to run that. So you know, help connect the dots as to you know, what led Rancher to do the K3S piece of it and you know, what did we take out? Or what's the differences between K8S and the K3S? >> That's a great question, you know. Even the name "K3S" is actually somewhat a wordplay on K8S You know we kind of cut half of 8 away and you're left with 3. It really happened with some of our early traction we sawing some customers. I remember, in retrospect it wasn't really that long ago. It was like middle of last year, we saw a blog coming out of Chick-fil-A and a group of technical enthusiasts were experimenting with actually running uh, Kubernetes in very, in like Intel Nook servers. You know, they were talking about potentially running three of those servers in every one of their stores and at the time they were using RKE and Rancher Kubernetes Engine to do that. And they run into a lot of issues. I mean to be honest if you think about running Kubernetes in the cloud in the database center, uh these servers have a lot of resources and you also have a dedicated operations teams. You have an SRE to manage them, right? But when you really bring it out into branch offices and Edge computing locations, now all of the sudden, number one, these uh, the software now has to take a lot less resource but also you don't really have SREs monitoring them every day anymore. And you, since these, Kubernetes distro really has to be zero touch and it has to run just like a, you know like a embedded window or Linux server. And that's what K3S was able to accomplish, we were able to really take away lot of the baggage that came with having all the drivers that were necessary to run Kubernetes in the cloud and we were also able to dramatically simplify what it takes to actually start Kubernetes and operate it. >> So unsolicited, I was doing an event right before this one and I asked some people what they looking forward to here at KubeCon. And independently, two different people said, "The thing I'm most excited about is K3S." And I think it's because it's the right slice through Kubernetes. I can run it in my lab. I can run it on my laptop. I can on a stack of Raspberry Pis or Nooks, but I could also run it in production if I, you know I can scale it up >> Stu: Yeah. >> John: And in fact they both got a twinkle in their eye and said well what if this is the future of Kubernetes, like you could take this and you could run it, you know? They were very excited about it. >> Absolutely! I mean, you know, I really think, you know, as a company we survive by, and thrive by delivering the kind of innovation that pushes the market forward right? I mean, we, otherwise people are not going to look at Rancher and say you guys are the originators of Kubernetes technology. So we're very happy to be able to come up with technologies like K3S that effectively greatly broadened the addressable market for everyone. Imagine you were a security vendor and before like all you really got to do is solving security problems. Or if you were a monitoring vendor you were able to solve monitoring problems for a data center and in the cloud. Now with K3S you end up getting to solve the same problems on the Edge and in branch offices. So that's why so many people are so excited about it. >> All right so Sheng you said K3S is one of the announcements this week, what's the rest of the news? >> Yeah so K3S, RKE, and all the GKE, AKS, EKS, they're really the fundamental layer of Kubernetes everywhere. Then on top of that one of the biggest piece of innovation that Rancher labs created is the idea of multi-cluster management. A few years ago it was pretty much of a revolutionary concept. Now it's widely understood. Of course an organization is not going to have just one cluster, they're going to have many clusters. So Rancher is the industry leader for doing multi-cluster management. And these clusters could span clouds, could span data centers, now all the way out to branch offices and the Edge. So we're exhibiting Rancher on the show floor. Everyone, most people I've met here, they know Rancher because of that flash of product. Now our second announcement though is yet another level above Rancher, so what we've seen is in order to really Kubernetes to achieve the next level of adoption in the Enterprise we're seeing you know some of the development teams and especially the less skilled dev ops teams, they're kind of struggling with the learning curve of Kubernetes and also some of the associated technologies around service mesh around Knative, around, you know, CICD, so we created a project called Rio, as in Rio de Janeiro the city. And the nice thing about Rio is it packaged together all these Cloud Native technologies and then we created very easy to use, very simple to understand user experience for developers and dev ops teams. So they no longer have to start with the training course on Kubernetes, on Istio, on Knative, on Tekton, just to get productive. They can pretty much get productive on day one. So that Rio project has hit a very important milestone today, we shipped the beta release for it and we're exhibiting it at the booth as well. >> Well that's great. You know, the beta release of Rio, pulling together a lot of these projects. Can you talk about some folks that, early adopters that have been using them or some folks that have been working with the project? >> Sheng: Yeah absolutely. So I talk about some of the early adoption we're seeing for both K3S and Rio. Uh, what we see the, first of all just the market reception of K3S, as you said, has been tremendous. Couple of even mentioned to you guys today in your earlier interviews. And it is primarily coming from customers who want to run Kubernetes in places you probably haven't quite anticipated before, so I kind of give you two examples. One is actually appliance manufacture. So if you think they used to ship appliances, then you can imagine these appliances come with Linux and they would image their appliance with an OS image with their applications. But what's happening is these applications are becoming so sophisticated they're now talking about running the entire data analytics stack and AI software. So it actually takes Kubernetes not necessarily, because it's one server in a situation of appliance. Kubernetes is not really managing a cluster, but it's managing all the application components and microservices. So they ended up bundling up K3S into their appliance. This is one example. Another example is actually an ISV, that's a very interesting use case as well. So uh, they ship a micro service based application software stack and again their software involves a lot of different complicated components. And they decided to replatform their software on Kubernetes. We've all heard a lot of that! But in their case they have to also ship, they don't just run the software themselves, they have to ship the software to the end users. And most of their end users are not familiar with Kubernetes yet, right? And they don't really want to say, to install our software you go provision the Kubernetes cluster and then you operate it from now on. So what they did is they took K3S and bundled into their application as if it were an application server, almost like a modern day WebLogic and WebSphere, then they shipped the whole thing to their customers. So I thought both of these use cases are really interesting. It really elevates the reach of Kubernetes from just being almost like a cloud platform in the old days to now being an application server. And then I'll also quickly talk about Rio. A lot of interest inside Rio is around really dev ops teams who've had, I mean, we did a survey early on and we found out that a lot of our customers they deploy Kubernetes in services. But they end up building a custom experience on top of their Kubernetes deployment, just so that most of their internal users wouldn't have to take a course on Kubernetes to start using it. So they can just tell that this thing that, this is where my source code is and then every thing from that point on will be automated. So now with Rio they wouldn't have to do that anymore. Effectively Rio is the direct source to URL type of, one step process. And they are able to adopt Rio for that purpose. >> So Sheng, I want to go back to when we started this conversation. You said, you know, the ecosystem growing. That not only, you know, so many vendors here, 129 end users, members of the CNCF. The theme we've been talking about is to really, you know, it's ready for production and people are all embracing it. But to get the vast majority of people, simplicity really needs to come front and center, I think. K3S really punctuates that. What else do we need to do as an ecosystem, you know, Rancher is looking to take a leadership position and help drive this, but what else do you want to see from your peers, the community, overall to help drive this to the promise that it could deliver. >> We really see the adoption of Kubernetes is probably going to wing at three, I mean. We see most organizations go through this three step journey. The first step is you got to install and operate Kubernetes. You know, day one, day two. And I think we've got it down. With K3S it becomes so easy. With GKE it becomes one API call or one simple UI interaction. And CNCS has really stepped up and created a great, you know, compliance certification program, right? So we're not seeing the kind of fragmentation that we saw with some of the other technologies. This is fantastic. Then the second step we see is, which a lot of our customers are going through now, is now you have all the Kubernetes clusters coming from different clouds, different infrastructure, potentially on the Edge. You have a management problem. Now you all of the sudden because we made Kubernetes clusters so easy to obtain you can potentially have a sprawl. If you are not careful you might leave them misconfigured. That could expose a security issue. So really it takes Rancher, it takes our ecosystem partners, like Twistlock, like Aqua. CICD partners, like CloudBees, GitLab. Just everyone really needs to come together, make that, solve that management problem. So not only, uh, you build this Kubernetes infrastructure but then you actually going to get a lot of users and they can use the cluster securely and reliably. Then I think the third step, which I think a lot of work still remain is we really want to focus on growing the footprint of workload, of enterprise workload, in the enterprise. So there the work is honestly just getting started. Anywhere from uh, if you walk into any enterprise you know what percentage of their total workload is running on Kubernetes today? I mean outside of Google and Uber, that percentage is probably very small, right? They're probably in the minority, maybe even in single digit percentage. So, we really need to do a lot of work. You know, we need to uh, Rancher created this project called LongHorn and we also work with a lot of our ecosystem partners in persistence storage area like Portworx, StorageOS, OpenEBS. Lot of us really need to come together and solve this problem of running persistent workload. I mean there was also a lot of talk about it at the keynote this morning, I was very encouraged to hear that. That could easily double, triple the amount of workload that could bring, that could be onboarded into Kubernetes and even experiences like Rio, you know? Make it further simpler, more accessible. That is really in the DNA of Rancher. Rancher wouldn't be surviving and thriving without our insight into how to make our technology consumable and widely adopted. So a lot of work we're doing is really to drive the adoption of Kubernetes in the enterprise beyond, you know, the current state and into something I really don't see in the future, Kubernetes wouldn't be as actually widely used as say AWS or vSphere. That would be my bar for success. Hopefully in a few years we can be talking about that. >> All right, that is a high bar Sheng. We look forward to more conversations with you going forward. Congratulations on the announcement. Great buzz on K3S, and yeah, thanks so much for joining us. >> Thank you very much. >> For John Troyer, I'm Stu Miniman, back with lots more coverage here from KubeCon CloudNativeCon 2019 in San Diego, you're watching theCUBE. [Upbeat music]

>> from our studios in the heart of Silicon Valley. HOLLOWAY ALTO, California It is a cube conversation. >> Welcome to this Special Cube conversation here in Palo Alto, California at the Cube Studios at the Cube headquarters. I'm John for the host, like you were a Dustin Kirkland product manager and Google friend of the Cuban. The community with Cooper Netease been on the Cube Cube alumni. Dustin. Welcome to the Cube conversation. >> Thanks. John's a beautiful studio. I've never been in the studio and on the show floor a few times, but this is This is fun. >> Great to have you on a great opportunity to chat about Cooper Netease yet of what you do out some product man's working Google. But really more importantly on this conversation is about the fifth anniversary, the birthday of Cuba Netease. Today we're celebrating the fifth birthday of Cooper Netease. Still, it's still a >> toddler, absolutely still growing. You think about how you know Lennox has been around for a long time. Open stack has been around these other big projects that have been around for, you know, going on decades and Lenox this case and Cooper nineties. It's going so fast, but It's only five years old, you know. >> You know, I remember Adam Open Stack event in Seattle many, many years ago. That was six years ago. Pubes on his 10th year. So many of these look backs moments. This is one of them. I was having a beer with Lou Tucker. J J Kiss Matic was like one of the first comes at the time didn't make it, But we were talking about open stagger like this Cooper Netease thing. This is really hot. This paper, this initiative this could really be the abstraction layer to kind of bring all this cloud Native wasn't part of the time, but it was like more of an open stack. Try and move up to stack. And it turned out it ended up happening. Cooper Netease then went on to change the landscape of what containers did. Dr. Got a lot of credit for pioneering that got the big VC funding became a unicorn, and then containers kind of went into a different direction because of Cooper duties. >> Very much so. I mean, the modernization of software infrastructure has been coming for a long time, and Cooper nutty sort of brings it all brings it all together at this point, but putting software into a container. We've been doing that different forest for for a lot of time, uh, for a long time, but But once you have a lot of containers, what do you do with that? Right? And that was the problem that Cooper Nettie solved so eloquently and has, you know, now for a couple of years, and it just keeps getting better. >> You know, you mentioned modernization. Let's talk about that because I think the modernization the theme is now pretty much prevalent in every vertical. I'll be in D. C. Next week for the Amazon Webster was public sector Summit, where modernization of governments and nations are being discussed. Education, modernization of it. We've seen it here. The media business that were participating in is about not where you store the code. It's how you code. How you build is a mindset shift. This has been the rial revelation around the Dev Ops Movement Infrastructures Code, now called Cloud Native. Share your thoughts on this modernization mindset because it really is how you build. >> Yeah, I think the cross pollination actually across industries and we even we see that even just in the word containers, right and all the imagery around shipping and shipping containers, we've applied these age old concepts that have been I don't have perfected but certainly optimized over decades of, actually centuries or millennia of moving things across water in containers. Right. But we apply that to software and boom. We have the step function difference in the way that we we manage and we orchestrated and administer code. That's one example of that cross pollination, and now you're talking about, like optimizing optimized governments or economies but being able to maybe then apply other concepts that we've come a long way in computer science do de bop set a good example? You know, applying Dev ops principles to non computer feels. Just think about that for a second. >> It's mind blowing. And if you think about also the step function you mentioned because I think this actually changed a lot of the entrepreneurial landscape as well and also has shaped open source and, you know, big news this this quarter is map are going to shut down due one of the biggest do players. Cloudera merge with Horton Works fired their CEO, the founder Michael. So has retired, Some say forced out. I don't think so. I think it's more of his time. I'm Rodel still there. Open source is a business model, you know. Can we be the red hat for her? Duped the red? Not really kind of the viable, but it's evolving. So open source has been impacted by this step function. There's a business impact. Talk about the dynamics with step function both on the business side and on how software's built specifically open source. >> You know, you and I have been around open source for a long, long time. I think it started when I was in college in the late nineties on then through my career at IBM. And it's It's interesting how on the fringe open source was for so long and such so so much of my BM career. And then early time spent onside it at Red Hat. It was it was something that was it was different, was weird. It was. It was very much fringe where the right uh, but now it's in mainstream and it's everywhere, and it's so mainstream that it's almost the defacto standard to just start with open source. But you know, there's some other news that's been happening lately that she didn't bring up. But it's a really touchy aspect of open source right now on that's on some of the licenses and how those licenses get applied by software, especially databases. When offered as a service in the cloud. That's one of the big problems. I think that that's that we're we're working within the open >> source, summarize the news and what it means. What's what's happening? What's the news and what's the really business? Our technical impact to the licensing? What's the issue? What's the core issue? >> Yeah, eso without taking judgment any any way, shape or form on this, the the the TL D are on. This is a number of open source database is most recently cockroach D. B. I have adopted a different licensing model that is nonstandard from an open source perspective. Uh, and from one perspective, they're they're adopting these different licensing models because other vendors can take that software and offered as a service, yes, and in some some cases, like Amazon like Sure, you said, uh, and offered as a as a service, uh, and maybe contribute. Maybe pay money to the smaller startup or the open source community behind it. But not necessarily. Uh, and it's in some ways is quite threatening to open source communities and open source companies on other cases, quite empowering. And it's going to be interesting to see how that plays out. The tension between open sourcing software and eventually making money off of it is something that we've we've seen for, you know, at least 25. >> And it continues to go on today, and this is, to me a real fascinating area that I think is going to be super important to keep an eye on because you want to encourage contribution and openness. Att the same time we look at the scale of just the Lenox foundations numbers. It's pretty massive in terms of now, the open source contribution. When you factor in even China and other nations, it's it's on exponential growth, right? So is it just open source? Is the model not necessarily a business? Yeah. So this is the big question. No one knows. >> I think we crossed that. And open source is the model. Um, and this is where me is a product manager. That's worked around open source. I've spent a lot of time thinking about how to create commercial offerings around open source. I spent 10 years at Economical, the first half of which, as an engineer, the second half of which, as a product manager around, uh, about building services, commercial services around 12 And I learned quite a few things that now apply absolutely to communities as well as to a number of open source startups. That that I've advised on DH kind of given them some perspective on maybe some successful and unsuccessful ways to monetize that that opens. >> Okay, so doesn't talk about Let's get back to Coburg. And so I think this is the next level Talk track is as Cooper Netease has established itself and landed in the industry and has adoption. It's now an expansion votes the land adopted expand. We've seen adoption. Now it's an expansion mode. Where does it go from here? Because you look at the tale signs things like service meshes server. Listen, you get some interesting trends that going to support this expansionary stage of uber netease. What is your view about the next expansion everyway what >> comes next? Yeah, I I think I think the next stage is really about democratizing communities for workloads that you know. It's quite obvious where when communities is the right answer at the scale of a Google or a Twitter or Netflix or, you know, some of these massive services that it is obviously and clearly the best answer to orchestrating containers. Now I think the next question is, how does that same thing that works at that massive scale Also worked for me as a developer at a very small scale helped me develop my software. My small team of five or 10 people. Do I need a coup? Burnett. He's If I'm ah five or 10 person startup. Well, I mean, not the original sort of borde vision of communities. It's probably overkill, but actually the tooling has really advanced, and we now >> have >> communities that makes sense on very small scales. You've got things like a three s from from Rancher. You've got micro Kates from from my colleagues at economical other ways of making shrinking communities down to something that fits, perhaps on devices perhaps at the edge, beyond just the traditional data center and into remote locations that need to deploy manage applications >> on the Cooper Netease clustering the some of the tech side. You know, we've seen some great tech trends as mentioned in Claudia Horton. Works and map Our Let's Take Claudia and Horton work. Remember back in the old days when it was booming? Oh, they were so proud to talk about their clusters. I stood up all these clusters and then I would ask them, Well, what do you doing with it? Well, we're