>> (soft upbeat music) >> Announcer: From around the globe, it's the cube with digital coverage of Ansible Fest 2020, brought to you by RedHat. >> Hello, welcome to the cubes coverage of Ansible Fest 2020. We're not in person, we're virtual. I'm John Furrier , your host of theCube. We've got a great power panel here of RedHat engineers. We have Brad Thorton, Senior Principle Software Engineer for Ansible networking. Adam Miller, Senior Principle Software Engineer for Security and Jill Rouleau, who's the Senior Software Engineer for Ansible Cloud. Thanks for joining me today. Appreciate it. Thanks for coming on. >> Thanks. >> Good to be here. >> We're not in person this year because of COVID, a lot going on but still a lot of great news coming out of Ansible Fest this year. Last year, you guys launched a lot since last year. It's been awesome. Launched the new platform. The automation platform, grown the collections, certified collections community from five supported platforms to over 50, launched a lot of automation services catalog. Brad let's start with you. Why are customers successful with Ansible in networking? >> Why are customers successful with Ansible in networking? Well, let's take a step back to a bit of classic network engineering, right? Lots of CLI interaction with the terminal, a real opportunity for human error there. Managing thousands of devices from the CLI becomes very difficult. I think one of the reasons why Ansible has done well in the networking space and why a lot of network engineers find it very easy to use is because you can still see an attack at the CLI. But what we have the ability to do is pull information from the same COI that you were using manually, and showed that as structured data and then let you return that structured data and push it back to the configuration. So what you get when you're using Ansible is a way to programmatically interface and do configuration management across your entire fleet. It brings consistency and stability, and speed really to network configuration management. >> You know, one of the big hottest areas is, you know, I always ask the folks in the cloud what's next after cloud and pretty much unanimously it's edge, and edge is super important around automation, Brad. What's your thoughts on, as people start thinking about, okay, I need to have edge devices. How does automation play into that? And cause networking, edge it's kind of hand in hand there. So what's your thought on that? >> Yeah, for sure. It really depends on what infrastructure you have at the edge. You might be deploying servers at the edge. You may be administering IOT devices and really how you're directing that traffic either into edge compute or back to your data center. I think one of the places Ansible is going to be really critical is administering the network devices along that path from the edge, from IOT back to the data center, or to the cloud. >> Jill, when you have a Cloud, what's your thoughts on that? Because when you think about Cloud and Multicloud, that's coming around the horizon, you're looking at kind of the operational model. We talked about this a lot last year around having Cloud ops on premises and in the Cloud. What should customers think about when they look at the engineering challenges and the development challenges around Cloud? >> So cloud gets used for a lot of different things, right? But if we step back Cloud just means any sort of distributed applications, whether it's on prem in your own data center, on the edge, in a public hosted environment, and automation is critical for making those things work, when you have these complex applications that are distributed across, whether it's a rack, a data center or globally. You need a tool that can help you make sense of all of that. You've got to... We can't manage things just with, Oh, everything is on one box anymore. Cloud really just means that things have been exploded out and broken up into a bunch of different pieces. And there's now a lot more architectural complexity, no matter where you're running that. And so I think if you step back and look at it from that perspective, you can actually apply a lot of the same approaches and philosophies to these new challenges as they come up without having to reinvent the wheel of how you think about these applications. Just because you're putting them in a new environment, like at the edge or in a public Cloud or on a new, private on premise solution. >> It's interesting, you know, I've been really loving the cloud native action lately, especially with COVID, we're seeing a lot of more modern apps come out of that. If I could follow up there, how do you guys look at tools like Terraform and how does Ansible compare to that? Because you guys are very popular in the cloud configuration, you look at cloud native, Jill, your thoughts. >> Yeah. So Terraform and tools like that. Things like cloud formation or heat in the OpenStack world, they do really, really great at things like deploying your apps and setting up your stack and getting them out there. And they're really focused on that problem space, which is a hard problem space that they do a fantastic job with where Ansible tends to come in and a tool like Ansible is what do you do on day two with that application? How do you run an update? How do you manage it in the longterm of something like 60% of the workloads or cloud spend at least on AWS is still just EC2 instances. What do you do with all of those EC2 instances once you've deployed them, once they're in a stack, whether you're managing it, whatever tool you're managing it with, Ansible is a phenomenal way of getting in there and saying, okay, I have these instances, I know about them, but maybe I just need to connect out and run an update or add a package or reconfigure a service that's running on there. And I think you can glue these things together and use Ansible with these other stack deployment based tools really, really effectively. >> Real quick, just a quick followup on that. what's the big pain point for developers right now when they're looking at these tools? Because they see the path, what are some of the pain points that they're living right now that they're trying to overcome? >> I think one of the problems kind of coincidentally is we have so many tools. We're in kind of a tool explosion in the cloud space, right now. You could piece together as as many tools to manage your stack, as you have components in your stack and just making sense of what that landscape looks like right now and figuring out what are the right tools for the job I'm trying to do, that can be flexible and that are not going to box me into having to spend half of my engineering time, just managing my tools and making sense of all of that is a significant effort and job on its own. >> Yes, too many may add, would choke in years ago in the big data search, the tools, the tool train, one we call the tool shed, after a while, you don't know what's in the back, what you're using every day. People get comfortable with the right tools, but the platform becomes a big part of that thinking holistically as a system. And Adam, this comes back to security. There's more tools in the security space than ever before. Talking about tool challenges, security is the biggest tool shed everyone's got tools they'd buy everything, but you got to look at, what a platform looks like and developers just want to have the truth. And when you look at the configuration management piece of it, security is critical. What's your thoughts on the source of truth when it comes into play for these security appliances? >> So these are... Source of truth piece is kind of an interesting one because this is going to be very dependent on the organization. What type of brownfield environment they've developed, what type of things that they rely on, and what types of data they store there. So we have the ability for various sources of truth to come in for your inventory source and the types of information you store with that. This could be tagged information on a series of cloud instances or series about resources. This could be something you store in a network management tool or a CMDB. This could even be something that you put into a privilege access management system, such as, CyberArk or hashivault. Like those are the things and because of Ansible flexibility and because of the way that everything is put together in a pluggable nature, we have the capability to actually bring in all of these components from anywhere in a brownfield environment, in a preexisting infrastructure, as well as new decisions that are being made for the enterprise as I move forward. And, and we can bring all that together and be that infrastructure glue, be that automation component that can tie all these disjoint loosely coupled, or complete disc couple pieces, together. And that's kind of part of that, that security posture, remediation various levels of introspection into your environment, these types of things, as we go forward, and that's kind of what we're focusing on doing with this. >> What kind of data is stored in the source of truth? >> I mean... So what type of data? This could be credential. It could be single use credential access. This could be your inventory data for your systems, what target systems you're trying to do. It could be, various attributes of different systems to be able to classify them ,and codify them in different ways. It's kind of kind of depending, be configuration data. You know, we have the ability with some of the work that Brad and his team are doing to actually take unstructured data, make it structured, bullet into whatever your chosen source of truth is, store it, and then utilize that to, kind of decompose it into different vendors, specific syntax representations and those types of things. So we have a lot of different capability there as well. >> Brad, you were mentioned, do you have a talk on parsing, can you elaborate on that? And why should network operators care about that? >> Yeah, welcome to 2020. We're still parsing network configuration and operational state. This is an interesting one. If you had asked me years ago, did I think that we would be investing development time into parsing with Ansible network configurations? I would have said, "Well, I certainly hope not. "I hope programmability of network devices and the vendors "really have their API's in order." But I think what we're seeing is network containers are still comfortable with the command line. They're still very familiar with the command line and when it comes time to do operational state assessment and health assessment of your network, engineers are comfortable going to the command line and running show commands. So really what we're trying to do in the parsing space is not author brand new parking and parsing engine ourselves, but really leverage a lot of the open source tools that are already out there bringing them into Ansible, so network engineers can now harvest the critical information from usher operational state commands on their network devices. And then once they've gotten to the structure data, things get really interesting because now you can do entrance criteria checks prior to doing configuration changes, right? So if you want to ensure a network device has a very particular operational state, all the BGP neighbors are, for example before pushing configuration changes, what we have the ability to do now is actually parse the command that you would have run from the command line. Use that within a decision tree in your Ansible playbook, and only move forward when the configuration changes. If the box is healthy. And then once the configuration changes are made at the end, you run those same health checks to ensure that you're in a speck can do a steady state and are production ready. So parsing is the mechanism. It's the data that you get