storing data. I think so. That became kind of this use case where standing up the cluster was the use case and they're like, OK, now let's put some data in it. It's a question for you is Coburn. Eddie's a little bit different. I'm not seeing they were seeing real use cases. What are people standing up? Cuban is clusters for what specific Besides the same Besides saying I've done it. Yeah, What's the what's the main use case that you're seeing this that has real value? >> Yeah, actually, there's you just jog t mind of really funny memory. You know, back in those big data days, I was CEO of a startup. We were encrypting data, and we were helping encrypt healthcare data for health care companies and the number of health care companies that I worked with at that time who said they had a big data problem and they had all of I don't know, 33 terabytes worth of worth of data that they needed to encrypt. It was kind of humorous sometimes like, Is that really a big, big data problem? This fits on a single disc, you know, Uh, but yeah, I mean, it's interesting how >> that the hype of of the tech was preceding. The reality needs needs, says Cooper Nettie. So I have a Cuban Eddie's cluster for blank. Fill in the blank. What are people saying? >> Yeah, uh, it's It's largely about the modernization. So I need to modernize my infrastructure. I'm going to adopt the platform. That's probably not, er, the old er job, a Web WebSphere type platform or something like that. I'm investing in hardware investing in Software Middle, where I'm investing in people, and I want all of those things to line up with where industry is going from a software perspective, and that's where Cooper Nighties is sort of the cornerstone piece of that Lennox Of course, that's That's pretty well established >> canoes delivery in an integration piece of is that the pipeline in was, that was the fit on the low hanging fruit use cases of Cooper Netease just development >> process. Or it's the operations it's the operations of now got software that I need to deploy across multiple versions, perhaps multiple sites. Uh, I need to handle that upgrade ideally without downtime in a way that you said service mash in a way that meshes together makes sense. I've got a roll out new certificates I need to address the security, vulnerability, thes air, all the things that Cooper and I used to such a better job at then, what people were doing previously, which was a whole lot of four loops, shell strips and sshh pushing, uh, pushing tar balls around. Maybe Debs or rpm's around. That is what Cooper not he's actually really solves and does an elegant job of solving as just a starting point. And that's just the beginning and, you know, without getting ve injury here, you know, Anthros is the thing that we had at Google have built around Cooper Netease that brings it to enterprise >> here the other day did a tweet. I called Anthem. I just typing too fast. I got a lot of crap on Twitter for that mission. And those multi cloud has been a big part of where Cubans seems to fit. You mentioned some of the licensing changes. Cloud has been a great resource for a lot of the new Web scale applications from all kinds of companies. Now, with several issues seeing a lot more than capabilities, how do you see the next shift with data State coming in? Because God stateless date and you got state full data. Yeah, this has become a conversation point. >> Yeah, I think Kelsey Hightower has said it pretty eloquently, as he usually does around the sort of the serval ist movement and lets lets developers focus on just their code and literally just their code, perhaps even just their function in just their piece of code, without having to be an expert on all of the turtles all the way, all the way down. That's the big difference about service have having written a couple of those functions. I can I can really invest my time on the couple of 100 lines of code that matter and not choosing a destro choosing a cougar Nati is choosing, you know, all the stack underneath. I simply choose the platform where I'm gonna drop that that function, compile it, uploaded and then riff and rub. On that >> fifth anniversary, Cooper Netease were riffing on Cooper Netease. Dustin Circle here inside the Cube Cube Alumni you were recently at the coop con in overseas in Europe, Barcelona, Barcelona, great city. Keeps been there many times. Do was there covering for us. Couldn't make this trip, Unfortunately, had a couple daughter's graduating, so I didn't make the trip. Sorry, guys. Um, what was the summary? What was the takeaway? Was the big walk away from that event? What synthesized? The main stories were the most important stories being >> told. >> Big news, big observations. >> It was a huge event to start with. It was that fear of Barcelona. Um, didn't take over the whole space. But I've been there a number of times from Mobile World Congress. But, you know, this is this is cube con in the same building that hosts all of mobile world Congress. So I think 8,000 attendees was what we saw. It's quite celebratory. You know, I think we were doing some some pre fifth birthday bash celebrations, Key takeaways, hybrid hybrid, Cloud, multi Cloud. I think that's the world that we've evolved into. You know, there was a lot of tension. I think in the early days about must stay on. Prem must go to the cloud. Everything's there's gonna be a winner and a loser and everything's gonna go one direction or another. I think the chips have fallen, and it's pretty obvious now that the world will exist in a very hybrid, multi cloud state. Ultimately, there's gonna be some stuff on Prem that doesn't move. There's going to be some stuff better hosted in one arm or public clouds. That's the multi cloud aspect, Uh, and there will be stubborn stuff at the edge and remote locations and vehicles on oil rigs at restaurants and stores and >> so forth. What's most exciting from a trans statement? What do you what? What's what's getting you excited from what you see on the landscape out there? >> So the tying all of that to Cooper Netease, Cuban aunties, is the thing that basically normalizes all of that. You write your application put it in a container and expect to communities to be there to scale that toe. Operate that top grade that to migrate that over time. From that perspective, Cooper nineties has really ticked, ticked all the boxes, and you've got a lot of choices now about which companies here, you're going to use it and where >> beyond communities, a lot of variety of projects coop flow, you got service messes out there a lot of difference. Project. What's What's a dark horse? What's something that sets out there that people should be paying attention to? That you see emerging? That's notable. That should be paying attention. To >> think is a combination of two things. One is pretty obvious, and that's a ML is coming like a freight train and is sort of the next layer of excitement. I think after Cooper, Netease becomes boring, which hopefully if we've done our jobs well, that communities layer gets settled and we'll evolve. But the sort of the hockey stick hopefully settles down and it becomes something super stable. Uh, the application of machine learning to create artificial intelligence conclusions, trends from things that is sort of the next big trend on then I would say another one If you really want the dark horse. I think it's around communications. And I think it's around the difference in the way that we communicate with one another across all forms of media voice, video chat, writing, how we interact with people, how we interact with our our tools with our software and in fact, how our software in Iraq's with us in our software acts with with other software that communications industry is, it's ripe for some pretty radical disruption. And you know some of the organizations and they're doing that. It's early early days on those >> changes. Final point you mentioned earlier in our conversation here about how Dev Ops is influencing impacting non tech and computer science. Really? What did you mean by that? >> Uh, well, I think you brought up unexpectedly and that that you were looking at the way Uh, some other industries are changing, and I think that cross pollination is actually quite quite powerful when you take and apply a skill and expertise you have outside of your industry. But it adds something new and interesting, too, to your professional environment. That's where you get these provocative operations. He's really creative, innovative things that you know. No one really saw it coming. >> Dave Ops principles apply to other disciplines. Yeah, agility. That's that's pointing down waterfall based processes. That's >> one phenomenal example. Imagine that for governments, right to remove some of the like the pain that you and I know. I've got to go and renew my license. My birthday's coming up. I gotta go to renew my driver's license. You know much. I'm dreading going to the the DMV Root >> Canal driver's license on the same. Exactly >> how waterfall is that experience. And could we could we beam or Mohr Agile More Dev Autopsy and some of our government across >> the U. S. Government's procurement practices airbase upon 1990 standards they still want Request a manual, a physical manual for every product violent? Who does that? >> I know that there are organizations trying to apply some open source principles to government. But I mean, think about, you know, just democracy and how being a little bit more open and transparent in the way that we are in open source code, the ability to accept patches. I have a side project, a passion for brewing beer and I love applying open source practices to the industry of brewing. And that's an example of where use professional work, Tio. Compliment a hobby. >> All right, we got to bring some cubic private label, some Q beer. >> If you like sour beer, I'm in the sour beer. >> That's okay. We like to get the pus for us. Final question for you. Five years from now, Cooper needs to be 10 years old. What's the world gonna look like when we wake up five years from now with two Cuban aunties? >> Yeah, I think, uh, I don't think we're struggling with the Cooper nutties. Uh, the community's layer. At that point, I think that's settled science, inasmuch as Lennox is pretty settled. Science, Yes, there's a release, and it comes out with incremental features and bug fixes. I think Cuban aunties is settled. Science management of of those containers is pretty well settled. Uh, five years from now, I think we end up with software, some software that that's writing software. And I don't quite mean that in the way That sounds scary, uh, and that we're eliminating developers, but I think we're creating Mohr powerful, more robust software that actually creates that that software and that's all built on top of the really strong, robust systems we have underneath >> automation to take the heavy lifting. But the human creation still keeping one of the >> humans Aaron the look it's were We're many decades away from humans being out of the loop on creative processes. >> Dustin Kirkland, he a product manager of Google Uh, Cooper Netease guru also keep alumni here in the studio talking about the coup. Burnett. He's 50 year anniversary. Of course, the kid was president creation during the beginning of the wave of communities. We love the trend we love Cloud would left home a tec. I'm Sean for here in Palo Alto. Thanks for watching.

>> Live, from San Francisco, it's theCUBE covering IBM Think 2019. Brought to you by IBM. >> Hello everyone, welcome back to theCUBE's live coverage here in San Francisco for IBM Think 2019. I'm John Furrier, Stu Miniman with theCUBE. Stu, it's been a great day. We're on our fourth day of four days of wall to wall coverage. A theme of AI, large scale compute with Cloud and data that's great. Great topics. Got two great guests here. Rohit Badlaney, who's the director of IBM Z As a Service, IBM Systems. Real great to see you. And Nataraj Nagaratnam, Distinguished Engineer and CTO and Director of Cloud Security at IBM and Hybrid Cloud, thanks for joining us. >> Glad to be here. >> So, the subtext to all the big messaging around AI and multi-cloud is that you need power to run this. Horsepower, you need big iron, you need the servers, you need the storage, but software is in the heart of all this. So you guys had some big announcements around capabilities. The Hyper Protect was a big one on the securities side but now you've got Z As a Service. We've seen Linux come on Z. So it's just another network now. It's just network computing is now tied in with cloud. Explain the offering. What's the big news? >> Sure, so two major announcements for us this week. One's around our private cloud capabilities on the platform. So we announced our IBM Cloud Private set of products fully supported on our LinuxOne systems, and what we've also announced is the extensions of those around hyper-secure workloads through a capability called the Secure Services Container, as well as giving our traditional z/OS clients cloud consumption through a capability called the z/OS Cloud Broker. So it's really looking at how do we cloudify the platform for our existing base, as well as clients looking to do digital transformation projects on-premise. How do we help them? >> This has been a key part of this. I want to just drill down this cloudification because we've been talking about how you guys are positioned for growth. All the REORG's are done. >> Sure, yeah >> The table's all set. Products have been modernized, upgraded. Now the path is pretty clear. Kind of like what Microsoft's playbook was. Build the core cloudification. Get your core set of products cloudified. Target your base of customers. Grow that and expand into the modern era. This is a key part of the strategy, right? >> Absolutely right. A key part of our private cloud strategy is targeted to our existing base and moving them forward on their cloud journey, whether they're looking to modernize parts of their application. Can we start first with where they are on-premise is really what we're after. >> Alright, also you have the Hyper Protect. >> Correct. >> What is that announcement? Can you explain Hyper Protect? >> Absolutely. Like Rohit talked about, taking our LinuxOne capabilities, now that enterprise trusts the level of assurance, the level of security that they're dependent on, on-premise and now in private cloud. We are taking that further into the public cloud offering as Hyper Protect services. So these are set of services that leverage the underlyings of security hardening that nobody else has the level of control that you can get and offering that as a service so you don't need to know Z or LinuxOne from a consumption perspective. So I'll take two examples. Hyper Protect Crypto Service is about exposing the level of control. That you can manage they keys. What we call "keep your own keys" because encryption is out there but it's all about key management so we provide that with the highest level of security that LinuxOne servers from us offer. Another example is database as a service, which runs in this Hyper Secure environment. Not only encryption and keys, but leveraging down the line pervasive encryption capabilities so nobody can even get into the box, so to say. >> Okay, so I get the encryption piece. That's solid, great. Internet encryption is always good. Containers, there's been discussions at the CNCF about containers not being part of the security boundaries and putting a VMware around it. Different schools of thought there. How do you guys look at the containerization? Does that fit into Secure Protect? Talk about that dynamic because encryption I get, but are you getting containers? >> Great question because it's about the workload, right? When people are modernizing their apps or building cloud-native apps, it's built on Kubernetes and containers. What we have done, the fantastic work across both the IBM Cloud Private on Z, as well as Hyper Protect, underlying it's all about containers, right? So as we deliver these services and for customers also to build data services as containers or VM's, they can deploy on this environment or consume these as a compute. So fundamentally it's kubernetes everywhere. That's a foundational focus for us. When it can go public, private and multicloud, and we are taking that journey into the most austere environment with a performance and scale of Z and LinuxONE. >> Alright, so Rohit, help bring us up to date. We've been talking about this hybrid and multi-cloud stuff for a number of years, and the idea we've heard for many years is, "I want to have the same stack on both ends. I want encryption all the way down to the chip set." I've heard of companies like Oracle, like IBM say, "We have resources in both. We want to do this." We understand kubernetes is not a magic layer, it takes care of a certain piece you know and we've been digging in that quite a bit. Super important, but there's more than that and there still are differences between what I'm doing in the private cloud and public cloud just naturally. Public cloud, I'm really limited to how many data centers, private cloud, everything's different. Help us understand what's the same, what's different. How do we sort that out in 2019? >> Sure, from a brand perspective we're looking at private cloud in our IBM Cloud Private set of products and standardizing on that from a kubernetes perspective, but also in a public cloud, we're standardizing on kubernetes. The key secret source is our Secure Services Container under there. It's the same technology that we use under our Blockchain Platform. Right, it brings the Z differentiation for hyper-security, lockdown, where you can run the most secure workloads, and we're standardizing that on both public and private cloud. Now, of course, there are key differences, right? We're standardizing on a different set of workloads on-premise. We're focusing on containerizing on-premise. That journey to move for the public cloud, we still need to get there. >> And the container piece is super important. Can you explain the piece around, if I've got multi-cloud going on, Z becomes a critical node on the network because if you have an on-premise base, Z's been very popular, LinuxONE has been really popular, but it's been for the big banks, and it seems like the big, you know, it's big ire, it's IBM, right? But it's not just the mainframe. It's not proprietary software anymore, it's essentially large-scale capability. >> Right. >> So now, when that gets factored into the pool of resources and cloud, how should customers look at Z? How should they look at the equation? Because this seems to me like an interesting vector into adding more head room for you guys, at least on the product side, but for a customer, it's not just a use case for the big banks, or doing big backups, it seems to have more legs now. Can you explain where this fits into the big picture? Because why wouldn't someone want to have a high performant? >> Why don't I use a customer example? I had a great session this morning with Brad Chun from Shuttle Fund, who joined us on stage. They know financial industry. They are building a Fintech capability called Digital Asset Custody Services. It's about how you digitize your asset, how do you tokenize them, how you secure it. So when they look at it from that perspective, they've been partnering with us, it's a classic hybrid workload where they've deployed some of the apps on the private cloud and on-premise with Z/LinuxONE and reaching out to the cloud using the Hyper Protect services. So when they bring this together, built on Blockchain under the covers, they're bringing the capability being agile to the market, the ability for them to innovate and deliver with speed, but with the level of capability. So from that perspective, it's a Fintech, but they are not the largest banks that you may know of, but that's the kind of innovation it enables, even if you don't have quote, unquote a mainframe or a Z. >> This gives you guys more power, and literally, sense of pretty more reach in the market because what containers and now these kubernetes, for example, Ginni Rometty said "kubernetes" twice in her keynote. I'm like, "Oh my God. The CEO of IBM said 'kubernetes' twice." We used to joke about it. Only geeks know about kubernetes. Here she is talking about kubernetes. Containers, kubernetes, and now service missions around the corner give you guys reach into the public cloud to extend the Z capability without foreclosing the benefits of Z. So that seems to be a trend. Who's the target for that? Give me an example of who's the customer or use case? What's the situation that would allow me to take advantage of cloud and extend the capability to Z? >> If you just step back, what we're really trying to do is create a higher shorten zone in our cloud called Hyper Protect. It's targeted to our existing Z base, who want to move on this enterprise out journey, but it's also targeted to clients like Shuttle Fund and DAX that Raj talked about that are building these hyper secure apps in the cloud and want the capabilities of the platform, but wanted more cloud-native style. It's the breadth of moving our existing base to the cloud, but also these new security developers who want to do enterprise development in the cloud. >> Security is key. That's the big drive. >> And that's the beauty of Z. That's what it brings to the table. And to a cloud is the hyper lockdown, the scale, the performance, all those characteristics. >> We know that security is always an on-going journey, but one of the ones that has a lot of people concerned is when we start adding IoT into the mix. It increased the surface area by orders of magnitude. How do those type of applications fit into these offerings? >> Great question. As a matter of fact, I didn't give you the question by the way, but this morning, KONE joined me on stage. >> We actually talked about it on Twitter. (laughs) >> KONE joined us on stage. It's about in the residential workflow, how they're enabling here their integration, access, and identity into that. As an example, they're building on our IoT platform and then they integrate with security services. That's the beauty of this. Rohit talked about developers, right? So when developers build it, our mission is to make it simple for a developer to build secure applications. With security skill shortage, you can't expect every developer to be a security geek, right? So we're making it simple, so that you can kind of connect your IoT to your business process and your back-end application seamlessly in a multi-cloud and hybrid-cloud fashion. That's where both from a cloud native perspective comes in, and building some of these sensitive applications on Hyper Protect or