from the parsing that's so critical. >> If I had to ask you real quick, just while it's on my mind. You know, people want to know about automation. It's top of mind use case. What are some of these things around automation and configuration parsing, whether it's parsing to other configuration manager, what are the big challenges around automation? Because it's the Holy grail. Everyone wants it now. What are the couches? where's the hotspots that needs to be jumped on and managed carefully? Or the easiest low hanging fruit? >> Well, there's really two pieces to it, right? There's the technology. And then there's the culture. And, and we talk really about a culture of automation, bringing the team with you as you move into automation, ensuring that everybody has the tools and they're familiar with how automation is going to work and how their day job is going to change because of automation. So I think once the organization embraces automation and the culture is in place. On the technology side, low hanging fruit automation can be as simple as just using Ansible to push the commands that you would have previously pushed to the device. And then as your organization matures, and you mature along this kind of path of network automation, you're dealing with larger pieces, larger sections of the configuration. And I think over time, network engineers will become data managers, right? Because they become less concerned about the network, the vendors specific configuration, and they're really managing the data that makes up the configuration. And I think once you hit that part, you've won at automation because you can move forward with Ansible resource modules. You're well positioned to do NETCONF for RESTCONF or... Right once you've kind of grown to that it's the data that we need to be concerned about and it could fit (indistinct) and the operational state management piece, you're going to go through a transformation on the networking side. >> So you mentioned-- >> And one thing to note there, if I may, I feel like a piece of this too, is you're able to actually bridge teams because of the capability of Ansible, the breadth of technologies that we've had integrations with and our ability to actually bridge that gap between different technologies, different teams. Once you have that culture of automation, you can start to realize these DevOps and DevSecOps workflow styles that are top of everybody's mind these days. And that's something that I think is very powerful. And I like to try to preach when I have the opportunity to talk to folks about what we can do, and the fact that we have so much capability and so many integrations across the entire industry. >> That's a great point. DevSecOps is totally a hop on. When you have software and hardware, it becomes interesting. There's a variety of different equipment, on the security automation. What kind of security appliances can you guys automate? >> As of today, we are able to do endpoint management systems, enterprise firewalls, security information, and event management systems. We're able to do security orchestration, automation, remediation systems, privileged access management systems. We're doing some threat intelligence platforms. And we've recently added to the I'm sorry, did I say intrusion detection? We have intrusion detection and prevention, and we recently added endpoint security management. >> Huge, huge value there. And I think everyone's wants that. Jill, I've got to ask you about the Cloud because the modules came up. What use cases do you see the Ansible modules in for the public cloud? Because you got a lot of cloud native folks in public cloud, you've got enterprises lifting and shifting, there's a hybrid and multicloud horizon here. What's some of the use cases where you see those Ansible modules fitting well with public level. >> The modules that we have in public cloud can work across all of those things, you know. In our public clouds, we have support for Amazon web services, Azure GCP, and they all support your main services. You can spin up a Lambda, you can deploy ECS clusters, build AMI, all of those things. And then once you get all of that up there, especially looking at AWS, which is where I spend the most time, you get all your EC2 instances up, you can now pull that back down into Ansible, build an inventory from that. And seamlessly then use Ansible to manage those instances, whether they're running Linux or windows or whatever distro you might have them running, we can go straight from having deployed all of those services and resources to managing them and going between your instances in your traditional operating system management or those instances and your cloud services. And if you've got multiple clouds or if you still have on prem, or if you need to, for some reason, add those remote cloud instances into some sort of on-prem hardware load balancer, security endpoint, we can go between all of those things and glue everything together, fairly seamlessly. You can put all of that into tower and have one kind of view of your cloud and your hardware and your on-prem and being able to move things between them. >> Just put some color commentary on what that means for the customer in terms of, is it pain reduction, time savings? How would you classify their value? >> I mean, both. Instead of having to go between a number of different tools and say, "Oh, well for my on-prem, I have to use this. "But as soon as I shift over to a cloud, "I have to use these tools. "And, Oh, I can't manage my Linux instances with this tool "that only knows how to speak to, the EC2 to API." You can use one tool for all of these things. So like we were saying, bring all of your different teams together, give them one tool and one view for managing everything end to end. I think that's, that's pretty killer. >> All right. Now I get to the fun part. I want you guys to weigh in on the Kubernetes. Adam, if you can start with you, we'll start with you go in and tell us why is Kubernetes more important now? What does it mean? A lot of hype continues to be out there. What's the real meet around Kubernetes what's going on? >> I think the big thing is the modernization of the application development delivery. When you talk about Kubernetes and OpenShift and the capabilities we have there, and you talk about the architecture, you can build a lot of the tooling that you used to have to maintain, to be able to deliver sophisticated resilient architectures in your application stack, are now baked into the actual platform, so the container platform itself takes care of that for you and removes that complexity from your operations team, from your development team. And then they can actually start to use these primitives and kind of achieve what the cloud native compute foundation keeps calling cloud native applications and the ability to develop and do this in a way that you are able to take yourself out of some of the components you used to have to babysit a lot. And that becomes in also with the OpenShift operator framework that came out of originally Coral S, and if you go to operator hub, you're able to see these full lifecycle management stacks of infrastructure components that you don't... You no longer have to actually, maintain a large portion of what you start to do. And so the operator SDK itself, are actually developing these operators. Ansible is one of the automation capabilities. So there's currently three supported there's Ansible, there's one that you just have full access to the Golang API and then helm charts. So Ansible's specifically obviously being where we focus. We have our collection content for the... carries that core, and then also ReHat to OpenShift certified collection's coming out in, I think, a month or so. Don't hold me to the timeline. I'm shoving in trouble for that one, but we have those things going to come out. Those will be baked into the operator's decay that we fully supported by our customer base. And then we can actually start utilizing the Ansible expertise of your operations team to container native of the infrastructure components that you want to put into this new platform. And then Ansible itself is able to build that capability of automating the entire Kubernetes or OpenShift cluster in a way that allows you to go into a brownfield environment and automate your existing infrastructure, along with your more container native, futuristic next generation, net structure. >> Jill this brings up the question. Why don't you just use native public cloud resources versus Kubernetes and Ansible? What's the... What should people know about where you use that, those resources? >> Well, and it's kind of what Adam was saying with all of those brownfield deployments and to the same point, how many workloads are still running just in EC2 instances or VMs on the cloud. There's still a lot of tech out there that is not ready to be made fully cloud native or containerized or broken up. And with OpenShift, it's one more layer that lets you put everything into a kind of single environment instead of having to break things up and say, "Oh, well, this application has to go here. "And this application has to be in this environment.' You can do that across a public cloud and use a little of this component and a little of that component. But if you can bring everything together in OpenShift and manage it all with the same tools on the same platform, it simplifies the landscape of, I need to care about all of these things and look at all of these different things and keep track of these and are my tools all going to work together and are my tools secure? Anytime you can simplify that part of your infrastructure, I think is a big win. >> John: You know, I think about-- >> The one thing, if I may, Jill spoke to this, I think in the way that a architectural, infrastructure person would, but I want to try to really quick take the business analyst component of it as the hybrid component. If you're trying to address multiple footprints, both on prem, off prem, multiple public clouds, if you're running OpenShift across all of them, you have that single, consistent deployment and development footprint for everywhere. So I don't disagree with anything they said, I just wanted to focus specifically on... That piece is something that I find personally unique, as that was a problem for me in a past life. And that kind of speaks to me. >> Well, speaking of past lives-- >> Having me as an infrastructure person, thank you. >> Yeah. >> Well, speaking of past lives, OpenStack, you look at Jill with OpenStack, we've been covering the Cuba thing when OpenStack was rolling out back in the day, but you can also have private cloud. Where you used to... There's a lot of private cloud out there. How do you talk about that? How do people understand using public cloud versus the private cloud aspect of Ansible? >> Yeah, and I think there is still a lot of private cloud out there and I don't think that's a bad thing. I've kind of moved over onto the public cloud side of things, but there are still a lot of use cases that a lot of different industries and companies have that don't make sense for putting into public cloud. So you still have a lot of these on-prem open shift and on-prem OpenStack deployments that make a ton of sense and that are solving a bunch of problems for these folks. And I think they can all work together. We have Ansible that can support both of those. If you're a telco, you're not going to put your network function, virtualization on USC as to one in spot instances, right? When you call nine one one, you don't want that going through the public cloud. You want that to be on dedicated infrastructure, that's reliable and well-managed and engineered for that use case. So I think we're going to see a lot of ongoing OpenStack and on-prem OpenShift, especially with edge, enabling those types of use cases for a long time. And I think that's great. >> I totally agree with you. I think private cloud is not a bad thing at all. Things that are only going to accelerate my opinion. You look at the VM world, they talked about the telco cloud and you mentioned edge when five G comes out, you're going to have basically have private clouds everywhere, I guess, in my opinion. But anyway, speaking of VMware, could you talk about the Ansible VMware module real quick? >> Yeah, so we have a new collection that we'll be debuting at Ansible Fest this year bore the VMware REST API. So the existing VMware modules that we have usually SOAP API for VMware, and they rely on an external Python library that VMware provides, but with these fare 6.0 and especially in vSphere 6.5, VMware has stepped up with a REST API end point that we find is a lot more performance and offers a lot of options. So we built a new collection of VMware modules that will take advantage of that. That's brand new, it's a lighter way. It's much faster, we'll get better performance out of it. You know, reduced external requirements. You can install it and get started faster. And especially with these sphere seven, continuing to build on this REST API, we're going to see more and more interfaces being exposed so that we can take advantage. We plan to expand it as new interfaces are being exposed in that API, it's compatible with all of the existing modules. You can go back and forth, use your existing playbooks and start introducing these. But I think especially on the performance side, and especially as we get these larger clouds and more cloud deployments, edge clouds, where you have these private clouds and lots and lots of different places, the performance benefits of this new collection that we're trying to build is going to be really, really powerful for a lot of folks. >> Awesome. Brad, we didn't forget about you. We're going to bring you back in. Network automation has moved towards the resource modules. Why should people care about them? >> Yeah. Resource modules, excuse me. Probably I think having been a network engineer for so long, I think some of the most exciting work that has gone into Ansible network over the past year and a half, what the resource modules really do for you is they will reach out to network devices. They will pull back that network native, that vendor native configuration. While the resource module actually does the parsing for you. So there's none of that with the resource modules. And we returned structured data back to the user that represents the configuration. Going back to your question about source of truth. You can take that structure data, maybe for your interface CONFIG, your OSPF CONFIG, your access list CONFIG, and you can store that data in your source of truth under source of truth. And then where you are moving forward, is you really spend time as every engineer managing the data that makes up the configuration, and you can share that data across different platforms. So if you were to look at a lot of the resource modules, the data model that they support, it's fairly consistent between vendors. As an example, I can pull OSPF configuration from one vendor and with very small changes, push that OSPF configuration to a different vendor's platform. So really what we've tried to do with the resource modules is normalize the data model across vendors. It'll never be a hundred percent because there's functionality that exists in one platform that doesn't exist and that's exposed through the configuration, but where we could, we have normalized the data model. So I think it's really introducing the concept of network configuration management through data management and not through CLI commands anymore. >> Yeah, that's a great point. It just expands the network automation vision. And one of the things that's interesting here in this panel is you're talking about, cloud holistically, public multicloud, private hybrid security network automation as a platform, not just a tool, we're still going to have all kind of tools out there. And then the importance of automating the edge. I mean, that's a network game Brad. I mean, it's a data problem, right? I mean, we all know about networking, moving packets from here to there, but automating the data is critical and you give have bad data and you don't have... If you have misinformation, it sounds like our current politics, but you know, bad information is bad automation. I mean, what's your thoughts? How do you share that concept to developers out there? What should they be thinking about in terms of the data quality? >> I think that's the next thing we have to tackle as network engineers. It's not, do I have access to the data? You can get the data now for resource modules, you can get the data from NETCONF, from RESTCONF, you can get it from OpenConfig, you can get it from parsing. The question really is, how do you ensure the integrity and the quality of the data that is making up your configurations and the consistency of the data that you're using to look at operational state. And I think this is where the source of truth really becomes important. If you look at Git as a viable source of truth, you've got all the tools and the mechanisms within Git to use that as your source of truth for network configuration. So network engineers are actually becoming developers in the sense that they're using Git ops to worklow to manage configuration moving forward. It's just really exciting to see that transformation happen. >> Great panel. Thanks for everyone coming on, I appreciate it. We'll just end this by saying, if you guys could just quickly summarize Ansible fast 2020 virtual, what should people walk away with? What should your customers walk away with this year? What's the key points. Jill, we'll start with you. >> Hopefully folks will walk away with the idea that the Ansible community includes so many different folks from all over, solving lots of different, interesting problems, and that we can all come together and work together to solve those problems in a way that is much more effective than if we were all trying to solve them individually ourselves, by bringing those problems out into the open and working together, we get a lot done. >> Awesome, Brad? >> I'm going to go with collections, collections, collections. We introduced in last year. This year, they are real. Ansible2.10 that just came out is made up of collections. We've got certified collections on automation. We've got cloud collections, network collections. So they are here. They're the real thing. And I think it just gets better and deeper and more content moving forward. All right, Adam? >> Going last is difficult. Especially following these two. They covered a lot of ground and I don't really know that I have much to add beyond the fact that when you think about Ansible, don't think about it in a single context. It is a complete automation solution. The capability that we have is very extensible. It's very pluggable, which has a standing ovation to the collections and the solutions that we can come up with collectively. Thanks to ourselves. Everybody in the community is almost infinite. A few years ago, one of the core engineers did a keynote speech using Ansible to automate Philips hue light bulbs. Like this is what we're capable of. We can automate the fortune 500 data centers and telco networks. And then we can also automate random IOT devices around your house. Like we have a lot of capability here and what we can do with the platform is very unique and something special. And it's very much thanks to the community, the team, the open source development way. I just, yeah-- >> (Indistinct) the open source of truth, being collaborative all is what it makes up and DevOps and Sec all happening together. Thanks for the insight. Appreciate the time. Thank you. >> Thank you. I'm John Furrier, you're watching theCube here for Ansible Fest, 2020 virtual. Thanks for watching. (soft upbeat music)

>>Live from Atlanta, Georgia. It's the cube covering Ansible Fest 2019 brought to you by red hat. >>Welcome back. This is the cubes coverage of Ansible Fest 2019. I'm Stu Miniman. My cohost of the week is John farrier. And this is the cube insights where we share our independent analysis, break down what we're hearing from the community, what we've learned from all of our interviews. John, uh, you know, we knew community would be a big portion of what we did here. Uh, culture and collaboration were things that we talked a lot about that wasn't necessarily what I thought I would be hearing. Uh, you've been talking a lot about how observability and automation are the, the huge wave. We've seen, you know, acquisitions, we've seen IPOs, we've seen investments. So, you know, your, your, your take here as we're wrapping up. Sure, sure. Last to, um, as we said in our opening in the big scene here has been automation for all that's Ansible's kind of rap because they're, you know, they're announcing their main news ants, full automation platform. >>So that's the big news. But the bottom line is where this emerged from was configuration management and supple started out as a small little project that's solved a very specific problem. It solved configuring devices and all the automation around, you know, opening up ports and things that that were important beyond the basic static routing, the old web one. Dot. O web 2.0 model. And it grew into a software abstraction layer for automating because a lot of that stuff, the mundane tasks in configuring networks and servers frankly were boring and redundant. Everyone hated them patches. So easy ground to automate. And I think, um, it's evolved a lot into dev ops because with the cloud scale more devices, just because software's defining everything, it doesn't mean servers go away. So we know that is more servers is more storage, it's in the cloud, it's on premise, it's cloud operations. >>So automation I think, and I'm, my prediction is is that automation will be as big of a category as observability was. And remember we kinda missed observability we saw it as important. We've covered all those companies, but especially in network management on steroids with the cloud. But look what happened. Multiple companies when public big companies getting sold for billions of dollars, a lot of M and a activity observability is the most, one of the most important areas of cloud 2.0 it's not just some white space around network management. The data is super important. I think automation is going to grow into a highly competitive, highly relevant in the lucrative marketplace for companies and I think Ansible is in pole position to capture that with red hat and now red hat part of IBM. I think automation is going to be very big land grab. It's going to be where the value is created. >>I think observability and automation are going to go hand in hand and I think AI and data, those are the things programming infrastructure revolve around those two spheres. I think it is going to be super important. I think that's why the cube is here. We smelled it out, we sniffing it and we can see. We can touch it and the community here, they're doing it. They're there actually have proof points. Yup. These, this community is demonstrating that the process is going to be more efficient. The technology works and the people are transforming and that is a key piece with automation. People can work on other things and it's certainly changing the game. So all three aspects of digital transformation are in lockstep and, and, and, and expanding rapidly. >>Yeah. John, I would expect nothing less than a bold prediction from you on this space. You know, it's only $150 million acquisition, which is really small compared to a lot of the acquisitions that we see these as heck. You know, red hat Ansible didn't get talked about all that much when you know, IBM went and spent over $30 