Z/LinuxONE and private cloud enables that end to end. >> I want to get you guys take while you're here because one of the things I've observed here at Think, which is clearly the theme is Cloud AI and developers all kind of coming together. I mean, AI, Amazon's event, AI, AI, AI, in cloud scale, you guys don't have that. But developer angle is really interesting. And you guys have a product called IBM Cloud Private, which seems to be a very big centerpiece of the strategy. What is this product? Why is it important? It seems to be part of all the key innovative parts that we see evolving out of the thing. Can you explain what is the IBM Cloud Private and how does it fit into the puzzle? >> Let me take a pass at it Raj. In a way it is, well, we really see IBM Cloud Private as that key linchpin on-premise. It's a Platform as a Service product on-premise, it's built on kubernetes and darker containers, but what it really brings is that standardized cloud consumption for containerized apps on-premise. We've expanded that, of course, to our Z footprint, and let me give you a use case of clients and how they use it. We're working with a very big, regulated bank that's looking to modernize a massive monolithic piece of WebSphere application server on-premise and break it down into micro-services. They're doing that on IBM Cloud Private. They've containerized big parts of the application on WebSphere on-premise. Now they've not made that journey to the cloud, to the public cloud, but they are using... How do you modernize your existing footprint into a more containerized micro-services one? >> So this is the trend we're seeing, the decomposition of monolithic apps on-premise is step one. Let's get that down, get the culture, and attract the new, younger people who come in, not the older guys like me, mini-computer days. Really make it ready, composable, then they're ready to go to the cloud. This seems to be the steps. Talk about that dynamic, Raj, from a technical perspective. How hard is it to do that? Is it a heavy lift? Is it pretty straight-forward? >> Great question. IBM, we're all about open, right? So when it comes to our cloud strategy open is the centerpiece offered, that's why we have banked on kubernetes and containers as that standardization layer. This way you can move a workflow from private to public, even ICP can be on other cloud vendors as well, not just IBM Cloud. So it's a private cloud that customers can manage, or in the public cloud or IBM kubernetes that we manage for them. Then it's about the app, the containerized app that can be moved around and that's where our announcements about Multicloud Manager, that we made late last year come into play, which helps you seamlessly move and integrate applications that are deployed on communities across private, public or multicloud. So that abstraction venire enables that to happen and that's why the open... >> So it's an operational construct? Not an IBM product, per say, if you think about it that way. So the question I have for you, I know Stu wants to jump in, he's got some questions. I want to get to this new mindset. The world's flipped upside down. The applications and workloads are dictating architecture and programmability to the DevOps, or infrastructure, in this case, Z or cloud. This is changing the game on how the cloud selection is. So we've been having a debate on theCUBE here, publicly, that in some cases it's the best cloud for the job decision, not a procurement, "I need multi-vendor cloud," versus I have a workload that runs best with this cloud. And it might be as if you're running 365, or G Suite as Google, Amazon's got something so it seems to be the trend. Do you agree with that? And certainly, there'll be many clouds. We think that's true, it's already happened. Your thoughts on this workload driving the requirements for the cloud? Whether it's a sole purpose cloud, meaning for the app. >> That's right. I'll start and Rohit will add in as well. That's where this chapter two comes into play, as we call Chapter Two of Cloud because it is about how do you take enterprise applications, the mission-critical complex workloads, and then look for the enablers. How do you make that modernization seamless? How do you make the cloud native seamless? So in that particular journey, is where IBM cloud and our Multicloud and Hybrid Cloud strategy come into play to make that transition happen and provide the set of capabilities that enterprises are looking for to move their critical workloads across private and public in bit much more assurance and performance and scale, and that's where the work that we are doing with Z, LinuxONE set of as an underpinning to embark on the journey to move those critical workloads to their cloud. So you're absolutely right. When they look at which cloud to go, it's about capabilities, the tools, the management orchestration layers that a cloud provider or a cloud vendor provide and it's not only just about IBM Public Cloud, but it's about enabling the enterprises to provide them the choice and then offer. >> So it's not multicloud for multicloud sake, it's multicloud, that's the reality. Workload drives the functionality. >> Absolutely. We see that as well. >> Validated on theCUBE by the gurus of IBM. The cloud for the job is the best solution. >> So I guess to kind of put a bow on this, the journey we're having is talking about distributed architectures, and you know, we're down on the weeds, we've got micro-services architectures, containerization, and we're working at making those things more secure. Obviously, there's still a little bit more work to do there, but what's next is we look forward, what are the challenges customers have. They live in this, you know, heterogeneous multicloud world. What do we have to do as an industry? Where is IBM making sure that they have a leadership position? >> From my perspective, I think really the next big wave of cloud is going to be looking at those enterprise workloads. It's funny, I was just having a conversation with a very big bank in the Netherlands, and they were, of course, a very big Z client, and asking us about the breadth of our cloud strategy and how they can move forward. Really looking at a private cloud strategy helping them modernize, and then looking at which targeted workloads they could move to public cloud is going to be the next frontier. And those 80 percent of workloads that haven't moved. >> An integration is key, and for you guys competitive strategy-wise, you've got a lot of business applications running on IBM's huge customer base. Focus on those. >> Yes. >> And then give them the path to the cloud. The integration piece is where the linchpin is and OSSI secure. >> Enterprise out guys. >> Love encryption, love to follow up more on the secure container thing, I think that's a great topic. We'll follow-up after this show Raj. Thanks for coming on. theCUBE coverage here. I'm John Furrier, Stu Miniman. Live coverage, day four, here live in San Francisco for IBM Think 2019. Stay with us more. Our next guests will be here right after a short break. (upbeat music)

>> Live from San Francisco, it's theCUBE covering IBM Think 2019, brought to you by IBM. >> Hey, welcome back everyone. We're here live at theCUBE in Moscone North in San Francisco, for IBM Think 2019. I'm John Furrier with Stu Miniman, talking to all the top executives, top people here at IBM, getting the scoop on cloud and AI. Our next guest, Jason Gardner, Vice President of Worldwide Sales for Hybrid Cloud at IBM, manages key product, which is part of the IBM Cloud Private, big part of the announcements, big Cloud story here. It's multi-cloud, it's hybrid. Welcome back. >> It's hybrid multi-cloud. Thank you, for having me back. >> CUBE Alumni been on as early, going back as 2012. Now, one big event. >> I can't believe it's been that long. But yeah, I'm happy to be back and I can't believe I've been on theCUBE for so long. >> Talk about your new role, and you had previous roles within IBM dealing with the kind of clients and integration. Your role now is worldwide sales. You're taking this Cloud Private offering, bringing the customers, being as the linchpin for integration. Talk about what you do and some of the engagements you have. >> Yeah, previously, I was really focused in on development and offering management on, point products and how they help clients move to the Cloud. Things such as our Pure Business, our Spare Business, and now I've actually been able to move into a much more horizontal role, where I have the portfolio across the Hybrid Cloud integration side, so everything from our Websphere family, which includes IBM Cloud Private, straight to the integration challenges that that brings as well as our digital business automation portfolio. >> Yeah, I have a personal joy. Stu knows I'm fanatic about Kubernetes, and when I heard Ginni Rometty say Kubernetes twice in a CNBC interview you know it's made it. >> Yes. >> Kubernetes is a big part of cloud native containers, really now has created the connective tissue to make cloud and multi cloud viable. This is a key part of it. I want you to talk about the context of these trends and unpack this Cloud Private offering. Because it's instrumental in seems in the news. >> It is, it is. >> What is it about? >> It is, it really creates that ubiquitous layer I think that we've all been searching for. That next generation of virtualization and connective tissue as you call it. And as you begin to unpack that it really kind of starts with the rise of microservices and the need to be able to pack them very tightly into containers. That's really the birth of Kubernetes, was the ability to orchestrate those containers. So Kubernetes becomes that ubiquitous layer in there. But, IBM Cloud Private takes that and takes it to the next level, right. And, really what it is, it's the services on top of that, the cloud services which enable those containers to work together. And, it is a lot of open source capabilities such as Helm, Prometheus, Kibana and some of those core services that those microservices require in order to be able to run efficiently. >> So, Jason, we know it's a multicloud world. Everybody out there would love to say, oh yes, there's one cloud, I can simplify it. I'd like to get to a nice scalable model that's simple. But, the reality is customers choose lots of different solutions because they have different needs. The Private Cloud piece is not really well understood. I'd love you to take us inside your users. Because they say okay, I'm using Amazon, I'm using Microsoft Business Services. There are certain data things that Google has. IBM has AI and business productivity and database offerings. That Cloud Private, what are the services, what are the use cases, what are the reasons why I'm buying this and being part of my overall portfolio. >> Yeah, Ginni called it Cloud 2.0, right. 1.0 was about lifting shift, it was about cloud native, and that really got us about 20% of the way there. It's at 80%, that's the real challenge, that's really where the complication comes into play. That's really what Private Cloud is about. Because not everybody can be able to take their applications, throw them away, build cloud native, or lift and shift them. If you think of big regulated industries like banking, insurance, healthcare, government. They really need to be able to have that level of security and assurances that they need within there. And, that's really where private cloud comes into play, is those really tough, challenging problems in the industry. >> Yeah, I love that. A trend I've heard from a number of customers, you talk about them getting to containerization and multifactor services, is, step one is, I've got to modernize the platform-- >> Absolutely. >> Then I can modernize the applications on top it. Is that the trend you're seeing? >> Yeah, definitely. We've been building on microservices and modernization, it's a journey right, and it's a journey of discovery I think for a lot of clients out there. And, we'd all love to be able to say, OK this is my platform and now I'm going to work on the applications. But really, sometimes the starting point may be one or the another, and it usually comes in a space of a digital requirement, and so they begin to out modernize the application and then realize, jeez! I need to be able to manage all of this, I need to be able to deploy it all, and that's when the platform comes into play and all the other services, I should say, that come along with it. >> Stu, I think you coined the term Private Cloud. I think wasn't it? >> The true private cloud. >> True private cloud. So the private cloud, again, it's all cloud operations, so I kind of disagree on this whole point about one cloud or multi-cloud. Because I think, yes multi-cloud, but you see people use cloud for workloads, right? So pick the right cloud for the right application. So this basically says, okay, if you want to use Amazon, use Amazon if that's what you want, but if you are going to use 365, maybe use Azure. >> Yep. >> If you are going to use G Suite, use Google. You guys kind of have the business apps nailed down. >> Right. >> So If you're going to use your business apps, maybe IBM. This is your opportunity. >> This is our opportunity. >> Talk about specifically the kinds of apps that you guys will power with your cloud, because multi-cloud certainly makes sense for you guys. It's multi-cloud, you won't that portability and interoperability, but the apps that you're going to power with IBM Cloud. Talk about what they are, how-- >> Yeah, if you look at, from a language perspective over the last, jeez it's been 23 years I think, since the rise of Java, right? And 1995, when the first app servers came out. Those app servers, that is really where ore applications really run on top of. And, it's those core Java applications, that are now needing that facelift, right? They need to be able to be injected with new forms of AI, new types of integrations, new types of personalization of that digital transformation that's driving it, and that's really the core suite, right? And if I look at that core suite in there, and then what do you do to modernize a Java application, and what kind of tools are available to you. How do you then manage, how do you distribute, and how do you scale those applications. It's very important. >> What is the adoption of the private cloud or the Cloud Private product. >> Yeah. >> Talk about some of the trends, how is it being used, be specific on how customers are using it. What are some of the use cases? >> Yeah, so the primary use case is to increase the agility, lower cost on the overall managing of them. But it's the increase in the agility, which is really hard to measure. Because clients want to be able to react very fast to it. And so as they build up microservices, microservices then become independent with one another. You can then update ones, very quickly and easily. They manage and they run independently, and they scale independently, and so Cloud Private provides you with all those services to able to run those microservices as containers, but then be able to tie them together in a much more comprehensive enterprise suite. You know, a core technology like Helm, I'm waiting for Ginni to say that one on stage. But a core technology like Helm, really provides that robust, enterprise class distribution for scalability and high availability of a microservice based application. >> Jason, can you bring us inside the organization of the customers your selling to? It used to be, it was the refresh cycle. It's like OK, my X86 refresh, or you know, the budget cycles that I had. Cloud is quite a bit different. >> It is. >> Private Cloud is kind of straddling between the old world and the new world. What are the dynamics you're seeing as to who controls the purse strings? Are they moving faster to that opex model. >> You know, there's no one person who owns the purse strings on it, but it does float between the infrastructure team, knows that they need to do something different, the developers or the application development team, and really the strategy, the Chief Strategy Officer, in that IT organization is really where it's coming together. Because one thing I think that we've all learned is that developers will find the easiest, fastest way to do something. No matter what rules or policies we put down. And this is about providing them with an environment that has guardrails, for them to be able to innovate as fast as they want, use the tools that they want, that their most comfortable with. Really, it's a grass roots kind of movement into these microservices, led by the developers. But the purse strings are still held at the CTO side. >> That's always a fascinating interest, because the developers they're going to go do it, but they're not usually the ones with the budget. >> That's right. >> But when do the ops people get involved, the business people, to make sure that IT manages it, gets rid of like stealth IT? >> And a lot of clients have learned to listen to the developers, because the early days of cloud, they didn't, and developers found ways through it, no matter what. And so that's really what it's about. It's like a game of bumper cars, right? You got to make sure they stay within the ring of what's safe. And, especially in this day and age of the security requirements that are out there, it's more important today than ever before. >> Jason, can you share some data around some observations that you've noticed on trends around industry uptake or is there any patterns in terms of the customer base? Obviously, people aren't going to going to cloud operations. Just, Ginni mentioned 60/40, 80/20, the ratios. What does that all mean? And, just share the trend data around adoption and patterns? >> Probably the biggest onE in there, is the 80/20, right? That there's still 80% of the applications left in the world are still locked behind the brick and mortar. That's probably our biggest piece of our opportunity, and providing clients with a way to lift them up and be able to modernize them. I think is where the huge opportunity is. But then looking at where do they land, it's not all going to public cloud, right. So private cloud it's a huge business. I think a lot of us underestimated how large that business really is, and depending on the industry, you'll see 50/50, 60/40, 40/60 split, depending on the regulations within that industry, that country, the geography, of where they really want to go to. And, a lot of our clients are asking us for solutions around that private side, but yet be able to have the flexibility to be able to-- >> So you're seeing friction on the public cloud, mainly that's inherent from either regulatory compliance, or just technical challenges. Is that kind of the vibe? >> That's probably the first one. I think there's still that regulatory requirements of data residency, and how do I get my data to application. I can build all the applications I want in the cloud, but how do I get my data there? How do I synchronize it? My lineage of my data. So they really challenged her on that. But, then on the other side of it, is around the cost, right. And, if you wanted to rebuild all of your applications, as true cloud native, from scratch. It will take you a very long time and be very, very expensive. And so, there's also a cost element and speed. You can modernize something much more quickly, and be able to get it to that same level of service, without having to start over. >> We had Arvind on earlier, yesterday, and I want to get your thoughts on the impact of the Red Hat acquisition news, because if you look at what Open Shift is doing with Cloud Private. Arvind was saying yesterday that, Arvind Krishna, he's like, this is really enabling a lot of the acceleration for the modernization of the new cloud stuff, and keeping the legacy stuff and/or transition out on different timetables. Your thought on that? >> Absolutely right, Open Shift is going to be a critical component for our overall hybrid strategy. I'm very excited about it and really looking forward to it. And, Cloud Private and the services that I talked about, run in Open Shift today. That was part of our partnership agreement. I think that you guys were at, that Arvind talked about at that time. But, it provides the platform, for all of those traditional applications, which we've modernized. And the interesting thing is that we've actually modernized ourselves. We've modernized our middle-ware. We've modernized some of those products that are you know, 10, 20 years old. Everything from WebSphere, to MQ, to BPM. They've all been modernized in that same fashion. >> Yeah, Jason, speaking of modernization. Bring us inside you're sales force a little bit. How do they keep up, and what's the skill set that you're looking for, on your team to sell on this. You know, they need to understand Helm and Kubernetes, and all these microservice architecture, where five years ago, it was a totally different world. >> Absolutely, you know I think that if I look at a, it's not a skill, it's passion, right? It's that never give up type of mentality, I think that we look for, in a sales force and I never give up attitude really provides you with that foundation, for never stop learning, right. If anything that you've guys have noticed here over the last ten years in your guys' journey, is that this industry just changes so repidly, all the time. And, so as a sales force, you can't just acquire skills. You don't go out and hire skills. You hire people and you hire passion, and you hire people with that never give up attitude. I've been going around. We've been doing our sales kick-offs. I've done two out of the three now, so far. I tell you they are energized. They love it. They are energized about the Red Hat Acquisition. It shows that IBM really gets it. They've been telling me, does IBM really get it? And now they're like wow, we really do get it? And, they're really energized, because all of the pieces are falling into place, around this modernization, and clients, and we're hitting the timeing. >> It's time to hit that pedal to the metal, put the gas on-- >> They always say, there's no speed limit on sales. >> (laughs) Exactly. OK, first of all great, great conversation, and thanks for waiting out our journey. Stu, I would say that the salespeople got to watch all theCube videos, because all of the best content is coming out of theCube here, and great to have you on. But, quick plug, I'll give you the last word. What's the pitch, share the pitch for the Hybrid Cloud, what your team is offering? What's the, the core pitch for your customers, when you go to them? >> I think the core pitch is around modernization. It's the journey that clients are on, from application development, to how you build your apps, and how you build the microservices. How you integrate those applications, what's your API strategy, how do you move that data around securely, and then how do you manage all of those pieces together in that new modern world. And then, really looking your overall processes, and can you modernize your overall processes, add AI capabilities into that. So, it's that modernization journey. That's really what I talk to them about, and you don't have to do everything, right? Start small, start as a pinpointed piece, and we'll help you along that journey. And it becomes a journey of self-discovery, but we're there the whole way. We're a partner, that's really what it's about. >> Jason Gardner, Vice President of Worldwide Sales with Hybrid Cloud at IBM. TheCube, bringing all the data here, from IBM Think 2019. This is day three, of four days of coverage, here in Moscone live in San Francisco. We'll be right back with more, after this short break. (upbeat music)