billion for red hat. But absolutely automation is so important that infrastructure is code movement that we've been tracking for quite a long time helps enable automation across the entire stack. A lot of discussion this week here, networking and security, two areas that we know need to make progress and we need to have, you know, less errors. We need to be able to make changes faster and cloud. We just as in the infrastructure space, that configuration management, we need to be able to simplify things. Absolutely. One of the things that will slow down the growth of cloud is that if we can't simplify those environments, so the same type of tooling and where Ansible is trying to, you know, span between the traditional environments and the cloud is to get this working in the containerization cloud native Kubernetes world that we're living in. >>Yeah, and it's still, you're right on, I mean this is the analysis and that it's spot on. I think one of the nuances in the industry landscape is a, when red hat got acquired by IBM for a massive amount of money, everyone's scratching their heads. But if you think about what red hat has done and you know I'm a real big fan of red hat, you are too. They're smart. They make great acquisitions, Ansible, not a big payout. They had coral West, they, they got open shifts there. They're the decouple their operating systems people. They get the notion of systems architecture. I think red hat is executed brilliantly in that systems mindset, which is perfect for cloud computing. I think Arvin Krishna at IBM really understood the impact of red hat and when I talked to him at red hat summit two years ago, right before the acquisition, he had the twinkle in his eye when I asked him about red at, because you can see them connecting the dots. Red hat brings a lot to the table and if IBM doesn't screw up red hat, then they're going to do well and we talk about red hat not screwing up Ansible and they didn't. Now part of it, if IBM doesn't screw up the red hat acquisition, let red hat bring that systems mindset in. I think IBM could use red has a beautiful way to bring a systems architecture into cloud, cloud native and really take a lot of territory down these new cloud native apps. >>John F automation is a force multiplier for customers and Ansible has that capability to be a force multiplier for red hat. When you look at the ecosystem they're building out here, the Ansible automation platform really helps it get customers more in lock steps. So you know, I was talking to the people and said, Oh, you know, AWS has an update. Oh we need to roll the entire core and put out another version. I can't wait for that. I need to be able to decouple the partner activity, which by the way, they talked about how the disk project is the six most popular in get hub decoupling collections might actually put them lower on the on the list, but that's okay because they're solving real customer problems. And it's interesting, John, we talk about the ecosystem here. One of, there's only a couple of other companies other than red hat that can commit without having to go through approval. Microsoft is one of them. So you talk about the, the collaboration, the ecosystem here where this can be, >>let's do the, the thing about Ansible is that it's a double edged sword. There value is also an Achilles heel. And one of the critical analysis that I have is, is that they're not broad enough yet. On and there and there. I won't say misunderstood the customers here in the community, they totally get it. Everyone here loves Ansible. The problem is is that in the global landscape of the industry, they're tiny red hat needs to bring this out faster. I think IBM has to get animal out there faster because they have all the elements kind of popping right now. You got community, very strong customer base, loyal and dynamic. You got champions developing. That's classic sign of success. They got a great product, perfectly fit for this glue layer, this integration layer, you know, below containers and maybe you can even sitting above containers depending on how you look at it. And then finally the ecosystem of partners. Not yet fully robust, but all the names are here. Microsoft, Cisco net app F five kind of feels like VMworld on a small scale. They have to up level it. I think that's the critical problem I see with with these guys is that it's almost too good and too small. >>Yeah. Uh, you know, when I look back at when red hat made the acquisition, there were a handful of companies, most of them embracing open source as to which configuration management tool you're going to do. Ansible did well against them and red hat helped make them the category leader in this space. There is a different competitive landscape today. Just public cloud. You know, Ansible can help, but there's some customers that would be like, Oh, I've got different tooling and it doesn't fit into what I'm doing today. So there's some different competitors in the landscape and we know John, every customer we've talked to, they've got a lot of tools. So how does Ansible get mind share inside the company? They had some great stories that we heard both on the Q from like ING and the Southern company as well as in the keynotes from JP Morgan where they're scaling out, they're building playbooks, they're doing this, but you know, this is not, you know, it's not just push a button to get all of this rolled out. >>The IBM marketing should help here. And if I'm, you know, um, uh, the marketing team at IBM, I'd be like all over this because this is a, a game changer because this could be a digital transformation ingredient. The people equation. The problem is, is that again, IBM to embrace this and Ansible has that glue layer integration. This could be great. Now the benefit to them, I think they're tailwind is they can solve a lot of problems. One nuance from the show that I learned was, okay, configuration management, dev ops, great. The network automation is looking good. Security is a huge opportunity because if you think about the basic blocking and tackling patches, configuration, misconfigurations, automation plays perfect role. So to get beachhead in the enterprise as an extraction layer is to own and dominate those basics. Because think about the big hacks. Capitol one, misconfigured firewall to an S three bucket, that wasn't Amazon's fault, but the data on Amazon, this is automation can solve a lot of these problems, patches, malware, vulnerabilities, the adversaries are going to be all over that. >>So I think the security piece, huge upside position, Ansible and red hat as an abstraction layer to solve those basic problems rather than overselling it could be a great strategy. I think they're doing a good job with that. Uh, it totally, you know, built on simplicity and modularity. Uh, this, this tooling is something that it can sit lots of places in the organization, uh, and help that cultural communication. Uh, I was a bit critical of, uh, you know, enterprise collaboration, uh, that, that top down push that you'd get. Um, but here, you know, you've got a tool that uh, as we, we just had on our final interview with, uh, Pirog, you know, developers, they didn't build this for developers, but developers are embracing it. The infrastructure people are embracing it. It gives a sense of some why we here to why we're here is I think Ansible fast as a community event, which we love. >>But two, I think this is early, you know, days in the Canadian, the coal mine and saying that the Ansible formula for automation is going to be a growth year. That's my prediction. And we have data to back it up. If you look at our our community and the folks out in the cube alumni know no that when we reach out to them and get some data. But here's what supports why I think the automation thing with Ansible and red hat is relevant because it applies what we just talked about. The number one thing that came back from the community stew was focused efforts on better results. Automation from time efficiency days, hours to minutes check. Security is absolutely a top driver for automation. That's a tailwind. The job satisfaction issue is not like a marketing feel. Good thing. People actually liked their jobs when they have to, don't have to come in on the weekends. >>So this automation does align with that. And finally infrastructure and developers re-skilling with new capabilities and new things. Is it just an uplift? So those are the drivers driving the automation. That's why RPA is so hot and this is a critical foundation in my opinion. So you know Ansible's is the leading the wave here in this new automation wave and I think it's going to be a big part because it's controlling the plumbing. Yeah, John wanted the machinery. Johnny is the, the, the future of work. We know that automation is going to be hugely important. You mentioned >>RPA, a huge one. I had an interview with the associate professor from Syracuse university or they're teaching this to education. It's not just, Oh Hey you got to go learn coding and learn this programming language. No, we need to have that. That combination of the business understanding and the technology and automation can sit right at that intersection. What's your big learning point? What did you take away? Yeah, so it is, it's that point here that this is not just to some, you know, cool little tool on the side. This is something you John, we've talked at many shows. Software can actually be a unifying factor inside companies to help build platforms and for customers to help them collaborate and work together. This a tool like Ansible isn't just something that is done tactically but strategically, you know, gets everyone on the same page enables that collaboration isn't just another channel of you know, some other thing that a, I don't want to have to deal with it. >>It helps me get my job better. Increases that job satisfaction. That's so hugely important as to if you think about the digital transformation form of the people, process technology, how many interviews have we done, how many interviews have we done, a companies we've talked to where they have the great product and on the process side to address the process. They have the tech but they fail on the people side. It's the cultural adoption, it's the, it's the real enablement and I think Ansible's challenge is to take the platform, the capabilities of their, of their, of their software, launch the platform and create value because if they're not enabling value out of the platform that does not cross check with what platforms are supposed to do, which is create value. And John, the thing I want to look for when we come back to this show next year is how much are they allowing customers delivered through data? >>When we heard from their engineering division here, okay, the platforms, the first piece, but how do I measure internally and how do I measure against our peers? We know that that people want to have, there's so much information out there. How am I doing? Am I, where am I on my the five, five step progression and adoption of automation and you know, Hey, am I doing good against my competition or are they smoking me? Well? That's the metrics with the insight piece and tying it to the rail. Now people can say, look, I just saved a bunch of money. I saved some time. That's the business impact and I think you know when you have the KPIs and you had the analysts to back it up, good things will happen. Students been great. All right, John, always a pleasure to catch up with you. We got lot more here toward the second half of 2019 a big thanks to the whole community for of course watching this here at antelopes Fest. Check out the cube.net for all the upcoming shows. Thank you to our whole production team and to our hosts. Red hat for giving this beautiful set right in the middle of the show. And thanks as always for watching the cube.

>> From Seattle. Washington. It's the key you covering Goob Khan and Cloud Native Con North America. Twenty eighteen. Brought to you by Red Hat, the Cloud Native Computing Foundation and its ecosystem partner. >> Okay. Welcome back. It runs the cubes. Live coverage of three days Wall to wall here at Koop Khan and Cloud Native Khan, twenty eighteen in Seattle, where day three only actions happening. Mr Keep John for was to Minuteman where you have bread. French Compton, Tina. Director, Technical Market had read, had breaking down the container storage trends and directions. Costly containers are super important. That's happened. Communities has happened. Now. New things were happening around a lot of innovation. Thanks for coming on the Q. Appreciate it. >> Thanks for having me back. >> So what's the state of the art of containers of trends? Some of the market directions? What's going on around containers? >> Well, here at this show, of course, it's been all about service mesh. Right is Theo. Service mesh, dynamically dynamic discovery, dynamic invocation of services. But all of those things Well, a certain percentage of those things, according to Keynote, require some type of persistent so eso yet service message, service meshes and persistence. >> So storage is a big part of the networking and compute all working together. The cloud that's been a big part of it. What's what's important here in this show? What's going on this week. That's really impacting that piece of it. That container in storage you mentioned state versus stateless work area stateless is to find people from persistence in state become important and applications. How much conversation's been here this week on that piece >> we'll talk about this week, and then I'll talk about the last couple of weeks this week. There, there. Couple of significant thing is going on. They're going to sort of unleash innovation in persistence as it pertains to the coup bernetti subsystem. First, of course, is a container storage inter. See, you know, today, all the all of the volume plug ins have been entry. You want to change. You know, some vendor wants to change their their storage capabilities. They need to re compile the binaries. Very slow. Very, very non agile. Of course, with the advent of the container storage interface, it's okay. Here's the common interface. All the all the volume plugging providers right to that interface so they could. Then they Khun Iterated to their heart's content without having to change the the entry >> source. So the impact is what? Speed, agility, >> agility of innovation, allowing all those guys t innovate Kind of the second thing. That's so that's man of discussion this week. Another thing's been a discussion you've seen in the in some of the sessions and stuff is the operator framework, you know, coming a champion by the Coral West guys, of course. Now part of Red hat, the operator framework in terms of effectively automating things that human operators would do for complex subsystems. Such a CZ storage. Eso basic installation based basic upgrades, you know, monitoring those services. So when you know something falls over, what do you do with that type of stuff? So I'd say C s I container storage interface as well as operator from me. Those are some of the things have been talked about this week. I still want to go back. Talk about last week, but go ahead. >> I wonder if you could tease this out a little before. So, you know, lost five years. You know, container ization, Cooper Netease. You know, massive change the way we think about architectures. Things like networking in storage. I have often been the anchor to kind of hold us down to be ableto make changes faster. Virtual ization helped some, but you know, container ization. We're gonna have to fix some of these same things. What conversations you're having with customers, You know, give us the latest on the, you know, the state versus state falls we heard in the keynote. It was They said forty percent of deployments have, you know, st full applications out there spending on numbers. And, you know, it's definitely has been growing. And at least I can do it as opposed to, you know, two years ago, it was like, Okay, we're doing containers, but we're just going to stateless for now, and we'll try to figure out what architectures goingto work. Even a year ago at this show, I heard in the back rooms there were lots of arguments as to which one of the storage projects was going to lead and seems seems like we're getting some maturity. I hope we hope to give us some visibility is where we are, and you know what's working and what still needs to be done. >> So although the industry talks about serve earless there, not yet talking about data lists, the or storage lists. I mean, you know, if we threw out the basic principle of data gravity data is the sun around which applications services rotate And so even I mean, even stateless aps stateless app Still do I owe frequently? The io of stateless apse is, you know, be arrest Will puts and gets to an object store that actually brings me. So let's let's talk about let's unpack the stateless and then let's go to St ful. So I'm gonna come back. Tio some of the conversations. A couple of weeks ago, Red had announced the acquisition of Nuba and Israeli Company. So when you think about what new Bob Plus sef due to provide stateless aps with a common set of Davis, a common set of David data services across the hybrid and multi cloud so those stateless app saying, Okay, I'm going to do I'm going to rest well puts and gets. But, man, it's complicated. If I'm gonna have to develop to various proprietary protocols I've got, you know, the is your blob protocol. I've got a W. S s three. I'm talking Teo Google persistent disc. And then if I want to run hybrid, I'm also talking to SEF objects storage on premises. And if I'm a developer I'm thinking, man, Wouldn't it be nice if I had a common set of David data services, including common protocol to talkto all of those different cloud storage back end? So, Nuba some people kind of call it a cloud storage controller provides that kind of common data services. So things like common FBI protocol? Um, things like mirroring. So you you want to write, right Once you're uprights once and it smeared across the various cloud object storage back ends to facilitate easy migration. The second one I wanna uproot to move over here. Your data is already there. So that's, uh that's a couple of reasons. And some of the conversation from a couple weeks ago about how Nuba plus self are helping stateless aps get Teo hybrid and multi cloud >> this. I think that is a great point. You have a hybrid cloud and multi cloud coming around the corner, which is about choice, Right? But see, I CD pipe lining of having a consistent developer environment clearly is one of the main benefits we're seeing in this community here. Okay, I got some sulfur developers with crank teams move around that consistency, no matter where were the environment is just really good goodness. Their storage is interesting and data is that because you're right, the sun is the data and every is orbiting around it. That's the Holy Grail. This is what people want. They want addressable data. They wanted real time. They wanna have an access. They don't want to do all this code to configure manage data, and it's complicate. Got data warehouses? You got time. Siri's data so date is getting more complicated, but it needs to be simple. So this is kind of challenge of the industry. How are you guys seeing that with open ship? How is your container piece fit in? How do you guys make that easy for customers to say? Look, I want to have that data like I wanted intelligent, that brick of access to data. So my abs don't have to do all the heavy lifting almost like Dev ops for data. It's like day tops, like I need to have programmable data on the absolutely which, which have thoughts on that. >> So first I wanna I wanna address that in two ways. The first is about open shipped itself that what you described is in fact, the sweet spot of what open shift is providing a common set of Cooper Nettie Services. Plus. See, I see the pipeline services for developers and operation staff independent of your cloud infrastructures. So whether open shift is running on top of a heavy west, whether it's running on top of his your whether it's running on top of the G, C. P. Whether it's running on premises on bare metal, you know, common set of cou bernetti services and CD pipeline services. Okay, that so what you described there's wanted to just highlight that That is open ship hybrid multi >> valuable check. That's awesome data >> now coming down. Coming down to data. So, in fact, open shift container storage is the mirror analog to open shift for that, providing a common set of Cooper Netease volume services. Independent of what? The storage substrate. ID. So think about it. If you're If you're inside of eight of us, you've got CBS is what's you know? When in Rome, act as the Romans. You've got E. B s there when you're inside of eight of us. Well, the type of communities volumes service of the CBS provides natively differed them for instance, when you're on premises and it's surfacing via and NFS plug in, maybe different. Likewise. We're inside of a CZ. You're with your