>> Live from San Francisco. It's the cube covering IBM thing twenty nineteen brought to you by IBM. >> Welcome back to the Cube here in Mosconi North at IBM. Think twenty nineteen. I'm stupid. And my CLO host for the segment is Day Volante. We have four days, a water wall. Coverage of this big show happened. Welcome back to the program. Jason McGee, who is an IBM fellow, and he's the vice president. CTO of Cloud Platform at IBM. Jason, Great to see a >> guy to have fair. >> All right, So, Jason, we spoke with you at Que Con Way. We're saying it's a slightly different audience. A little bit bigger here. Not as many hoodies and jeans and T shirts a little bit more of a business crowd were still talking about clouds. So let's talk about your kind of your role here at the show. What's gonna keep you busy all week? >> S o? I mean, obviously, cloud is a huge part of what's going on. I think talking a lot about both public and private, about hybrid and some are multi called management capabilities. You know, my role as the leader called Platform. I'm talking a lot about platform as a service and communities and containers in the studio and kind of all the new technologies that people are using to help build the next generation of applications. >> All right, so we've had a few interviews today already talk about some of the multi cloud pieces. We had Sandberg on alien talk about eternity. So first you're gonna help correct the things that he got >> anything. Gang >> and service measures have been a really hot conversation the last year or so SDO envoy and the like t talk to us about where IBM fits into this discussion of service meshes. >> Yeah, so you know, I think >> we've been on this kind of journey as an industry of last year's to build anew at platform on DH service meshes kind of fit the part of the problem, which is, How does everything talk to each other and how to actually control that and get visibility into it? You know, IBM has had a founding role in that project. My team at IBM and Google got together with the guys, a lift to create it. Theo, what I'm most excited about, I think a twenty nineteen is that's that technology is really transitioning into something people are using in production and their applications. It's becoming more of kind of the default stack that people are using Really helping them do security invisibility control over their applications? >> Yeah. What? One thing that I heard just from the community and wonder if you could tell me is, you know, is dio itself. The governance model is still not fully into CNC s. Yeah, I heard a little bit, hasn't he? On some envoy? Of course. Out there in the like. So, you know, where are we? What needs to happen to kind of >> move forward? Yeah, you're right. So we're not there quite yet. We're pushing hard to make that happen. Certainly. From an IBM perspective, we absolutely believe that CNC F is the right home for Osteo as you mentioned some of the pieces like Envoy or they're ready. You know, C N c f has done such a tremendous job over the last eighteen months. Really rallying all the core technologies that make up this new coordinate A platform that we're building on costo is no out there's one. Oh, it's been sure people are using it. You know, that last step needs to happen to get into the community. >> So I have to ask you So things move so fast in this world, you go back to the open stack days, and that was going to change the world. And then Dakar Containers. And then Cooper netease, usto I can't help but thinking, Okay, This isn't the end of the line. What's Jason? What's the underlying trend here that's going on in the coding world? Yeah, sure. I'll put it in, maybe in >> my own lens. Given my history, you nominal WebSphere app server guy. You know that in the first half of my career I built that Andi, >> I think the fundamental >> problem solving is actually exactly the same. It's like, how do you build a platform that's app developers focus on building their APS, and I'll focus on all the plumbing and the infrastructure for running those aps. We did that twenty years ago in Java with APP servers, and we're doing it now with cloud, and we're doing it on top of containers. Things like usto like, while they're important in their own right there really actually Mohr important because they're just part of this bigger puzzle that we're putting together. And I think for the average suffer developer, they shouldn't really have to care about. What part of this deal will part is is Cuban eighties. And which part is K native like all that needs to come together into a single platform that they can use to build their APS and run them security. Right? And and I think it's Seo is just recognizing that next piece. You know, I think we've all agreed on containers and communities. We all talk about it all the time, and it's tio Is that next layer I catalyze securing >> control things. Yeah. So you teed it up nicely because we want out. Developers just be able to worry about the application. So you mentioned K native. The whole server list trend is one where you know the idea, of course, is I shouldn't have to worry about the infrastructure layer it just be taking care of me. We've talked about it for pass for a number of years. There are various ways to do it. So at, uh, Cube Colin and we've been looking for about the last year. Now you know, Where does you No, Crew, Burnett, ease and surveillance. How do they fit together? And K Native looks to be a pieces. Toe bridge. Some of those barrels? Absolutely. Where are we and what? What? What's? What's IBM doing there? >> So I think >> you rightly say that they should fit together like they're all part of this continuum of how developers build APS. And, you know, if you look at server, less applications, you know, there's the servos to mention I'm personally not a big service terminology fan. I think they're Maura about event oriented computing. And how do you have a good model for event oriented systems today? With Cuba Netease, anise Teo, I think we've built the base platform, I think, with a native what we're doing is bringing server lists and also just kind of twelve factor applications into the fold in a more formal way on when we get all those pieces together and we integrate them. I think then developers really unleashed to just build their application, whatever way it makes the most sense for what they're doing. And some things like server lists of Anna Marie. And it's going to be easier. And some problems. Straight containers will be an easier way to do >> it. You know, you say you don't like survivalists you like event better a function. So so explain that to the audience, like Why? Why should we care? And why is that different? How is that different? Yeah, I think, for >> a couple things. First off, the idea of server lists applies much more broadly than just what we think of this kind of function based program. You know, like any system that does a good job of managing and masking the infrastructure below me, you could consider a surveillance system, right? So when you just say server Lis, it's kind of like secondhand for functions. I'd rather we just kind of say, functions because that's actually a different programming model where you kind of trigger off of events and you write a functional piece of code and the system takes care of those details. You could argue that caught foundries, a server list system in the sense that you just as a developer anyway, you just see if push your code and it just runs and its scales and it does whatever you need, right? So part of my mission, you know, part of what I look at a lot is how do we bring all these things together in a way that is easy for the developer to stay focused. It steals a great example. You know, one of things were announcing this week is managed osteo support as part of our community service. What does that really mean? It means the developer can use the capability Viste without worrying about How do I install in Rennes D'oh, which they don't really care about? They just really care about how they get value out of its capability. >> Yeah, that's one of the things that having watched all these crew Benetti system and the like is how many companies really need to understand how to build this and run that because can I just get it delivered to me as a service? And therefore that you know that whole you know what I want out of cloud? I want a simple model to be able to consume, Not necessarily. I want to build the stuff that's important to me and not the rest of you. >> And I think if you look at the industry, there's really, I think, kind of two dominant consumption models that have actually emerged for people really using these things, there's public cloud platforms you're delivering things as a service. And then there's kind of platform software stacks like open shifts like I've been called private, which take all of these pieces and bring them together. And I think for most developers, they'll consume in one of those two ways because they don't really want the task of how to assemble all these pieces together. >> Tio, go back to the service piece like what? One distinction I heard made is okay. If I can really scale it down to zero, if I don't need to make it, then that can be serve a list. But there there's alternatives coming out there like what K native has. If I want to run this in my own environment, it's not turbulence because I do need toe. It might be functions, but I need to manage this environment. The infrastructure is my responsibility, not some >> service provider, right? And I think if you'll get server list to me, I was personally, I always think of it in kind of two scenarios. There's like surveillance as ah program remodel in a technology and surveillance as a business model, right? As a consumption model for payment. I think this programming model parts applicable in lots of cases, including private clouds. And in Custer, the business model parties, I think, frankly, unique to public. I'll thing that says I can just pay for the milliseconds of CPU, Compute that amusing and nothing more. >> That's a good thing for consumers. For >> the consumer, it's actually good thing for cloud providers because it gives us a way Tio reuse our infrastructure and creative ways, Right? But I think first and foremost, we have to get Mohr adoption of it as a programming model that developers used to build their applications and do it combined with other things. Because I think most realistic APs aren't gonna all be cirrhosis or all B Cooper nineties. They're going to be something. >> Yeah, right. It's like everything else. It's it's you know, what percent into the applications? Will this takeover? We had this discussion with virtual ization. We've been having this discussion with cloud and certain list, of course, is is pretty early in that environment. K native did I hear is there's some announcement this week that IBM >> so Soak a native, obviously is a project is kind of much earlier in its maturation and something like Castillo is. But we're making that available as part of our Republican private cards as well, Really? So people can get started with the ideas of K native. They can have an easy way to get that environment stood up, and they can start building those applications on DSO. That's now something that, you know, we're kind of bringing out as we work in the community to actually mature the project itself. >> Excellent. One of the things everybody's, of course, keeping an eye on. I saw Arvin Christian talking about the clouds. Tragedy is how red hat fits into all this. So we know you can't talk about kind of post acquisition. But red hats involved in K native. They're involved in a lot of the >> services and developers you gotta be exciting for. Yeah, >> it is. And obviously, like, Look, we've been partners for many years, you know, in on the open source side of things. We've worked closely with Red Hat for a long time. We actually view the world in very similar ways. You know, like you said, we're working on a native together. We've been working on Open West Feather. We obviously work in Cuban eighties together. So personally, I'm pretty excited about them coming in IBM. Assuming that acquisition goes through, they, you know, they fit into our strategy really well. And I think we'll just kind of enhance what we've all been working to build. >> All right, Jason, what else? What's looking? You talk about the maturity of these solutions, give us, um, guide post for the people watching the industry that we should be looking at as twenty nineteen rolls through >> us. So I think there's a >> couple things that, you know, I think this unified application platform notion that we've been kind of touching on here, I think will really come into its own in twenty nineteen. And and I would really love to see people kind of embraced that idea that we don't need. Three container stacks were not tryingto build these seven things. You know, one of things I'm kind of excited about with a native is by bringing server lists and twelve factor into Cuba Netease. It allows each of those frameworks to be kind of the best they can be at their part of the problem space and not solved unrelated problems. You know, I looked at the kind of server less versus coop camps, you know, the purest. And both think all problems will be solved in their camp. Which means they tried to solve all problems. Like, how do I do state full systems and server, Wes. And how do I bring in storage and solve all these things that maybe containers is better at. So I think this unification that I see happening will allow us to have really high efficiency, twelve factor and surveillance in the context of Koob and will change how people are able to use these platforms. I think twenty nineteen is really about adoption of all of this stuff. You know, we still are really early, frankly, in the kind of container adoption landscape, and I think most people in the broader industry or just kind of getting their feet wet they all agree that they're all trying, but they're just starting, and he knows a lot of interesting work. >> Jason, are there any anything that air holding people back? Anything that you You know what? What do you see is some of the things that might help accelerate some of this adoption? >> Yeah, I think one of the things that's >> holding people back is just the diversity of options that exists in the cognitive space means you guys have all probably rising like the C in C F landscape chart. I've never seen so many icons on something in my life. That's really frightening for the average enterprise. To look at a picture like that and go like which of these things are going to be useful, which are going to exist in a year like how Doe, I bet, make that sort >> of those things. So I think that's actually >> help people back a lot. I think that kind of agreement around communities that happened in the last eighteen months or so was really liberating, for a lot of people have helped them kind of move forward there. I think if we can all agree on a few more pieces around this deal, reckon native like it'll really help kind of unlock people and get them trying actually doing it. And I don't think it's anything more than picking a project and starting. I think a lot of enterprises over analyze everything, and they just need to pick something and go and learn. And they'll >> so pick some narrow use case pick, pick an app, pick >> a use case and go do it right and you'll learn and you'll figure out how it works for you. And then you do the second and the fourth in the tenth. And before you know it, you're on your way. That's what we did at IBM ourselves, and you know, now we're running our whole entire public out on top of communities. >> Jason and any any warnings from that kind of experience that you trade to users? A CZ. They looked forward. >> Yeah, we had a >> lot of learnings from music. One is we could run a heck of a lot more diverse work less than we thought when we started. You know, we're running databases where any data warehouses, running machine learning. We're running Blockchain. We're running every kind of application you didn't think could ever work on containers on containers s so one of the lessons Wass. It's much more flexible than you think. It isthe right. The >> other thing is you >> really have to rethink everything. Like the way you do compliance, the way you do security, the way you monitor the system. Like all of those things I need to change because the underlying kind of container system enables you to solve them in such a powerful way. And so if you go into it just thinking, Oh, I'm just going to change this one part of how I do aps and the rest will change. I think you'll find in a year that you're changing the whole operating model around your environment. >> Well, Jason, rethink everything we're here at IBM. Thing up twenty nineteen. Thinks is always for catching up with Thanks for everything going on for David. Want a, um, stew? Minutemen got three more days of live coverage here for Mosconi North. If you hear, stop by and say hi or reach out to us on the interwebs. Thanks so much for watching the cues.

>> Live from Seattle, Washington it's theCUBE covering KubeCon and CloudNativeCon North America 2018 brought to you by Red Hat the Cloud Native Computing Foundation and it's Ecosystem Partners. >> Well, everyone welcome back to theCube's live coverage here in Seattle for KubeCon and CloudNativeCon 2018. I'm John Furrier with Stu Miniman. Three days of coverage around the Cloud Native growth, around the Ecosystem around open source, and the role of micro servers in the cloud. Our next guest is Roland Barcia who's the IBM Distinguished Engineer for IBM's Hybrid Cloud. Welcome to theCube. >> Thank you, glad to be here. >> Thanks for joining us. Being a Distinguished Engineer of IBM is a pretty big honor so congratulations. >> Thank you. >> it means you got technical chops so we can get down and dirty if we want to. >> Sure. >> I want to get your take on this because a lot of companies in IT are transforming and then that's been called digital transformation, it's happening and cloud has developed scale. And the wish list if you had the magic wand that could make things do better is actually happening. Supernetting's actually creating some goodness that if you had the magic wand, if I asked that question three years ago, if you had a magic wand what would an environment look like? Seamless operations around the cloud, so it's kind of happening. How are you guys positioned for this? Talk about the IBM cloud, what you're doing here, and how you see this cloud native market exploding. It's almost 8,000 people here up from 4,000 last year. >> Yeah, that's a great question I think. I work a lot with our enterprise clients. I'm part of what's called the IBM Cloud Garage, so I'm very customer facing. And often times, we're seeing that there is different paces of a journey. And so for example, I worked with a client that started building a cloud native application. They built about 60 micro services. And at the end of that, they were deploying it as one job which means they defeated the whole purpose of micro service architecture. And so what we really need to think about is an end to end journey. I think the developers are probably the more modern role in an enterprise, but we're starting to see modernization of an operations team for example, and adopting culture, and cutting down the walls of IT organizational groups into mixed squads, adopting something like a Spotify model. And I think a lot of the challenges in adopting kubernetes is really in cultural aspects and in enterprise. Does that make sense? >> Yeah. And because network guys are different than the app guys, and now they have policy knobs on kubernetes they can play with. Network guys love policy. >> Yeah, and they're fighting over ownership, right? >> Roland indeed. We look at that modernization, the application modernization really is that long home intent. And what we hear here is you need to be able to meet customers where they are. Sure, there's some stuff they're building shiny and new and have the developers, but enterprises have a lot of application and therefore there's a grand spectrum. What do you hear from customers? What's the easy part and where's the parts they're getting stuck? >> Yeah, so I think the easy part is writing the application. I think where they're getting stuck is really scaling it to the enterprise, doing the operations, doing the DevOps. I always tell people that a modernization journey might be better started by taking a certain class of applications like middleware where we have a WebSphere heritage from IBM, and saying why don't we take a look at containerizing that. We've built tools like Transformation Advisor that'll scan your WebSphere applications and tell you what do you need to change in that middleware application to make it behave well in a containerized platform. Then from there, you build your DevOps engine, your DevOps pipeline and you really start to get your operations teams going in delivering containers, delivering applications as containers. And then getting your policies and your standards in place. Then you can start opening up around innovation and start really driving towards building cloud native new applications in addition to that. >> One of those areas we've been talking about in the industry for decades is automation. The conversation's a little bit different these days. Maybe you can bring us up to speed about what's different than say it was earlier days. >> Yeah, I think IT organizations have always done a bit of automation. I think they write scripts, they automate builds. I think the mantra that I use is automate everything, right? Organizations need to really start to automate in a new