persistent disco, so open shift container storage device the same type of abstraction Lee are providing a common set of cou bernetti communities volumes services independent of what? The storage server layer is so >> cool you guys was tracked away the complexity. So the APP developer doesn't do anything about storage on those discreet platforms, >> doesn't know anything about storage and provides a common set of services instead of Well, let's see, this is running on this cloud. I don't have the have a different set of services, so common set of services. >> So one of things I love about talking right out of the shows is you actually have a lot of customers that are doing this way. Actually, we spoke to one of your customers yesterday. Talk about how you know communities is helping them create sustainable data centers over in Europe. In the Nordics, especially so communities is awesome. But what's really awesome is the things that we can do on top of it. I wonder if you've got, you know, help connect some of this toe. You know, your customers really things, you know? How does this, you know, change the game? How does it change their teams? You know, what can you share with us? >> One of things that I can't. What's what's top of mind. So what's not top of mind for me at the moment is you know what kind of knew how their reinventing the world what is top of mind with me right now? We've just been studying. Our our results is we look back and this is a little bit of a A Okay? It's a trend, but it's a different kind of friend you're talking about. In the last six quarters, we've had six hundred percent growth with open ship container storage. Um, so And now we send last six quarters were also at a point. Now we're seeing some of those same folks from the Nordics here. You're describing that are coming back now, you know, they have experimented on, So there are some There are Cem Cem cruise ship. There's a cruise ship company that is deployed this on on ships. What we're now seeing. What's very gratifying for us is they're coming back now for a second pass. Now, a year into it, it's okay. Clearly, it must be providing enough value that you come back. Okay. I want to buy this for another ship or more shifts. That's gratifying for us. The first year was, let's see. Let's try this uber Netease, this open ship container store stuff out. But, you know, coming back to the trough for another take, It's good for us. >> And what's going around the corner? He opens shifting, doing great. I love this abstraction layer we're seeing for the first time in the industry, clear visibility and a real value proposition. When I were joking yesterday, you know, we were at open stack years ago, or even Cube con three years ago. We would ask the question If you had a magic wand, what would you hope to have happened? It's actually some of the things that are actually happening. I mean, clean, heavy lifting is gone, and all the developer side consistency, productivity, better advantage on the application development side and then taking away all the hassles of having that she trained people on multiple clouds. So this is kind of happening. What's next? So what's the next next, uh, bowling pin to fall down? What's the, you know, Hit the front ten. What's next? What's going on? How do you guys see the next innovation around Open ship and storage containers, >> cloud independent data services and mobility. So independent of the clouds. And again, it's hybrid, too. So you don't want to be locked into your own cloud either. So cloud independent data services and mobility. So he said, Listen, I want to be I want to have a common de doop compression mirroring, but I want to sit in the layer above my clouds back to the data gravity thing. I want to ensure that my data is where I need it on different clouds. So I'm elevating to a new layer this this cloud storage controller, this this cloud independent set of data services way. Think that's where the pucks going? >> Yeah, I think the data date is critical, I think. Way said years ago. Data ops. There's a Dev ops model for data. You look at that way's not just putting into a data lake actually making it useful. Yeah, Thanks. Come on. Cuba. Here. Bringing all the data here. The Cube. We're sharing it here. Live in Seattle. Is our third year coop coming there from the beginning? That's the cubes coverage of Cloud Native Khan and Coop gone. Bring all the action here. Was red hot on the Cube. Back with more live coverage. Stay with us. Day three, three days ago off the wall. Coverage will be back after this short break.

>> Narrator: Live, from Las Vegas, it's theCUBE. Covering IBM Think, 2018. Brought to you by IBM >> Hello everyone, welcome back to theCUBE, we are here on the floor at IBM Think 2018 in theCUBE studios, live coverage from IBM Think. I'm John Furrier, the host of theCUBE, and we're here with Stefanie Chiras, who is the Vice President of Offering Management IBM Cognitive Systems, that's Power Systems, a variety of other great stuff, real technology performance happening with Power, it's been a good strategic bet for IBM. Stefanie, great to see you again, thanks for coming back on theCUBE. >> Absolutely, I love to be on, John, thank you for inviting me. >> When we we had a brief (mumbles) Bob Picciano, who's heading up Power and that group, one of the things we learned is there's a lot of stuff going on that's really going to be impacting the performance of things. Just take a minute to explain what you guys are offering in this area. Where does it fit into the IBM portfolio? What's the customer use cases? Where does that offering fit in? >> Yeah, absolutely. So I think here at Think it's been a great chance for us to see how we have really transformed. You know, we have been known in the market for AIX and IBMI. We continue to drive value in that space. We just GA'd on, yesterday, our new systems, based Power9 Processor chip for AIX and IBMI in Linux. So that remains a strong strategic push. Enterprise Linux. We transformed in 2014 to embrace Linux wholeheartedly, so we really are going after now the Linux base. SAP HANA has been an incredible workload where over a thousand customers run in SAP HANA. And boy we are going after this cognitive and AI space with our performance and our acceleration capabilities, particularly around GPUs, so things like unique differentiation in our NVLink is driving our capabilities with some great announcements here that we've had in the last couple of days. >> Jamie Thomas was on earlier, and she and I were talking about some of the things around really the software stack and the hardware kind of coming together. Can you just break that out? Because I know Power, we've been covering it, Doug Balog's been on many times. A lot of great growth right out of the gate. Ecosystem formed right around it. What else has happened? And separate out where the hardware innovation is and technology and what's software and how the ecosystem and people are adopting it. Can you just take us through that? >> Yeah, absolutely. And actually I think it's an interesting question because the ecosystem actually has happened on both sides of the fence, with both the hardware side and the software side, so OpenPOWER has grown dramatically on the hardware side. We just released our Power9 processor chip, so here is our new baby. This is the Power9. >> Hold it up. >> So this is our Power9 here, 8 billion transistors, 14 miles of wiring and 17 layers of metal, I mean it's a technology wonder. >> The props are getting so small we can't even show on the camera. (laughing) >> This is the Moore's Law piece that Jenny was talking about in her keynote. >> That's exactly it. But what we have really done strategically is changed what gets delivered from the CPU to more what gets delivered at a system level, and so our IO capabilities. First chip to market, delivering the first systems to market with PCIe Gen 4. So able to connect to other things much faster. We have NVLink 2.0, which provides nearly 10x the bandwidth to transport data between this chip and a GPU. So Jensen was onstage yesterday from NVIDIA. He held up his chip proudly as well. The capabilities that are coming out from being able to transport data between the power CPU and the GPU is unbelievable. >> Talk about the relationship with NVIDIA for a second, 'cause that's also, NVIDIA stocks up a lot of (mumbles) the bitcoin mining graphics card, but this is, again, one use case, NVIDIA's been doing very well, they're doing really well in IOT, self-driving cars, where data performance is critical. How do you guys play in that? What's the relationship with NVIDIA? >> Yeah, so it has been a great partnership with NVIDIA. When we launched in 2013, right at the end of 2013 we launched OpenPOWER, NVIDIA was one of the five founding members with us, Google, Mellanox, and Tyan. So they clearly wanted to change the game at the systems value level. We launched into that with we went and jointly bid with NVIDIA and Mellanox, we jointly bid for the Department of Energy when we co-named it Coral. But that came to culmination at the end of last year when we delivered the Summit and Sierra supercomputers to Oak Ridge and Lawrence Livermore. We did that with innovation from both us and NVIDIA, and that's what's driving things like this