way. How I deliver containers, but delivering the app is not enough. I need to automate all levels of testing in a modern way. Test driven development is big. At the IBM Cloud Garage, we have something we call the IBM Cloud Garage Method which really takes a set of practices like test driven development, pair programming, things out of lean startup, extreme programming, and really start to help enterprises adopt those practices. So I say why can't we automate end to end performance testing in the pipeline, and functional testing, and writing them early and in the beginning of projects? That way, as I'm deploying containers which are very dynamic, along with configuration, and along with policy you're testing it continuously. And I think that level of automation is what we need to get to. >> Talk about security as well 'cause security's one of those things where it's got to be baked in upfront. You got to think about it holistically. It's also now being pulled out of IT, it's more of a board function because the risk management is one hack you could get crushed. And so you got to have security. And the container there's a security boundary issue, so it's important. >> Last week we met with an insurance company. We did a workshop. And they walked us through all the compliant steps that they need to go through today. How they do it with traditional middleware and virtual machines and hardware and it was a very, what I'm going to say governance driven process. And so a lot of checks and balances, stop don't move forward, which is really the industry for developing and innovating is going the opposite way: self service and enabling. And there's a lot of risk with that. And so what we're really trying to do with technology is like Multicloud Manager, technology we have around multicluster, management is how do I do things like I want to check which clusters are Hipaa compliant and which ones are out. How do i force that policy? >> That's smart. >> Now that everything is software driven, software developed, there's an opportunity to really automate those checks. >> So your point automate everything. >> Yeah, I want to automate everything. >> Governance is a service. (laughing) >> Yeah, that's right. And actually, that can help get away from error prone human checks where they had all these tons of documents of all different policies they have to go through can now be automated in a seamless way. >> So compliance and governance could be a stumbling block or it can be just part of the software. That's what you're getting at here. >> That's right, that's what I'm getting at. I think the transition is look at it as an opportunity now that everything is software driven, use software disciplines that developers are used to in those security roles and those CSO roles, etc. >> So I want to ask you a question. So one of the things we're seeing obviously with the cloud is it's great for certain things, and then on premises it has latency issues. We saw Amazon essentially endorse this by saying RDS on VMware on premises. They announced Outpost had reinvent oh, latency. Things aren't moving into the cloud as fast. So you're going to see this hybrid environment. So hybrids, we get that, it's been around, check. No real discussion other than it's happening. The real trend is multicloud, right? >> That' right. >> And so multicloud is just a modern version of the word multi vendor about the client server days. So systems were a multi vendor man choice. This is a fundamental thing. It's not so much about multicloud as it is about choice. How do you guys see that? You are in an environment where you have a lot of customers who don't have one cloud, so this is a big upcoming trend in 2019. >> Most of our clients have at least five different clouds that they deal with, whether it be an IaaS, a PaaS, a SaaS base solution. What we're seeing as a trend is we talked about on premise and private and enterprise is I think is 80% of workloads are still in the data center. And so they want to build that private cloud environment as a transitionary point to public, but what we're seeing across the multicloud space is I'm going to say a new integration space. So if you really think 15 years ago, SOA and enterprise service bosses in a very centralized fashion, I think there's a new opportunity for integration across clouds and on-prem in a more decentralized way. So I think integration is kind of the next trend that we're seeing in this multicloud space because the new applications that we're seeing with cognitive data AI are mixing data sources from multiple clouds and on-prem and needing to control that in a hybrid control plane is key. >> It's funny, the industry always talks about these buzzwords, multicloud. If we're talkin' about multicloud, then it's a problem. The idea of infrastructure as code it's not even use the word multicloud. I mean, if you think about it, if you're programming the infrastructure and enabling the stuff under the covers, why even talk about cloud? It should be automated, so that's the future state, but in reality, that's kind of what enterprisers are tryin' to think about. >> They are, and I think it's a tension between innovation and moving fast and control, right? The enterprisers want to move fast, but they want to make sure that they don't break security protocol, that they don't break resiliency that they're maybe have used to with their existing customers and applications. I do think the challenge is how operations teams and management teams start to act like developers to get to that point. And I think that's part of the journey. >> Open source obviously a big part of this show, and that's open source, people contribute upstream It's great stuff. IBM is a big contributor, and it'll be even more when Red Hat gets into the mix. So upstream's great, but as you got 8,000 people here, you're startin' to see people talkin' about business issues, and other things. One of the downstream impacts of this conference being so open source centric is the IT equation and then just the classic developer. So you have multiple personas now kind of interacting. You got the developer, you got the IT architect, cloud architect pro whatever, and then you got the open source community members. Melting pot: good, challenges, thoughts? >> So I think it's so developers love that, right? I think from an enterprise perspective, there are issues. We're seeing a lot of our clients with our private cloud platform ask us to build out what's called air gapped environment which is how do I build up an open source style ecosystem within my enterprise. So things like getting an artifactory registry or a Docker registry or whatever type of registry where I get certified, open source packages in my enterprise that I've gone and done security vulnerability scans with, or that I've made sure that I look at every layer from the Linux kernel all the way up to whatever software is included. So what we're seeing is how do I open the aperture a bit, but do it in a more responsible fashion I think is the key. >> Yeah, and that's for stability, right? So Stu, one of things I've been talkin' about and want to get your thoughts on this role is that you got the cloud as a scalable system then one of the things that's being discussed in Silicon Valley now for the first time, we've been sitting on theCube for years, is the cloud's a system. It's just some architecture, it's network distributing, computing, art paradigm, all that computer science has been around for awhile, right? >> Yes, yes. >> So if you've been a systems person whether hardware or whatever, operating systems, you get cloud. But also you got the horizontal specialism of applications that are using machine learning and data and applications which is unique on top. So you have the collision of those two worlds. This is kind of a modern version of two worlds that we used to call systems and apps, but they're happening in a real dynamic way. What's your thoughts on this? Because you got the benefits of horizontally scalable cloud and you now have the ability to power that so we're seeing things like AI, which has been around for a long, long time, have a renaissance because now you got a lot of compute. >> That's right, and I think data is the real big challenge we're seeing with a lot of our clients. They have a lot of it in their enterprise, they don't want to unlock it all right away. We recently did what's called IBM Cloud Private for Data, in which we brought in a set of technologies around our AI, our Watson core to really start leveraging some of those tools in a private manner. And then what we're seeing is a lot of applications that are moving to the cloud have a data drag. It might start as something as simple as caching data and no SQL databases, but very quickly they want to learn a lot more about that data. So we're seeing that mix happening all the time. >> We've had it, we've had someone say in theCube ML's the new SQL. >> Yeah. >> Because you're starting to see SQL abstraction layers are a beautiful thing if they're connected. So I want to get your thoughts on this because everyone's kind of in discovery mode right now. Learning, there's a lot of education. I mean, we're talkin' about real, big time players. Architects are becoming cloud architects. Sysadmins are becoming operators for large infrastructure scale. You see network guys goin' wait a minute, if I don't get on the new network programmable model I'm going to be irrelevant. So a lot of persona changes in the enterprise. How are you guys handling that with customers? I know you guys have the expert program. Comment on that dynamic. >> I think what we're doing is we use the IBM Cloud Garage to bring in practices like the Spotify method where we start pushing things like >> What's the Spotify method? >> Spotify method is a way of doing kind of development where rather than having your disciplines of architects, development, operations, we're now splitting teams, let's say functionally, where I have mixed disciplines in a squad and maybe saying hey, the person building the account team has an SRE, an ops guy, a dev guy all within their same squad. And then maybe have guilds across disciplines, right? And so what we do at the Garage is we bring 'em in to one of the Garages. We have four team locations worldwide. Maybe do your first project. Then we build enablement and education around that, bring it back to the enterprise and start making that viral. And that's what we're doing in the IBM Cloud Garage. >> So not a monolithic thing, breakin' it down, integrating multiple disciplines, kind of like a playlist. >> Yeah, that's right. And I think the best way to do it is to practice it, right, in action. Let's pick a project rather than talking about it. >> If I had to ask you in 2019, what is the IT investment going to look like with kubernetes impact? How does kubernetes change the IT priorities and investments for an enterprise? >> Yeah, so I think you'll see kubernetes become a vehicle for enterprises to deliver content. So one, the whole area around helm and other package managers as a way to bundle software. I think as people build more clusters, multicluster management is going to be the big trend of how do I deal now with clusters that I have in public cloud and private cloud, all different clouds? And I think that integration layer that I talked about where what does modern integration look like across kubernetes based applications. >> Someone asked me last week at Reinvent hey, can't we just automate kubernetes? And then I was like, well it's kind of automated now. What's your thoughts on that? >> So I think when someone asks a question what does it mean to automate that I think the kubernetes stack really sits on top of IaaS infrastructure. And so for example, our IBM Cloud Private you can run it on zLinux or Power. And we have a lot of IBM folks that run multi architecture clusters. And therefore, they still need a level of automating how I create clusters over IaaS and there's technologies like Terraform and others that help with that, but then there's also automating standing up the DevOps stack, automating deployment of the applications over that stack. And I think they mean automating how I use kubernetes in an environment. >> So 2019, the year of programmability and automation creating goodness around kubernetes. >> Yeah, absolutely, >> Roland, thanks for comin' >> Thank you, it was great. >> on theCube, thanks for that smart insight. TheCube coverage here, day two winding down. We got day three tomorrow. This is theCube covering KubeCon and CloudNativeCon 2018. We'll be right back with more day two coverage after this short break. (happy electronic music)

>> Live from Seattle, Washington, it's theCUBE, covering KubeCon and Cloud Native Con North America 2018 brought to you by Red Hat, the Cloud Native Computing Foundation and it's ecosystem partners. >> Hey welcome back everyone, we are live here in Seattle. It's theCUBE's coverage of KubeCon, Cloud Native Con, a part of CNCF, Cloud Native Computing Foundation, the rise of Kubernetes, this is what the show is all about. Three days of wall to wall coverage. We've been there from the beginning covering this KubeCon effort from the beginning. I'm John Furrier with Stu Miniman, we're here to analyze and break down the event with our guest analyst for the segment, Steve Herrod, CUBE alumni, he was there the first day we ever did theCUBE in 2010. He's been a good friend of theCUBE. Now he's a venture capitalist, managing director at General Catalyst, a premiere VC in the industry. Steve, great to see you. >> Good to be here. >> Thanks for coming on. >> Feels like the early days of some of the other conferences, too, doesn't it? >> It feels like AWS, you know seven/eight years ago where it tips over, there's a tipping point. We see that doubling, so you know, it's kind of that tipping point where there's more demand for theCUBE and we can fill it so there's great content but it's a bigger picture, right? And I want to break through that, I want to get your thoughts and let's have a shared conversation around what's really going on here. You're talking about a disruption in the industry of cloud computing. You got Amazon, just a freight train just taking all the beach, the waves coming in and this is an opportunity, this is my opinion, for the industry to kind of say, hey, it's a multi cloud world so you're not going to take all of it. You got Google, you got Microsoft, you got start ups. This is a way to create an opensource way to fill the gap. Your thoughts? You agree? >> I totally agree and I think what's interesting, this conference does not have a corporate, at least an explicit corporate sponsor. It has four or five that are all trying to have their play in it. Microsoft's not one of them, which is sort of interesting. But it was, I think, a very bold thing this year to have this big of a venue and invite this many people and then hope that you're going to get the sponsorships and all the other stuff that follows. >> In Seattle. >> In Seattle. Yeah, our weather is a little bit-- >> It's very meta. (laughing) >> Interesting. But, just to your point, I do think this is really interesting because it is more open than a lot of these conferences where people are coming together. Both open source but also so much focus on how do you do functions in a way that works across places, how do you service meshes. Like everything is, it's both good and bad because there's so many choices that people are being seen right now. >> You were the CTO of VMware, Stu you worked in the CTO office at EMC back in the day, you're seeing a systems kind of vibe going on in cloud and you got application renaissance, kind of almost like the app server days, think WebSphere or whatever, that movement in the 90's and 2000's, that kind of grew quickly, all kind of being modernized. So you have cloud scale. >> Mm-hmm. >> AI has been around for a long time but because of the cloud, there's a renaissance. Video's been around for a long time but because of the cloud, things like theCUBE is happening. So the cloud is enabling a rebirth of a lot of things. >> Mm-hmm. >> And enabling a lot of new things, how do you guys view that systems view, application renaissance? Jassy talks about a reinvent as a new kind of persona developing. >> Mm-hmm. >> As a buyer and IT investments are changing, you're making start up investments, it's crazy. >> Yep. >> What do you think? >> Yeah, so first of all John, I like what you're saying about that systems view because too often we would kind of focus on a specific tool. So virtualization was great, but, you know, big thing, I took a bunch of servers and made it smaller servers but I took the same old application and I shoved it in there, and I left it running for another five or 10 years when I probably should have modernized it. Today, you know we just had Cheryl on talking about the ecosystem and customers and what I want to focus on is how the users get value. What are building on top of this? >> Right. >> Not the next cool thing to build, but how do I run my business? How do I do cool things with genomics? How do I improve healthcare? And in many ways we're seeing some of these top down things. I mean what's gotten me so excited about things like serverless and been really poking and teasing at how that fits in with this ecosystem is it's not just about a way to kind of turn the crank on making things a little bit more efficient or, you know, I can manage more machines with fewer people, but you know it moves up things and for someone like myself, a networking guy with an infrastructure background? >> Right. >> It's a little out of my comfort zone and that's okay. You know we talked to Lou Tucker, Lou's really excited about where AI's going and what's there, so I think we're in a real renaissance here and it's a big inflection point. >> Well I think to your point, what's interesting, whenever I do a teacher course to a college or when I'm talking to start ups or even in the old days it's really easy to forget that infrastructure is not a thing in it's own right. It's solely there to enable applications and to enable other things and so whenever you get really deep in the weeds on this is a new security model for this type of container or this, it's important and you're thinking about the best way to do it but, really you're right, you have to abstract it out to can I ship value faster? Can I save customers money? Can I do something safer? You really have to think about it in that context. And there's so much activity here you have to really make sure you're thinking about where it all fits together. >> And you know, the computer science conversations changes, too. The nature of what is computer science is evolving. I want to get to that in the next kind of discussion point but I want to just, Steve, ask you, you were on the VMware side when VMware kind of entered in with virtualization. It was a desktop, it was an app, it was like you loaded it on a machine and then that ended up transforming a massive industry and so a lot of people compare what VMware did in it's growth and it's impact but saying the cloud has got certainly more orders of magnitude, you mentioned security. >> Mm-hmm. >> Where's the VMware moment in this cloud transformation impact? Your thoughts there, just because you've been on both sides, one as a driver, CTO at VMware and now as an investor. Where do you see cloud-- >> Yeah, I kind of thought of it as two different angles. One is, appealing to developers and then that taking you all the way through operations which is, I mean that is, dev ops is sort of looking at that. VMware's first product was a workstation product that made developers have a bunch of environments right in front of them and we always had a vision for getting into the operations center but we knew we had to kind of come up through that path and I think likewise, a lot of this tooling that we see here is developer first and it's them saying, "I like this tool "and I can make my job be more enjoyable this way." But what you're really seeing, especially at this one is, how do you start in the developer tools and then not be detested by developers but then actually be paid for it by the operations side. So if you look at the type of vendors that are here? You start having venture capitalists here. You have a few people wearing suits here. It is about making this more enterprisey, more production ready and that's kind of the natural progression of any major impact like this. >> And Heptio, certainly Stu was reporting earlier, the number has been better than the filing of VMware. You know, a half a billion dollar acquisition for talent and a position in the marketplace. There's liquidity so there's investment opportunities. We talked to Jerry Chan about this at AWS, I want to get your thoughts, how is the investment thesis going on because what are you investing in? The notion of a stack, has kind of transformed into Lego blocks and services. >> Yep. >> So the notion of a stack is kind of changing although I've heard people say the, "Kubernetes stack." I'm like, well, what does that mean? (laughing) >> Which one? Yeah. >> So there's a lot of kind of stack derivatives. >> Mm-hmm. >> But how do you invest in this? What are you looking for? Where is the value? >> Yep. >> Where are sniffing out the deals? Where's the white spaces? And where should entrepreneurs go? >> Yeah, and I have several companies presenting here so I've certainly done some investments around this space, but I focus on a few things very specifically. I've been around this a little while. I really like to think about not tools that go to the new, hot new companies. I really try to think about what is more mainstream company going to adopt? And that usually means a few things. It has to have enterprise capabilities. It has to fit into the rest of the things. But I look at like how are you going to digest this with your other tools and the other processes that you have in place? If it's a security solution, I look at, I don't want really something that only protects the brave new world, I want it to fit in somehow with security policies and other things that are happening. >> So mainstream adoption? IT kind of impact? >> Yeah, just like a tool that actually works across environments and lets you go from here to there. You all have talked to Illumio several times? >> Yeah. >> They're trying to do micro segmentation for physical machines all the way through containers. The other thing I'm keeping a close eye on is, this is chaos, in terms of the number of start ups doing very specific point solutions and you have to really think about how does that grow into a big enough chunk of a budget or a big enough problem. So every single time I make an