capability. And now we bring in software that exploits it. So that NVLink connection between the CPU and the GPU, we deliver software called PowerAI, we've optimized the frameworks to take advantage of that data transport between that CPU and GPU so it makes it consumable. With all of these things it's not just about the technology, it's about is it easy to consume at the software level? So great announcement yesterday with the capabilities to do logistic regression. Unbelievable, taking the ability to do advertising analytics, taking it from 70 minutes to 1 and 1/2. >> I mean we're going to geek out here. But let's go under the hood for a second. This is a really kind of a high end systems product, at the kind of performance levels. Where does that connect to the go to market? Who's the buyer of it? Is it OEMs? Is it integrators? Is it new hardware devices? How do I get involved and who's the target customer? And what kind of developers are you reaching? Can you just take us through that who's buying this product? >> So this is no longer relegated to the elite set. What we did, and I think this is amazing, when we delivered the Summit and Sierra, right? Huge cluster of these nodes. We took that same node, we pulled it into our product line as the AC922, and we delivered a 4 GPU air-cooled version to market. On December 22nd we GA'd, of last year. And we sold to over 40 independent clients by the end of 2017, so that's a short runway. And most of it, honestly, is all driven around AI. The AI adoption, and it's a cross enterprise. Our goal is really to make sure that the enterprises who are looking at AI now with their developer are ready to take it into production. We offer support for the frameworks on the system so they know that when they do development on this infrastructure, they can take it to production later. So it's very much driven toward taking AI to the enterprise, and it's all over. It's insurance, it's financial services sector. It's those kinds of enterprise that are using AI. >> So IO sensitive, right? So IOT not a target or maybe? >> So you know when we talk out to edge it's a little bit different, right? So the IOT today for us is driving a lot of data, that's coming in, and then you know at different levels-- >> There's not a lot of (mumbles) power needed at the edge. >> There is not, there is not. And it kind of scales in. We are seeing, I would say, kind of progression of that compute moving out closer. Whether or not it's on, it doesn't all come home necessarily anymore. >> Compute is being pushed to where the data is. >> Stefanie: Absolutely right. >> That's head room for you guys. Not a priority now because there's not an intense (mumbles) compute can solve that. >> Stefanie: That's right. >> All right, so where does the Cloud fit into it? You guys powering IBMs Cloud? >> So IBM Cloud has been a great announcement this year as well. So you've seen the focus here around AI and Cloud. So we announced that HANA will come on Power into the Cloud, specializing in large memory sets, so 24 terabyte memory sets. For clients that's huge to be able to exploit that-- >> Is IBM Cloud using Power or not? >> That will be in IBM Cloud. So go to IBM Cloud, be able to deploy an SAP certified HANA on Power deployment for large memory installs, which is great. We also announced PowerAI access, on Power9 technology in IBM Cloud. So we definitely are partnering both with IMB Cloud as well as with the analytics pieces. Data Science Experience available on Power. And I think it's very important, what you said earlier, John, about you want to bring the capabilities to where the data is. So things like a lot of clients are doing AI on prem where we can offer a solution. You can augment that with capabilities like Watson, right? Off prem. You can also do dev ops now with AI in the IBM Cloud. So it really becomes both a deployment model, but the client needs to be able to choose how they want to do it. >> And the data can come from multiple sources. There's always going to be latencies. So what about blockchain? I want to get to blockchain. Are you guys doing anything in the blockchain ecosystem? Obviously one complaint we've been hearing, obviously, is some of these cryptocurrency chains like Ethereum, has performance issues, they got projects coming out. A lot of open source in there. Is Power even puttin' their toe in the water with blockchain? >> We have put our toe in the water. Blockchain runs on Power. From an IBM portfolio perspective-- >> IBM blockchain runs on Power or blockchain, or other blockchains? >> Like Hyperledger. Like Hyperledger will run. So open source, blockchain will run on Power, but if you look at the IBM portfolio, the security capabilities in Z14 that that brings and pulling that into IBM Cloud, our focus is really to be able to deliver that level of security. So we lead with system Z in that space, and Z has been incredible with blockchain. >> Z is pretty expensive to purchase, though. >> But now you can purchase it in the Cloud through IBM Cloud, which is great. >> Awesome, this is the benefit of the Cloud. Sounds like soft layer is moving towards more of a Z mainframe, Power, backend? >> I think the IBM Cloud is broadening the capabilities that it has, because the workloads demand different things. Blockchain demands security. Now you can get that in the Cloud through Z. AI demands incredible compute strength with GPU acceleration, Power is great for that. And now a client doesn't have to choose. They can use the Cloud and get the best infrastructure for the workload they want, and IBM Cloud runs it. >> You guys have been busy. >> We've been busy. (laughing) >> Bob Picciano's been bunkered in. You guys have been crankin' out... love to do a deeper dive on this, Stefanie, and so we'd love to follow up with you guys, and we told Bob we would dig into that, too. Question I have for you now is, how do you talk about this group that you're building together? You know, the names are all internal IBM names, Power... Is it like a group? Do you guys call yourself like the modern infrastructure group? Is it like, what is it called, if you had to explain it to outside IBM, AIs easy, I know what AI team does. You're kind of doing AI. You're enabling AI. Are you a modern infrastructure? What is the pillar are you under? >> Yeah, so we sit under IBM systems, and we are definitely systems proud, right? Everything runs on infrastructure somewhere. And then within that three spaces you certainly have Z storage, and we empower, since we've set our sites on AI and cognitive workloads, internally we're called IBM Cognitive Systems. And I think that's really two things, both a focus on the workloads and differentiation we want to bring to clients, but also the fact that it's not just about the hardware, we're now doing software with things like PowerAI software, optimized for our hardware. There's magic that happens when the software and the hardware are co-optimized. >> Well if you look, I mean systems proud, I love that conversation because you look at the systems revolution that I grew up in, the computer science generation of the 80s, that was the open movement, BSD, pre-Linux, and then now everything about the Cloud and what's going on with AI and what I call the innovation sandwich with data in the middle and blockchain and AI as bread. >> Stefanie: Yep. >> You have all the perfect elements of automation, you know, Cloud. That's all going to be powered by a system. >> Absolutely. >> Especially operating systems skills are super imprtant. >> Super important. Super important. >> This is the foundational elements. >> Absolutely, and I think your point on open, that has really come in and changed how quickly this innovation is happening, but completely agree, right? And we'll see more fit for purpose types of things, as you mentioned. More fit for purpose. Where the infrastructure and the OS are driving huge value at a workload level, and that's what the client needs. >> You know, what dev ops proved with the Cloud movement was you can have programmable infrastructure. And what we're seeing with blockchain and decentralized web and AI, is that the real value, intellectual property, is going to be the business logic. That is going to be dealing with now a whole 'nother layer of programmability. It used to be the other way around. The technology determined >> That's right. >> the core decision, so the risk was technology purchase. Now that this risk is business model decision, how do you code your business? >> And it's very challenging for any business because the efficiency happens when those decisions get made jointly together. That's when real business efficiency. If you make one decision on one side of the line or the other side of the line only, you're losing efficiency that can be driven. >> And open is big because you have consensus algorithms, you got regulatory issues, the more data you're exposed to, and more horsepower that you have, this is the future, perfect storm. >> Perfect storm. >> Stefanie, thanks for coming on theCUBE, >> It's exciting. >> Great to see you. >> Oh my pleasure John, great to see you. >> You're awesome. Systems proud here in theCUBE, we're sharing all the systems data here at IBM Think. I'm John Furrier, more live coverage after this short break. All right.