investment, I ask how does this do something 10 times better than something else and is that important to the company? And that's really hard to answer sometimes. >> Steve, and what's your take on the kind of opensource, open core, business model today? To be honest, I go around, I talked to some of the founders there, and everybody wants to contribute to opensource but maybe I don't want to build a business around it, because actually monetizing that is really tough. Is it just, I look to get acquired by one of the big players here? Or can I actually build a business with opensource at it's core? >> That's literally the billion dollar question. >> Yeah. >> But I do think, like on the positive side, the number of exits or big things recently with Magento, with Cloudera doing great, with, obviously, Red Hat, but we've seen, and Neilsoft, like a lot of big acquisitions and some good IPOs. But on the flip side, you definitely have to think about it differently now. There's a growing license that is very careful about allowing clouds to host your opensource project without contributing back. Hopefully that'll allow this hosted model to play out. I personally, I certainly look to opensource. You can see what's going on from traction but when you see it as a great lead generation engine which it often is for folks, I think that's a really healthy way to avoid spending a bunch of marketing money. >> Yeah, it's been fun. A lot of different shows we go to. Love your analysis, thanks for coming on, appreciate it. Just in general, as not a VC, but as a tech person and in the industry, I want to ask you and Stu what wave are we on? Obviously Kubernetes is now kind of front and center but we've still got cloud native. Is it the cloud? You got IoT and Amazon ARM, but we saw a lot of conversations around Edge. They had some interesting announcements around satellite telemetry coming in to regions. So you got Google, you got Microsoft, you got the big players. Is it the rich get richer? Is there going to be a new second tier? Cloud service provider? Where is this going? How is it going to reshape the industry? I mean, just big picture, what's your thoughts? >> Well, this is literally what I get paid to do is figure out where things are headed. I'd say, just at a top level, this is a super fun time to be in this lower level of the stack. You mentioned already AI gets, sort of AI washing goes on a lot right now but the very core of it is literally changing every application in interesting ways. And for me, I was a former hardware designer. The fact that you can now build and have really cool new hardware that's accelerating this stuff is really exciting. You saw Amazon's announcements, not only an ARM based server but Inferentia chips. Google has been doing this with TPUs-- >> Hundred gig networking in there, like, you know, high speed-- >> It is impressive. >> Cluster configurations, it's amazing stuff. >> So I love the fact that we can actually have very big innovation at each stage of the stack and it's because the combination of every company becoming an app, digital company coupled with the power of AI to transform things means you need dev ops to faster, you need these platforms that let you do more self service. And then I sprinkle on top of that is just the ridiculous demand for high quality engineers and if you don't give them an environment where they feel productive, they're just not going to stay at your company. And so all the mix comes together. I don't think they're going to be, there'll be some giant companies that already are, but I think the ability to create a new company that becomes large quickly or becomes small quickly if you screw up is bigger than ever. >> Yeah, I think it's total acceleration. >> Everything's faster. >> Values accelerated but it's also failure, too, right? >> Exactly, everything is accelerated. >> You have an option to abandon in you NPV calculations and IRRS (laughing) in your portfolio. >> Exactly, no it's-- >> The word pivot comes to mind. >> Everything is faster, that's the right way to think about it. >> Stu what's your take on this? >> Yeah, so we're at an interesting point in the industry. It's a bit of a paradox. On the one hand, the challenge of our time, we've been talking on theCUBE since the early days, John, is it's about distributed architectures and we're decomposing all of the pieces. Even Kubernetes itself, we're going to talk about how it's decomposing. On the other hand, everything is consolidating. >> That's right. >> I've seen more vertical stack integration from the chip and hardware level all the way through. You see Apple, Microsoft, Google-- >> That's right. >> And Amazon, all have chips companies and are going really interesting stuff there but it is such a complex individual. >> It is. >> That no one company can do it all, so there is opportunity for people to build on top of that. We have new marketplaces, we have new ways of doing it so it's, yes, there's going to be some really big winners and we have seen changes but there are still opportunities and yeah, John, keeps us busy always. >> Well here's my take on it, I want to get you guys' reaction to my view on this. So obviously we're in the media business, we're disrupting media with theCUBE so we look at the market and it's kind of matched the music industry. The power curve, the power law is very flat and straight and then a very long tail, with the head of the power law is the big players. But then when media came out, it kind of created a fatter tail and a bigger torso. I think that I see in the cloud, I see the rich getting richer. Amazon, Google, Microsoft, Alibaba, and maybe a couple players underneath there, IBM, Oracle, those big guys. And then it's going to be a second tier of cloud service providers. Someone who's going to package all these awesome sets of features in the long tail so you're going to start to see a growth because the big guys cannot be winning all the mid range business. I think, you're right, I think there's going to be a lot of solutions that are just exceptional. >> Mm-hmm. >> And I think the scale of the cloud is going to create an opportunity for new kinds of service providers. Someone who says, hey, you know what? I'm going to package this differently. I'm going to assemble-- >> I think so. >> A cloud solution, on either one of all of the clouds. Why wouldn't I use the accelerated Amazon, or the power of Google? >> I think that's well thought and I do think, we've talked about this for a while too, but I do believe there's going to be specialization by industry where you have certain algorithms and data that's unique to it, by geography. There's still going to be sovereignty issues. Even by just what type of things am I trying to build. So I do think simultaneously there's commonality on the platform but that allows you to do specialization and to really serve a specific industry quite well. >> And machine learning is a great specialty thing. The metadata to power machine learning. >> So Steve, do you have final questions you want to ask us before we run out of time? >> Well I would just say, you see a lot of these conferences. I actually like to show up at these and say, what in point time does this look like the AWS reinvent. For me, what point in time does this look like maybe the VMware event in my case, but I don't know, it just feels to me like we've jumped over, we're sort of at that point where this is going to keep going and growing. >> Yeah, how do we make sure we've hit the inflection point but not jumped the charts? >> Yeah, I mean, do you think we are here? And how does this feel versus some of the other events that you spend time on? >> Yeah, I mean, John you want me to? >> I mean, you know. >> So my take, first of all, is there's a little worry and there's some concern of us that have been through this before, is like, wait, did we just create another OpenStack? >> Yeah. >> And my resounding answer so far, is no. While there might be 35 main projects here each one of those was started for a reason. They stand on their alone, they have, you know we've got Matt Klein on from Lyft, as our next guest here. >> Yeah. >> You know, Envoy, if Kubernetes didn't exist, Envoy would probably still exist. So there's a lot of these pieces that are good but it is complicated. >> It is very complicated. >> And there's all these pieces but that's a real opportunity for a lot of companies. The SIs, the big platforms, to be able to help put this together. >> Yeah. >> And the customers are thrilled with what is going on. >> That's well stated, yeah. >> There's interesting things there. Right, this ecosystem, the only ecosystem I've seen probably grow faster is the Amazon one so it is doing well and we've been looking for years as to like a nice, vendor independent ecosystem. >> Right. >> To grow because, you know, there's some of the ones in the storage industry and things like that. >> Yeah. >> All died. >> That's right. >> So there are vendor shows and this, you know the Lennox Foundation's done a nice job. >> Right, I agree. >> With it and it's been-- >> That's the unique part here for me. >> We bet early on it, so. >> Well we bet early on it, it was a good bet, but here's the challenge that they have; they have lightning in a bottle and it's definitely arrived so there's a little bit of jump to shark moment. You got some things happening that's kind of glam oriented but absolutely it's arrived. I think the challenge that they have is opensource community is a core constituency of this event, and the Lennox Foundation is structured to be kind of a very tight top, thin at the top period of management and the scale of this event and this movement is too big for them, I think, to handle. I think they either have to have sub brand or start segmenting out because if they lose the opensource community, the they're going to lose the vibe of the event and that's the core of what it is. >> Right. >> The downstream benefits, kind of a an opensource parlance, is the IT impact and the developer impact. And inherent in that is business benefits so you're going to start to see more suits coming in and you're going to start to have a melting pot and that is a risky proposition if they don't get out front on that. So yes, it's arrived, but there's so much time they're going to be doing it just to the projects. >> Right. >> Just to the innovation. >> You're going to have to wear these next time that you see them. >> There's a money making aspect of it, yes. >> Right. >> The money making aspect of this is huge. >> Yeah. >> And I think that's what we're watching. >> Yep. >> As the business people come in and say, look at this, this is billions and billions of dollars. >> Yeah. >> This is-- >> Maybe just one more thought on that. The notion is really important, this is a distributed, not really owned by one person, one company, and there's the chaos that comes with that and so how do you do the balance between these two things? >> Yeah, yeah. >> Its like when, I know, when Amazon announced their Blockchain thing, it's like, Blockchain's supposed to be distributed. Now we have a company running it in one cloud. It's like that balance between the push and pull of centralization that we're going to see. >> Well have to put some computer science architecture together and put an operating system around it. >> There ya go. >> We'll have some dev ops. Steve, thanks for coming on theCUBE, great to have you on. >> Good to see you guys. >> Well it's great to see you. A legend in the industry, Steve Herrod, CUBE alumni from 2010, been on every year. Now a venture capitalist, former CTO of VMware. With Stu Miniman, I'm John Furrier, analyst of KubeCon, stay with us for more coverage after this short break. (upbeat techno music)

>> From Yorktown Heights, New York, it's theCUBE, covering IBM Cloud Innovation Day, brought to you by IBM. >> I'm Peter Burris of Wikibon. Welcome back to IBM Innovation Day, covered by theCUBE, from beautiful Yorktown Heights, New York, Thomas J. Watson Research Center. A lot of great conversations about the journey to the cloud and what it means, and we're going to have another one here with Denis Kennelly, who is the General Manager of Cloud Integration in IBM. Denis, welcome to theCUBE. >> Thank you, Peter, and welcome to Yorktown also. >> I love it here. So, very quickly, what does the GM of Cloud Integration do? >> Yeah, so, I suppose we start from the beginning, right? So I am responsible for a lot of what we call the traditional IBM middleware. So these are brands that are known to the industry and to our customers, things like WebSphere, Message Queue, or MQ, as we know it, which is kind of the core foundation stones for a lot of IT today that's out there in the industry. And it's not just about, you know, sometimes people talk about this legacy, but this is what all the systems run on today. And also, I'm involved in the whole journey of moving that middleware to the cloud and enabling customers to get on that journey to cloud. And it's not just to a cloud, because your typical enterprise today has probably on average about five different clouds, and clouds, as we know them as the IS players of the past, but also when we talk about cloud, we also think about things like SaaS properties and applications of that regard. So it's helping customers go from that traditional IT infrastructure and on their journey to the cloud. That's what I do. >> So utilizing these enterprise-ready technologies that have driven the enterprise, bringing them to the cloud as services, but also making sure that the stuff that's currently installed can engage and integrate the cloud from a management service standpoint as well. >> Absolutely, because customers have made a huge investment in this middleware, and a lot of the transactions, and a lot of the security, and a lot of the risks set in these systems, and they have served us very well for many decades. Now, as we start to move to the cloud, it isn't a binary switch. It's going to be a transition over time, and today, I think we're about 20% into that journey. I would say we've done some of the easier parts. Now we're getting into some of the more complex and some of the more difficult problems. And kind of one of the underlying pieces of technology we're using to enable customers to do that is container technology. So we've made the decision to use containers right across our middleware, our software. So what I mean by that is we've taken all our software and it's running on containers today, and that's a key enabler to make this happen, because containers give you that flexibility and that openness to run on different targeted environments and be able to run on different clouds at the end of the day. >> The model by which developers thought about integration would be through a transaction. Generally pretty stateful. So, I'll put something in a queue, I'll wait for a response, guaranteed delivery. Now we're moving to a world, containers, a lot more reliance on stateless interactions. It means we're being driven mainly by events. I'm thinking in terms of events. Talk about how that is changing the way we think about the role of middleware or the role of integration amongst all these different possible services. >> Yeah, it's a great point. I mean, so if you think about containers, we think about stateless, and we think about microservices, and we talk about event-based applications, so a lot of those front ends are on that today and building on those technologies. So you've got to enable the new developers to build in that way. Now, how do you integrate that with that backend, right? Because at the end of the day, these transactions are running in the backend, and you really want to enable, as part of the transformation, you want to open up those backends to those new developers and to those new customer insights, because what is digital transformation? It's about putting the customer at the middle and enable insights on those customers, and enable rapid development of those applications. So at the core of that is integration, and integration is not just message-based integration. It's being able to take those backend transactions and surface them up through APIs, not just the standard APIs as we think of maybe as web services, but event-based probability models, and event-based APIs also, and doing that in a consistent and a secure manner, because if you have all these complex transactional systems, who has access to that data? Who has access to make those transactions? Who can, at certain levels, et cetera, and we really have to do that in a secure and a consistent manner across these environments is critical to what we do. >> So, can you give us some examples of some customers that are successfully transitioning their backend systems to these new technologies in a way that protects the backend system, makes it economical to do so, in other words, doesn't force change, but can utilize some of these new integration technologies to make both the new investments more valuable but also the backends more valuable too. >> Yeah, I mean, if you think of, I'll give you an example of a customer, American Airlines, in the airline industry, right? So, if you think about travel and airline travel in times past, you know, you made a reservation maybe through an agent and you booked the flight from A to B. Today, you have your cellphone, you get regular updates on your flights. If you're delayed, you're possibly offered re-routing options, et cetera, right, so there's a classic example of how digital has transformed the airline industry and the airline booking industry. If your flight, you know, if there's weather patterns, et cetera, how you can get real time updates on your flights. So, okay, that's all happening on the front end, on your cellphone, or your tablet, or whatever, but the backend booking system is still a transactional-based system that says, Peter is on this flight going from A to B at this time, et cetera. So, that's an example of how we have modernized an application and we have worked with American Airlines to make that happen, to give you that kind of 360 view as a customer, where you bring in together flight information, weather information, rating information, because we'll offer you different alternatives in terms of if you need to rebook in the event of something going on, and at the backend, there's still a transaction that says, book Peter on this flight from A to B, and that's a real life example of a transformation, how we've integrated those two worlds there. >> So if we go back five or six, or more than that, say 10, 15 years, in the days of MQ, for example, the people who were developing, and setting up those systems, and administering and managing those systems were a relatively specialized group. Today, the whole concept of DevOps in many respects is borrowing from much of the stuff that those folks did many, many years ago as infrastructure builders, or developers, as I call them. How does that group move into this new world of integration in the cloud? >> Yeah, so, I think first of all, the rate and pace has multiplied, right, so the rate and pace of which we make changes to the system has multiplied. I mean, maybe traditionally, we run in changes maybe once a month. We have things like change control windows. Things were very well controlled, et cetera, right? But at the end of the day, it doesn't meet the needs of today and what we need to do in a digital world. So today, we're running in changes on the hour. So now, you're faced with a challenge, right? So when you make changes, how do you know that the system is still performing, is still operating at the level you need it to operate on? You start to think about security and you start to think about, okay, I've made a change, have I introduced vulnerabilities into the system? You've got to, you know, in the past, these were all separate groups and almost islands within the operation center, where you have the developer, who kind of over to all the code, and then operations looked at it and see how it's performed, and security checked for compliance, et cetera, and they were kind of three different islands of personas or groups within the organization. Today, that's really collapsing into one organization. The developer is responsible for making sure the change gets in, for making sure the change performs, and is also security compliant. And we call this the role of the SRE, or the systems reliability engineer, and really bringing those two worlds together into one persona, and it's not just one persona but having the systems on the inside to make that happen. And that's critical in how management is changing and the management of these systems is changing, and how the skill level is needed in this new world. >> So Denis, one more question. In a few months, IBM Think is going to take over San Francisco, February 2019, >> Looking forward to it. >> 3,000 people. Talk to us a little bit about what gets you excited about Think, and what kind of conversations you hope to be having while you're there. >> Yeah, well, you know, this is the one time of the year where all of IBM comes together, and it's new this year that we're going to San Francisco, and in particular, in our cloud business, which I'll talk about, which really encompasses everything we're talking about here, which is our middleware business and also how we move customers to the cloud, and really engaging with customers in those conversations. And this is the one time of the year where all of IBM comes together, and where you can see the full breadth of our capabilities all the ways from our systems, and the hardware, down at that level, at the chip level, right through to the middleware and the software to our cloud, and actually engaging with customers, and really understanding what the customer needs are, and making sure that what we are working on is meeting those customer needs, and of course, if we need to adapt or change, and take that feedback back into the organization, so we do that in real time. It's a very exciting time for us. It's a week in the year that I really look forward to, because that's where all of IBM comes together, including our services, et cetera, and where we actually have conversations with key customers and partners and really understanding what's going on in the industry and how we can help people on this journey to the cloud that I talked about. >> Denis Kennelly, IBM General Manager of Cloud Integration, thanks very much for being on theCUBE. >> Thank you, Peter. And once again, this is Peter Burris. We're signing off from the IBM Innovation Day, here at the Thomas J. Watson Research Center in Yorktown Heights. Thank you very much for watching. Let's carry on these conversations about cloud and the future of computing.

>> Live, from Las Vegas, it's the Cube, covering AWS re:Invent 2018, brought to you by Amazon Web Services, Intel, and their ecosystem partners. >> Hey welcome back everyone, live here in Las Vegas for AWS re:Invent 2018, all the action is happening for Amazon Web Services. I'm John Furrier, Dave Vellante, Dave six years covering Amazon, great opportunity, a lot of news, Red Hat is a big part of it, Mike Ferris is here. Vice President, Technical Business Development for Red Hat, welcome back, good to see you. >> Likewise. >> A lot's going with you guys since our Red Hat Summit days in San Francisco just a few months ago. >> Yeah. >> Big news hit. >> Yeah. >> The bomb around the world, the rock that hit the ground really hard, shook everyone up, surprised everyone including me, I'm like "Wow, IBM and Red Hat". What an interesting relationship, obviously the history with IBM has been good. Talk about the announcement with IBM because this is huge. Of course, big numbers, but also impact wise pretty big. >> Yeah, it's exciting times right? And if you kind of look at, you know, from the perspective of Red Hat in this, this will allow us to really scale and accelerate what we've already been doing for the past, you know, since really the 1994 era when Red Hat was founded and, you know, it kind of validates a lot of what we've put into open source and enterprise customers since then. You know, we really see a couple of key outtakes from this, one of which is, certainly it's going to give us the resources to be able to really grow with the scale that we need to. It's also going to allow us to invest more in open source in emerging areas, bring the value of scale and certainly choice and flexibility to more customers, and then ultimately kind of the global advantage of hybrid and multi cloud, we'll be able to reach more partners and customers everywhere, and it puts us several years ahead of where we have been and where we would have been frankly, and ultimately our intent is that with IBM we'll become the leading hybrid and multi cloud provider overall. >> Yeah, Jimmy and Jim Whitehurst kind of ruined our Sunday, we were sitting down to watch football and he's like got the announcement. And then Jimmy kept saying "It's not backend loaded, it's not backend loaded" and then you start to realize, wow, IBM has an enormous business of managing applications that need to be modernized and OpenShift is obviously a great place to do that so, it's got to be super exciting for you guys to have that giant new opportunity to go after as well as global scale that you didn't have before. >> And, you know, this extends the stuff that we did, announced in May at Red Hat Summit with IBM where we really focused on how do we take WebSphere DB2MQ, running on IBM cloud private, running on OpenShift, and make that the hybrid choice. And so it's a natural extension of what we've already been doing and it gives us a lot more resources than we would have otherwise. >> This is good, coming into the next segment I want to chat about is RHEL, and what people might not understand from the announcment is the synergy you guys have with IBM because, being a student of Red Hat, being just in the industry when you guys were rebels, open source, second tier citizen, and the enterprise, the adoption then became tier one service. I mean you guys have, level of service, 17 years or something, huge numbers, but remember where it all started. And then you became a tier one supplier to almost all the enterprises, so you're actually a product company as well as a huge open source player. That's powerful and unique. >> Absolutely, even if you look at kind of what Amazon is doing this week and have been doing over the years, they're a huge value ad provider of open source technology as well, and one of the statements that we've always made is, the public cloud would not exist if not for Linux and open source, and so everything has been based upon that. There's one provider that doesn't use Linux as the base of their platform but certainly as we've taken the in roads into the enterprise, you know, I was there when it started with just turning Red Hat Enterprise Linux on and then bringing it from the edge of network into the data center and talking about major providers like Oracle, HP, Del, IBM as part of that. Now, we're looking at "Is it a de facto standard?", and everyone including Amazon and all of it's competitors are really invested heavily in the open source world. >> And so, let's talk about the impact to the products, okay so one of the things that has come up, at least on my Twitter feed and the conversations is, okay, it's going to take some time to close the deal, you're still Red Hat, you're still doing your things, what's the impact to the customers and to the ecosystem in your mind? How are you guys talking about that right now? Obviously, it's more of the same, keep the Red Hat same, unique, independent, what new thing is going to come out of it? >> So, to be clear, the deal has not closed, right, so there's not a lot we're going to say otherwise. >> A year away, you got a lot of work to do. >> Our focus is what it always has been. Let's build the best enterprise products using the open source development model and make those available across all public and hybrid cloud environments. >> At a certain level, that's enterprise, multi-year, old Red Hat, same Red Hat model, alright. >> But let me follow up on that, because you're a believer in multi cloud, we're a believer in, whatever you call it, multiple clouds, customers are going to use multiple clouds. We believe that, you believe that, it seems like Amazon has a slightly different perspective on that, >> Cause they're one cloud. >> in that this greater value, right cause they're one cloud, there's greater value, but it seems like the reality when you talk to customers is, we're not just one company, we've got different divisions, and eventually we've got to bring those together in some kind of extraction layer. That's what you guys want to be, right? So, your perspectives on multi cloud? >> Absolutely, so, each individual department, each project, each developer, in all of these major enterprises, you know, has a different vantage, and yes, there are corporate standards, golden masters of RHEL that get produced, everybody's supposed to be using, but you know, the practicalities of how you develop software, especially in the age of dev ops and containers and moving forward is actually, you have to have the choice necessary to meet your specific needs, and while we will absolutely do everything we can to make sure that things are consistent, I mean, we started this with RHEL consistency, on and off premise, when we did the original Amazon relationship. The point is, you need to be able to give people the flexibility and choice that they desire, regardless of what area of the company that they're in, and that's going to be the focus, regardless of whether it's Microsoft, Amazon, Google, IBM clouds, international clouds with Alibaba, it's all the same to us and we have to make sure it's there. >> What's always great about the cloud shows, especially this one, it's one of my favorites, because it really is dev ops deep in the mindset culture. As you see AI and machine learning start to get powered by all these great resources, computer, et cetera, the developer is going crazy, there's going to be another renaissance in software development, and then you got things like Kubernetes and containers now mainstream. Kubernetes almost, I say, de facto standard. >> Yeah. >> Absolutely happened, you guys had a big part of making that happen. People are now agreeing on things, so the formation's coming together pretty quickly, you're seeing the growth, we're hearing terms like "co-creation", "co-opetition", those are signals for a large rising tide, your thoughts? >> So, it's interesting, we were an early investor in Kubernetes, we actually launched OpenShift prior to Kubernetes, and then we adopted it and made a shift of our platform before it was too late. We did the same thing with hypervisors when we moved from Zen to KBM, but this overall approach is, once we see the energy happening both in the community and the early customers, then you see the partners start to come on board, it becomes the de facto standard, it's really crucial for us as an open source company to make sure we follow those trends, and then we help mature them across the business ecosystem, and that's something we've loved being able to engage with. I mean, Google certainly instigated the Kubernetes movement, but then it starts to propagate, just like on the open stack side, it came out of Rackspace and Nasa and then moved on to different areas and so, you know, our focus is, how do we continue that choice and that evolution overall? >> How would you talk about the impact of Kubernetes if someone says "Hey Mike, what's the real impact, what is it going to accomplish at the end of the day?" What's your view of that? >> It will have the same impact that the Linux current standardization has had, you know, but in this case for micro services and application packaging and being able to do dev ops much more efficiently across heterogeneous platforms. >> Does it make it easier or less painful or does it go away? Is it automated under the covers? I mean, this is a big, awesome opportunity. >> So the orchestration capabilities of Kubernetes combined with all the other tools that surround key container platforms like OpenShift, really give that developer the full life cycle environment to be able to take something from concept through deployment, and onto the maintenance phases, and you know, what we end up doing is we look at, okay the technologies are there, what value ads to we have around that to make sure that a customer and a developer cn actually maintain this thing long term and keep their enterprise applications up? >> So, security for example. >> Security is a great example, right? How do we make sure that every container that gets deployed on Kubernetes platforms or by Kubernetes platforms, that every container that's deployed which, keep in mind, is an operating system, it has an operating system in the container itself, how is that kept up to date? How do you make sure that when the next security errata is released, from us or a different vendor possibly, how do you make sure that that container is secure? And, you know, we've done a lot in our registry as well as our catalog to make sure that all of our partners and customers can see their containers, know what grade they have in a security context, and be able to grow that. That's one of the core things that we see adding into this Kubernetes value and authorization level. >> It's not a trivial technical problem either. >> No. >> Sometimes micro services aren't so micro. >> It's been part of what we've for RHEL from the start, it's been how do we bring that enterprise value into technology that is maturing out of the open source community and make that available to customers? >> Yeah, one of the key things you guys, first of all, OpenShift has been phenomenal, you guys did a great job with that, been watching that grow, but I think a real seminal moment was the CoreOS acquisition. >> Sure. >> That was a real turbo boost for you guys, great acquisition, fits in with the culture, and then Kubernetes just lifted from that, that was the point but, at the timing of all this, Kubernetes gets mainstream lift, people recognize that the standardization it is a good thing, and then, boom, developers are getting engaged. >> Yeah, and if you see what the CoreOS environment has brought us from over their updates for our platforms, to being able to talk about a registry in the environment. Being able to say that, is kind of additive to this overall messaging, it really rounds out the offering for us, and allows us to participate even more deeply in the communities as well. >> Well, we're looking forward to keeping you covered, we love Kubernetes, we've got a special report called "Kubernetes Special Report" on siliconangle.com, it's called "The Rise Of Kubernetes", it's a dedicated set of content, we're publishing a lot on Kubernetes. Final question I want to get to you because I think it's super important, what's the relationship you have with AWS? And take some time to explain the partnership, how many years, what you guys are doing together, I know you're actively involved, so take a minute. >> It is somewhat blurry, it's been a long time, so 2007 era is when we started in depth with them, and I can remember the early days, actually in the development of S3, prior to EC2, being able to say alright, what is this thing and how does Red Hat participate in this? And I think, yesterday Terry Wiese even mentioned that we were one of the first partners to actually engage in the consumption model and, you know, claiming partial credit for out 34 billion dollar valuation that we just got announced. But, you know, overall the relationship really spawned out of that, how do we help build a cloud and how do we help offer our products to our customers in a more flexible way? And so that snowballed over the years from just early adopters being able to play with it to now where you see it's many many millions of dollars that are being generated in customers and they think, in the hundreds of millions of hours of our products being consumed, at least within a month if not shorter timeframes, every time period we have. >> You know that's an unsung benefit that people might not know about with Red Hat is that, you guys are in early markets because, one, everyone uses Linux pretty much these days for anything core, meaningful. And you listen to community, and so you guys are always involved in big moving things, cloud, Amazon, 2007, it was command line back then. >> Yeah. >> It wasn't even, I think RightScale just came online that year, so you remember. You guys are always in all these markets so it's a good indicator, you guys are a bellwether, I think it's a good beacon to look at. >> And we do this, certainly on the container space, and the middleware space, and the storage space, you know, we replicate this model and, including in management, about how do we actually invest in the right places where we see the industry and communities going so we can actually help those? >> And you're very partner friendly, you bring a lot to the table, I love the open source ethos, I think that's the future. The future of that ethos of contributing to get value downstream is going to be a business practice, not just software, so you guys are a big part of the industry on that and I want to give you guys props for that. Okay, more Cube coverage here in Las Vegas, AWS Reinvent, after this short break, more live coverage, I'm John Furrier, Dave Vellante, we'll be right back. (electronic music)

>> Live from Orlando Florida, it's theCUBE. Covering Cisco Live 2018, brought to you by Cisco, NetApp, and theCUBE's ecosystem partners. (electronic music flourish) >> Welcome back, I'm Stu Miniman and this is theCUBE's exclusive coverage of Cisco Live 2018 in Orlando Florida. Joining me, my co-host for this segment Dave Vellante sitting in for John Furrier and happy to welcome to the program Jeff Eckard, who's the Vice President of Storage Solutions at IBM. Jeff, thanks so much for joining us. >> Thank you, good to see you guys. >> All right, and 26,000 people here. It'd been many years since I'd been to Cisco Live. There's some things that are same, many of the same faces, but a lot of new jobs, a lot of buzz going on. What's your impression been of the show this week? >> Yeah, it's been an interesting, great show for IBM and our presence, but it's a very large ecosystem of Cisco partners, a lot of their, our joint end users and a lot of focus on multi-cloud. You've consistently heard that as a theme from Cisco as well as IBM since last fall at their partner forum and they've continued it here with a lot of focus on being able to take tools and capabilities and enabling enterprises to manage data where they want to manage it. And it's really interesting, from traditional systems vendors like Cisco, to see that focus particularly around developers. >> It's been fascinating for me to watch. Jeff, you and I have some background in the storage and storage networking piece, specifically, where it was like, OK, where I sit in the stack and I've got a couple of integrations, and we work on our standards here. It's much broader. >> Oh, absolutely. The things that we're working on. We're talking about cloud. There's a lot of software that flows. Data and applications are critically important. Talk a little bit about some of that transformation and how you're seeing the expansion, and-- >> Yeah, no, it's a interesting time. If you think about the opportunities and challenges facing all enterprises, data is at the core of digital transformation, digital enhancement, whatever term you wanna use with it. Typically, it's focused in on wanting to provide realtime insights so that you make better decisions against threats or opportunities. Being able to deliver personalized services to your clients, and then also improving your internal processes and business outcomes. And so data is core for digital transformation, and you kinda see, kind of this web of what we're talking about here and then what we're doing with clients as well. >> You know, Jeff, you talk about multi-cloud, you've been in the business for a while, and throughout your career you've tried to help customers simplify their lives, and everybody felt, I thought, OK, I'm gonna put stuff in the cloud, it's gonna get simpler, and now you see this spate of clouds, whether it's infrastructures of service, private clouds, SaaS, and complexity is, in some regards, never have been higher, particularly as it relates to the data. >> That's right. >> You've gotta figure out, where do you put this stuff? How do you protect it, what about governance? Even if you think security's better in the cloud, it might be different for every cloud. So how is IBM approaching, generally in your team, specifically approaching simplifying the complex of this multi-cloud world? >> Sure, so from an IBM Perspective, at the top level we approached it with innovative technology and a lot of industry expertise, whether it's in financial services or healthcare, cloud and what we do with the public IBM cloud is really important around the services we provide there, data and AI, and then as you come down from that, modern infrastructure is key because modern infrastructure supports the data. So when you look at 80% of enterprises are intending to be multi-cloud. Something like 70% already are, right? Because of what you referenced with the consumption of SaaS. So, multi-cloud is the defacto operating model for applications and then, therefore, for the data. So from an IBM storage and SDI perspective, we kind of view... There are three primary adoption patterns that we're seeing with our clients. The first is around modernizing traditional applications or workloads, which also drags modern infrastructure, flash-based systems, leveraging more of storage efficiency technologies, like compression and dedupe, being able to protect that data, whether it's in a traditional VMware environment or the emerging containers environment. So, yeah, data's at the core. The partnership that we have with Cisco around VersaStack enables us to support traditional private clouds, whether those are built on the VMware set of tools or now, as last week we announced, the VersaStack for IBM Cloud Private. IBM Cloud Private is an enterprise platform for developers to leverage microservices and containerized IBM Middleware Services, whether that's WebSphere or MQ or Microservices Builder, as well as a whole catalog of open source technologies and tools to get agility out of the DevOps process and then also layer on analytics on top of that. >> So customers, they're gonna want consistency across all those clouds. So what role do you guys bring? Are you trying to be a platform of platforms, or is that too aspirational? Obviously, you can't have 100% market shares, so that's not practical. But to the extent that people adopt your technologies, is that how we should be thinking of about it? >> Well, so IBM Cloud Private is an open platform. It's built on Docker runtimes and Kubernetes orchestration. It's open to where you can leverage things like Red Hat OpenShift if you've chosen them for your containers platform, and then we also support the traditional Private Clouds with VMware. So, there's a whole set of tools in there. What we're trying to do from a data management perspective is protect it, whether that's backup and recovery, morphing into this new category of secondary data reuse. So, for instance, from a traditional workflow of just doing backup and recovery, we can now take native format copies of the data, whether that's in Oracle or SQL Server database, et cetera, and take that data to the Public Cloud, where different personas and use cases can act on that data. So you can spin up a VM from that Native format within our tools in the IBM cloud. So that's from a data protection standpoint. On data management, we have, later this year, we'll talk more formally about programs that we have around metadata management. That's where you can index and classify, for instance, unstructured or structured data, and act on that in terms of, where was it last accessed? Who should be accessing it? Is it personally identifiable information? Do I wanna run analytics on it? So the metadata management is an opportunity to plug in to broader IBM things, whether it's Watson data platform or information governance catalogs, to provide that kind of uber across cloud infrastructure management. >> And that's a machine sort of intelligence, automation component, that scale, right? >> It could absolutely be used for augmented intelligence, artificial intelligence, some of the machine learning pieces as well. >> Jeff, Jeff, I'm wondering if you could give us a little insight of some of the places that customers are falling down. We were just talking to a systems integrator before you came on and he said, "Well, sometimes I take a virtualized environment "and I move it and it's not really geared "for this modern platform." Containerization can help in a lot of these environments, so when you talk about the pattern we've seen that works many times is you modernize the platform, and then I can modernize the application, start pulling things apart, start refactoring, start playing with some of these environments because I can't just... Lift and shift can help, but it can't be that's the only move. There's a lot of work that needs to get done, and a lot of time that's underestimated. >> Right, well it's not a panacea, but there is a key tool called Transformation Advisor that is part of the IBM cloud platform. It's intended to assist with the challenge that you just stated, which is, OK, how do I take a traditional workload, determine if it's ready to be containerized, and then start the process of containerization. You can go back to some of the VM migration pieces, too. There's a whole set of tools that enterprises have used. Transformation Advisor is one tooling example of what we can do in the platform. And then we obviously have services through Global Services that can help at a large scale for enterprises to kinda make that step. >> You bring up a good point there, 'cause we always struggle with some of these tool transformations, but if you go back to virtualization it was really some of the organizational things that had to shift. Wonder if you can talk about some of the things that are changing here. This show, we've spent a lot of time talking about Cisco's moving up the stack, network people are much more closer tied to some of those new application development, especially with things like intent-based networking. >> Well, it's a interesting reminder that we get often from clients, 'cause you're really touching at some of the remember the operational steps, things like containerization are interesting new technologies, and there's a lot of advantages to them. But just going back a minute, of the heritage with what we've been doing with Cisco around VersaStack, leveraging it on a VMware environment, we hear a lot from customers that their operational practices really are set around Vmware and the VMware tooling. So one of the things that we did with IBM Cloud Private is, it can run on top of VMware. So as customers want to take a kind of transitive step towards microservices, they can continue to leverage their operational practices around VMware. So it's important to, it sometimes takes enterprises a little bit longer than you may guess, right, to embrace the new set of things. Our product portfolio and our directions are set where they can leverage some of the operational pieces they already have. >> Well, just for our viewers who may not know, I mean, the recent history of IBM and Cisco is quite interesting. IBM at one point purchased a company called BNT, which got sold as part of the X86 sale to Lenovo. That opened up a huge opportunity for IBM and Cisco to partner because it was very clear swim lanes. And that sorta catalyzed a relationship that from your standpoint, VersaStack was sort of the first instantiation of that relationship. So, take us through, sort of, where you guys are in the partnership and where you see it going. >> Sure, yeah, so VersaStack, for folks who may not be familiar, it's a Converge System, right? So it's IBM storage, flash or otherwise, leverages Cisco UCS servers, and then their Nexus and MDS Switching. So it's integrated, validated as a single solution to, as the name implies, to be very versatile and provide agility and flexibility. And so, through our routes to market, either with distribution or resellers or system integrators, it is a way that we can address platforms that matter to our joint customers. We've talked about IBM Cloud Private. A lot of heritage around VMware and SQL server and Oracle and a lot of focus around SAP HANA. So, we typically will partner around which enterprise platforms are we going, and then we also partner, in general, around MDS Switching with Cisco, and we'll talk more about that in months to come as we enhance that relationship. >> So, the solutions part of your title, you just mentioned VMware, Oracle, SAP HANA, there may be others. How do you guys approach solutions? Maybe you can talk about that a little bit. >> Yeah, so a solution, at a PetaLogic level, is a successful repeatable outcome. And what we focus on, then, are the integrations that matter. Those could be, integrations with IBM tools, like we talked about with IBM Cloud Private. Could be the integrations that we do jointly with Cisco through the validated design process for some of these applications or databases. And so we have teams that do the validation work and figure out how we marry IBM capabilities with ecosystem capabilities. And there's a whole, whether we're automating private clouds or accelerating workloads including the partnership that IBM and Cisco have with Horton Works. And then in industry context as well, particularly in healthcare and financial services. We'll pick the platforms that really matter and then do the integrations that enable us to take, whether it's our systems or our software or IBM level capabilities to market. >> I wanna come back to this simplicity theme, specifically in the context of data protection. With all this multi-cloud, data protection has become a really hot topic. You guys have dramatically simplified your data protection offering with Spectra Protect Plus. Talk about data protection, how it's changing from where it used to be just, OK, it's a virtualized world. We kind of understand the challenges of virtual data protection. That has played itself out, and now there's a whole new wave coming. What's your perspective on this? >> Well, I don't know if the virtual is play, I mean, the virtualized environment is still kind of paying the freight, if you will. >> Yeah, played out in terms of-- >> Yes, no, no, yeah, right. >> We understand what had to change. >> Right. And customers have made that change >> Yeah, and your simplicity point on that is really key. So one of the enhancements that we announced last year at VMWorld was Spectrum Protect Plus. So that's an agent list, OVA based, VM based backup and recovery tool. And it's very simple to use. The trick is that we've focused its capabilities around secondary data re-use. So I mentioned earlier, that whole workflow has evolved to where the data has increasing value beyond its primary use, right? So backup and recover, but then we can leverage those native format copies. Spectrum Protect Plus is available either on a bring your own license or a monthly subscription in the IBM cloud, other clouds over time. And so we enable enterprises to not only do the traditional backup and protection, but very simply, move that data to either a secondary or tertiary data center, if that's still a part of their backup architecture, or into the public cloud. And so the simplicity factor comes in, again, that it's agent lists. There's a catalog of where all your copies are, and you can reuse that data for whether it's DevOps or DevTest or analytics purposes. >> OK, so that's helpful. So what I'm trying to get to was sort of the enablers, maybe from a technology standpoint, because in the virtualization world, it was all about efficiency because you didn't have the underutilized physical resources anymore. >> Yep, right. >> All the servers utilized 10%. (chuckles) Well, I got rid of a lot of those physical servers, and the one job that needed that power was backup, so I needed a new way to approach it. What I'm hearing is, in this multi-cloud world, it's a focus on simplicity. I'm inferring from that, a cloud-like experience, maybe some other capabilities that you guys are-- >> Yeah, so. >> Doing away with. >> The containers are a progression. I mean, VMware came around to maximize your CPU and storage utilization. Containers provide yet another level of efficiency on top of that. They bring with them the need for changes in your data protection. And so we, at Think in March, we talked about our directions around container aware data protection and container aware snapshots. Most vendors will use snapshots and then volume level controls of how we've traditionally done backup. We have a progression, and we'll talk more about it later in the year, of how we do snapshots, again, that are container aware. They leverage our tools, such as Spectrum Copy Data Management, Spectrum Protect Plus, integrate with our arrays. But they'll bring the same level of capability that we've had traditionally in a virtualized environment to also support data protection in a container world. >> Well, it's an interesting landscape right now in data protection. >> Oh, it's awesome! There's so many new tools, and it's great to be able, (Dave chuckling) like we talked about earlier, to partner with Cisco around some of this as well. >> Great, Jeff, I wanna give you the final word, as if, for those that couldn't make it to the show, either share key conversation you're having, you're hearing from customers, or a big takeaway from the show that you'd like to share. >> Sure, yeah, we've had a lot of customers come up and wanna know, OK, well, how do you start, right? And we talked about, there are three primary adoption patterns, whether it's modernizing, and typically it will start with modernizing traditional workloads. 70% of private cloud usage is for that particular use case. Well, you can pretty quickly show them, then, the progression to, OK, they wanna be more agile. They wanna go cloud-native. From that private cloud infrastructure, you can do that, and then you can have a consistent way that you interact around services in the public cloud. And so that's what we've been talking to clients about. They wanted to know, how do I start with what I have, and then how do I get to this better future? And how do I leverage your tools and capabilities? And so whether that's with IBM systems components or what we do with our partnership with Cisco, we're showing them how we, collectively, can help them on that journey. >> All right, Jeff, I really appreciate all the updates. Dave, thanks so much for joining me for this segment. >> Yeah, thank you. >> We still have a full day here, three days wall-to-wall coverage of theCUBE, Cisco Live 2018. Thanks so much for watching. (techno musical flourish)

>> [Announcer] 18, brought to you by Red Hat >> Well, welcome back everyone. This is theCUBE's exclusive coverage here in San Francisco, California, for Red Hat Summit 2018. I am John Furrier, co-host of theCUBE with my analyst co-host this week, John Troyer, co-founder of the TechReckoning advisory services. And our next guest is Arvind Krishna, who is the Senior Vice President of Hybrid Cloud at IBM and Director of IBM Research. Welcome back to theCUBE, good to see you. >> Thanks John and John great to meet you guys here. >> You can't get confused here you've got two John's here. Great to have you on because, you guys have been doing some deals with Red Hat, obviously the leader at open storage. You guys are one of them as well contributing to Linuxes well documented in the IBM history books on your role and relationship to Linux so check, check. But you guys are doing a lot of work with cloud, in a way that, frankly, is very specific to IBM but also has a large industry impact, not like the classic cloud. So I want to tie the knot here and put that together. So first I got to ask you, take a minute to talk about why you're here with Red Hat, what's the update with IBM with Red Hat? >> Great John, thanks for giving me the time. I'm going to talk about it in two steps: One, I'm going to talk about a few common tenets between IBM and Red Hat. Then I'll go from there to the specific news. So for the context, we both believe in Linux, I think that easy to state. We both believe in containers, I think that is the next thing to state. We'll come back talk about containers because this is a world, containers are linked to Linux containers are linked to these technologies called Kubernetes. Containers are linked to how you make workloads portable across many different environments, both private and public. Then I go on from there to say, that we both believe in hybrid. Hybrid meaning that people want the ability to run their workload, where ever they want. Be it on a private cloud, be it on a public cloud. And do it without having to rewrite everything as you go across. Okay, so let's establish, those are the market needs. So then you come back and say. And IBM has a great portfolio of Middleware, names like WebSphere and DB2 and I can go on and on. And Red Hat has a great footprint of Linux, in the Enterprise. So now you say, we've got the market need of hybrid. We've got these two thing, which between them are tens of millions, maybe hundreds of millions of end points. How do you make that need get fulfilled by this? And that's what we just announced here. So we announced that IBM Middleware will run containerized on Red Hat containers, on Red Hat Enterprise Linux. In addition, we said IBM Cloud Private, which is the ability to bring all of the IBM Middleware in a sort of a cloud-friendly form. Right you click and you install it, it keep it self up, it doesn't go down, it's elastic in a set of technologies we call IBM Cloud Private, running in turn on Red Hat OpenShift Container service on Red Hat Linux. So now for the first time, if you say I want private, I want public, I want to go here, I want to go there. You have a complete certified stack, that is complete. I think I can say, we're a unique in the industry, in giving you this. >> And this is where, kind of where, the fruit comes off the tree, for you guys. Because, we've been following you guys for years, and everyone's: Where's the cloud strategy? And first of all, it's not, you don't have a cloud strategy you have cloud products. Right, so you have delivered the goods. You got the, so just to replay. The market need we all know is the hybrid cloud, multi-cloud, choice et cetera, et cetera. >> You take Red Hat's footprint, your capabilities, your combined install base, is foundational. >> [Arvind] Right >> So, nothing needs to change. There's no lift and shift, there's no rip and replace, >> you can, it's out there it's foundational. Now on top of it, is where the action is. That where you're kind of getting at, right? >> That's correct, so we can go into somebody running, let's say, a massive online banking application or they're running a reservation system. It's using technologies from us, it's using Linux underneath and today it's all a bunch of piece pods, you have a huge complex stuff it's all hard-wired and rigidly nailed down to the floor in a few places and now you can say: Hey, I'll take the application. I don't have to rewrite the application. I can containerize it, I can put it here. And that same app now begins to work but in a way that's a lot more fluid and elastic. Or my other way: I want to do a bit more work. I want to expose a bit of it up as microservices. I want to insert some IA. You can go do that. You want to fully make it microservices enabled to be able to make it into little components >> and ultimately you can do that. >> So you can take it in sort of bite size chunks and go from one to other, at the pace that you want. >> [John F.] Now that's game changing. >> Yeah, that's what I really like about this announcement. It really brings best of breed together. You know, there is a lot of talk about containers. Legacy and we've been talking about what goes where? And do you have to break everything up? Like you were just saying. But the announcement today, WebSphere, the battle tested huge enterprise scale component, DB2, those things containerized and also in a frame work like with IBM, either with IBM microservices and application development things or others right, that's a huge endorsement for OpenShift as a platform. >> Absolutely, it is and look, we would be remiss if we didn't talk a little bit. I mean we use the word containers and containerized a lot. Yes, you're right. Containers are a really, really important technology but what containers enable is much more than prior attempts such as VM's and all have done. Containers really allow you to say: Hey, I solved the security problem, I solved the patching problem, the restart problem, all those problems that lie around the operations of a typical enterprise, can get solved with containers. VM's solved a lot about isolating the infrastructure but it didn't solve, as John was saying, the top half of the stack. And that's I think the huge power here. >> Yeah, I want to just double click on that because I think the containers thing is instrumental. Because it, first of all, being in the media and loving what we do. We're kind of a new kind of media company but traditional media is been throwing IBM under the bus since saying: Wow old guard and all these things. Here's the thing, you don't have to change anything. You got containers you can essentially wrap it up and then bring a microservice architecture into it. So you can actually leverage at cloud scale. So what interests me is that you can move instantly, >> value proposition wise, pre-existing market, cloudify it, if you will, with operational capabilities. >> Right. >> This is where I like the Cloud Private. So I want to kind of go there for a second. If I have a need to take what I have at IBM, whether it is WebSphere. Now I got developers, I got installed base. I don't have to put a migration plan away. I containerize it. Thank you very much. I do some cloud native stuff but I want to make it private. My use case is very specific, maybe it's confidential, maybe it's like a government region, Whatever. I can create a cloud operations, is that right? I can cloudify it, and run it? >> Absolutely correct, so when you look at Cloud Private, to go down that path, we said Cloud Private allows you to run on your private infrastructure but I want all these abilities you just described John. I want to be able to do microservices. I want to be able to scale up and down. I want to be able to say operations happen automatically. But it gives you all that but in the private without it having to go all the way to the public. If you cared a lot about, your in a regulated industry, you went down government or confidential data. Or you say this data is so sensitive, I don't really, I am not going to take the risk of it being anywhere else. It absolutely gives you that ability to go do that and that is what brought Cloud Private to the market for and then you combine that with OpenShift and now you get the powers of both together. >> See you guys essentially have brought to the table the years of effort with Bluemix, all that good stuff going on, you can bring it in and actually run this in any industry vertical. Pretty much, right? >> Absolutely, so if you look at part what the past has been for the entire industry. It has been a lot about constructing a public cloud. Not just us, but us and our competition. And a public cloud has certain capabilities and it has certain elasticity, it has a global footprint. But it doesn't have a footprint that is in every zip code or in every town or in every city. That's not what happens to a public cloud. So we say. It's a hybrid world meaning that you're going to run some workloads on a public cloud, I'd like to run some workloads on a private and I'd like to have the ability that I don't have to pre decide which is where. And that is what the containers and microservices, the OpenShift that combination all give you to say you don't need to pre decide. You rewrite the workload onto this and then you can decide where it runs. >> Well I was having this conversation with some folks at a recent Amazon Web services conference. Well, if you go to cloud operations, then the on premise is essentially the edge. It's not necessarily. Then the definition of on premise, really doesn't even exist. >> So if you have cloud operations, in a way, what is the data center then? It's just a connected issue. >> That's right, it's the infrastructure which is set up and then, at that point, the Software Manger, at the data center, as opposed to anything else. And that's kind of been the goal that we're all been wanting. >> Sounds like this is visibly at IBM's essentially execution plan from day one. We've been seeing it and connecting the dots. Having the ability to take either pre-existing resources, foundational things like Red Hat or what not in the enterprise. Not throwing it away. Building on top of it and having a new operating model, with software, with elastic scale, horizontally scalable, Synchronous, all these good things. Enabling microservices, with Kubernetes and containers. Now for the first time, >> I can roll out new software development life cycles in a cloud native environment without forgoing legacy infrastructure and investment. >> Absolutely, and one more element. And if you want to insert some cloud service into the environment, be it in private or in public, you can go do that. For example, you want to insert a couple of AI services >> into the middle of your application you could go do that. So the environment allows you to, do what you described and these additionals. >> I want to talk about people for a second. The titles that we haven't mentioned CIO, Business Leader, Business Unit Leaders, how are they looking at >> digital transformation and business transformation in your client bases you go out and talk to them. >> Let's take a hypothetical bank. And every bank today is looking about simple questions. How do I improve my customer experience? And everybody want, when they say customer experience, really do mean digital customer experience to make it very tangible. And what they mean by that is how do I get my end customer engaged with me through an app. The app is probably in a device like this. Some smart phone, we won't say what it is, and so how do you do that? And so they say: Well, all obviously to check your balance. You obviously want to check your credit card. You want to do all those things. The same things we do today. So that application exists, there is not much point in rewriting it. You might do the UI up but it's an app that exists. Then you say but I also want to give you information that's useful to you in the context to what you're doing. I want say, you can get a 10 second loan, not a 30 day loan, but a 10 second loan. I want to make a offer to you in the middle of you browsing credit card. All those are new customergistics, where do you construct those apps? How do you mix and match it? How do you use all the capabilities along with the data you've got to go do that? And what we're trying to now say, here is a platform that you can go, do all that on. Right, that complete lifecycle you mentioned, the development lifecycle but I got to add to it >> the data lifecycle, as well as, here is the versioning, here are my AI models, all those things, built in, into one platform. >> And scales are huge, the new competitive advantage. You guys are enabling that. So I got to ask you a question on multi cloud. Obviously, as people start building out the cloud on PRIM and with Public Cloud and the things you're laying out. I can see that going on for a while, a lot of work being done there. We're seeing that Wikibon had a true Private Cloud report what I thought was truly telling. A lot of growth there, still not going away. Public Cloud's certainly grown in numbers are clear. However, the word multicloud's being kicked around I think it's more of a future stay obviously but people have multiple clouds Will have relationships with multiple clouds. No one's going to have one cloud. It's not a winner take all game. Winner take most but you know you're have multiple clouds. What does multi cloud mean to you guys in your architecture? Is that moving workloads in real time based upon spot pricing indexes or is that just co-locating on clouds and saying I got this app on this cloud, that app on that cloud, control plane it. These are architectural questions. What the hell is multicloud? >> So there's a today, then there is a tomorrow, then there is a long future state, right? So let's take today, let's take IBM. We're on Salesforce, we're on ServiceNow, we're on Workday, we're on SuccessFactors, well all of there are different clouds. We run our own public cloud, we run our own private cloud and we have Judicial Data Center. And we might have some of the other clouds also through apps that we barter we don't even know. Okay, so that's just us. I think everyone of our clients are like this. The multicloud is here today. I begin with that first, simple statement. And I need to connect the data and can connect when thing go where. The next step, I think people, nobody's going to have even one public cloud. Even amongst the big public clouds, most people are going to have two if not more That's today and tomorrow. >> Your channel partners have clouds, by the way, your Global SI's all have clouds, theCUBE is a cloud for crying out load. >> Right, so then you go into the aspirational state and that may be the one you said, where people just spot pricing. But even if I stay back from spot pricing and completely (mumbles) I make. And I'm worrying about network and I'm worrying about radio reach. If I just backup around to but I may decide I have this app, I run it on private, well, but I don't have all the infrastructures I want to burst it today and I, where do I burst it? I got to decide which public and how do I go there? >> And that's a problem of today and we're doing that and that is why I think multicloud is here now. >> Not some point in the future. >> The prime statement there is latency, managing, service level agreements between clouds and so on and so forth. >> Access control on governance, Where does my data go? Because there may be regulatory reasons to decide where the data can flow and all those things. >> Great point about the cloud. I never thought about it that way. It is a good illustration. I would also say that, I see the same arguments in the data base world. Not everyone has DB2, not everyone has Oracle, not everyone has, databases are everywhere, you have databases part of IoT devices now. So like no one makes a decision on the database. Similar with clouds, you see a similar dynamic. It's the glue layer that, interest me. As you, how do you bring them together? So holistically looking at the 20 miles stare in the future, what is the integration strategy long-term? If you look at distributed system or an operating system there has to be an architectural guiding principle for integration, your thoughts. >> This has been a world 30 years in the making. We can say networking, everyone had their own networking standard and the, let's say the '80s probably goes back to the '70s right? You had SNA, you had TCP/IP, you had NetBIO's-- >> DECnet. DECnet. You can on and on and in the end it's TCP/IP that won out as the glue. Others by the way, survived but in packets and then TCP/IP was the glue. Then you can fast forward 15 years beyond that and HTTP became the glue, we call that the internet. Then you can fast forward and you can say, now how do I make applications portable? And I will turn round and tell you that containers on Linux with Kubernetes as orchestration is that glue layer. Now in order to make it so, just like TCP/IP, it wasn't enough to say TCP/IP you needed routing tables, you needed DNS, you needed name repository, you needed all those things. Similarly, you need all those here are called the scatlog and automation, so that's the glue layer that makes all of this work >> This is important, I love this conversation because I have been ranting on theCUBE for years. You nailed it. A new stack is developing and DNS's are old and internet infrastructure, cloud infrastructure at the global scale is seeing things like network effect, okay we see blockchain in token economics, databases, multiple databases, on structure day >> a new plethora of new things are happening that are building on top of say HTTP >> [Arvind] Correct! >> And this is the new opportunity. >> This is the new platform which is emerging and it is going to enable business to operate, as you said, >> at scale, to be very digital, to be very nimble. Application life cycles aren't always going to be months, they're going to come down to days and this is what gets enabled >> So I what you to give your opinion, personal or IBM or whatever perspective because I think you nailed the glue layer on Kubernetes, Docker, this new glue layer that and you made references to, things like HTTP and TCP, which changed the industry landscape, wealth creation, new brands emerged, companies we never heard of emerged out of this and we're all using them today. We expect a new set of brands are going to emerge, new technologies are going to emerge. In your expert opinion, how gigantic is this swarm of new innovation going to be? Just, 'cause you've seen many ways before. In you view, your minds eye, what are you expecting? >> Share your insight into how big of a shift and wave is this going to be and add some color to that. >> I think that if I take a shorter and then a longer term view. in the short term, I think that we said, that this is in the order of $100 billion, that's not just our estimate, I think even Gartner has estimated about the same number. That will be the amount of opportunity for new technologies in what we've been describing. And that is I think short term. If I go longer term, I think as much as a half but at least a fourth of the complete IT market is going to shift round to these technologies. So then the winners of those that make the shift and then by conclusion, the losers are those who don't make the shift fast enough. If half the market moves, that's huge. >> It's interesting we used to look at certain segments going back years just company, oh this company's replatformizing, >> replatforming their op lift and shift and all this stuff. What you're talking about here is so game changing because the industry is replatforming >> That's correct. It's not a company. >>It's an industry! That's right. And I think the internet era of 1995, to put that point, is perhaps the easiest analogy to what is happening. >> Not the emergence of cloud, not the emergence of all that I think that was small steps. >> What we are talking about now is back to the 1995 statement >> [John] Every vertical is upgrading their stack across what from e-commerce to whatever. >> That's right. >> It's completely modernizing. >> Correct. Around cloud. >> What we call digital transformation in a sense, yes >> I'm not a big fan of the word but I understand what you mean. Great insight Arvind, thanks for coming on theCUBE and sharing. We didn't even get to some of the other good stuff. But IBM and Red Hat doing some great stuff obviously foundational, I mean, Red Hat, Tier one, first class citizen in every single enterprise and software environment you know, now OpenSource runs the world. You guys are no stranger to Linux being the first billion dollar investment going back >> so you guys have a heritage there so congratulations on the relationship. >> I mean 18 years ago, if I remember 1999. >> I love the strategy, hybrid cloud here at IBM and Red Hat. This is theCUBE, bringing all the action here in San Francisco. I am John Furrier, John Troyer. More live coverage. Stay with us, here in theCUBE. We'll be right back. (upbeat music)