>> Narrator: Live from Las Vegas, it's the Cube, covering IBM Think 2018, brought to you by IBM. >> We're back at IBM Think 2018. You're watching the Cube, the leader in live tech coverage. My name is Dave Vellante and I'm here with my co-host, Peter Burris. Ken King is here; he's the general manager of OpenPOWER from IBM, and Sumit Gupta, PhD, who is the VP, HPC, AI, ML for IBM Cognitive. Gentleman, welcome to the Cube >> Sumit: Thank you. >> Thank you for having us. >> So, really, guys, a pleasure. We had dinner last night, talked about Picciano who runs the OpenPOWER business, appreciate you guys comin' on, but, I got to ask you, Sumit, I'll start with you. OpenPOWER, Cognitive systems, a lot of people say, "Well, that's just the power system. "This is the old AIX business, it's just renaming it. "It's a branding thing.", what do you say? >> I think we had a fundamental strategy shift where we realized that AI was going to be the dominant workload moving into the future, and the systems that have been designed today or in the past are not the right systems for the AI future. So, we also believe that it's not just about silicon and even a single server. It's about the software, it's about thinking at the react level and the data center level. So, fundamentally, Cognitive Systems is about co-designing hardware and software with an open ecosystem of partners who are innovating to maximize the data and AI support at a react level. >> Somebody was talkin' to Steve Mills, probably about 10 years ago, and he said, "Listen, if you're going to compete with Intel, "you can copy them, that's not what we're going to do." You know, he didn't like the spark strategy. "We have a better strategy.", is what he said, and "Oh, strategies, we're going to open it up, "we're going to try to get 10% of the market. "You know, we'll see if we can get there.", but, Ken, I wonder if you could sort of talk about, just from a high level, the strategy and maybe go into the segments. >> Yeah, absolutely, so, yeah, you're absolutely right on the strategy. You know, we have completely opened up the architecture. Our focus on growth is around having an ecosystem and an open architecture so everybody can innovate on top of it effectively and everybody in the ecosystem can profit from it and gains good margins. So, that's the strategy, that's how we design the OpenPOWER ecosystem, but, you know, our segments, our core segments, AIX in Unix is still a core, very big core segment of ours. Unix itself is flat to declining, but AIX is continuing to take share in that segment through all the new innovations we're delivering. The other segments are all growth segments, high growth segments, whether it's SAP HANA, our cognitive infrastructure in modern day to platform, or even what we're doing in the HyperScale data centers. Those are all significant growth opportunities for us, and those are all Linux based, and, so, that is really where a lot of the OpenPOWER initiatives are driving growth for us and leveraging the fact that, through that ecosystem, we're getting a lot of incremental innovation that's occurring and it's delivering competitive differentiation for our platform. I say for our platform, but that doesn't mean just for IBM, but for all the ecosystem partners as well, and a lot of that was on display on Monday when we had our OpenPOWER summit. >> So, to talk about more about the OpenPOWER summit, what was that all about, who was there? Give us some stats on OpenPOWER and ecosystem. >> Yeah, absolutely. So, it was a good day, we're up to well over 300 members. We have over 50 different systems that are coming out in the market from IBM or our partners. Over 20 different manufacturers out there actually developing OpenPOWER systems. A lot of announcements or a lot of statements that were made at the summit that we thought were extremely valuable, first of all, we got the number one server vendor in Europe, Atos, designing and developing P9, the number on in Japan, Hitachi, the number one in China, Inspur. We got top ODMs like Super Micro, Wistron, and others that are also developing their power nine. We have a lot of different component providers on the new PCIe gen four, on the open cabinet capabilities, a lot of announcements made by a number of component partners and accelerator partners at the summit as well. The other thing I'm excited about is we have over 70 ISVs now on the platform, and a number of statements were made and announcements on Monday from people like MapD, Anaconda, H2O, Conetica and others who are leveraging those innovations bought on the platform like NVLink and the coherency between GPU and CPU to do accelerated analytics and accelerated GPU database kind of capabilities, but the thing that had me the most excited on Monday were the end users. I've always said, and the analysts always ask me the questions of when are you going to start penetration in the market? When are you going to show that you've got a lot of end users deploying this? And there were a lot of statements by a lot of big players on Monday. Google was on stage and publicly said the IO was amazing, the memory bandwidth is amazing. We are deploying Zaius, which is the power nine server, in our data centers and we're ready for scale, and it's now Google strong which is basically saying that this thing is hardened and ready for production, but we also (laughs) had a number of other significant ones, Tencent talkin' about deploying OpenPOWER, 30% better efficiency, 30% less server resources required, the cloud armor of Alibaba talkin' about how they're putting on their on their X-Dragon, they have it in a piler program, they're asking everybody to use it now so they can figure out how do they go into production. PayPal made statements about how they're using it, but the machine learning and deep learning to do fraud detection, and we even had Limelight, who is not as big a name, but >> CDN, yeah. >> They're a CDN tool provider to people like Netflix and others. We're talkin' about the great capability with the IO and the ability to reduce the buffering and improve the streaming for all these CDN providers out there. So, we were really excited about all those end users and all the things they're saying. That demonstrates the power of this ecosystem. >> Alright, so just to comment on the architecture and then, I want to get into the Cognitive piece. I mean, you guys did, years ago, little Indians, recognizing you got to get software based to be compatible. You mentioned, Ken, bandwidth, IO bandwidth, CAPI stuff that you've done. So, there's a lot of incentives, especially for the big hyperscale guys, to be able to do more with less, but, to me, let's get into the AI, the Cognitive piece. Bob Picciano comes over from running a $15 billion analytics business, so, obviously, he's got some knowledge. He's bringin' in people like you with all these cool buzzwords in your title. So, talk a little bit about infrastructure for AI and why power is the right platform. >> Sure, so, I think we all recognize that the performance advantages and even power advantages that we were getting from Dennard scaling, also known as Moore's law, is over, right. So, people talk about the end of Moore's Law, and that's really the end of gaining processor performance with Dennard scaling and the Moore's Law. What we believe is that to continue to meet the performance needs of all of these new AI and data workloads, you need accelerators, and not just computer accelerators, you actually need accelerated networking. You need accelerated storage, you need high-density memory sitting very close to the compute power, and, if you really think about it, what's happened is, again, system view, right, we're not silicon view, we're looking at the system. The minute you start looking at the silicon you realize you want to get the data to where the computer is, or the computer where the data is. So, it all becomes about creating bigger pipelines, factor of pipelines, to move data around to get to the right compute piece. For example, we put much more emphasis on a much faster memory system to make sure we are getting data from the system memory to the CPU. >> Coherently. >> Coherently, that's the main memory. We put interfaces on power nine including NVLink, OpenCAPI, and PCIe gen four, and that enabled us to get that data either from the network to the system memory, or out back to the network, or to storage, or to accelerators like GPUs. We built and embedded these high-speed interconnects into power nine, into the processor. Nvidia put NVLink into their GPU, and we've been working with marketers like Xilinx and Mellanox on getting OpenCAPI onto their components. >> And we're seeing up to 10x for both memory bandwidth and IO over x86 which is significant. You should talk about how we're seeing up to 4x improvement in training of MLDL algorithms over x86 which is dramatic in how quickly you can get from data to insight, right? You could take training and turn it from weeks to days, or days to hours, or even hours to minutes, and that makes a huge difference in what you can do in any industry as far as getting insight out of your data which is the competitive differentiator in today's environment. >> Let's talk about this notion of architecture, or systems especially. The basic platform for how we've been building systems has been relatively consistent for a long time. The basic approach to how we think about building systems has been relatively consistent. You start with the database manager, you run it on an Intel processor, you build your application, you scale it up based on SMP needs. There's been some variations; we're going into clustering, because we do some other things, but you guys are talking about something fundamentally different, and flash memory, the ability to do flash storage, which dramatically changes the relationship between the processor and the data, means that we're not going to see all of the organization of the workloads around the server, see how much we can do in it. It's really going to be much more of a balanced approach. How is power going to provide that more balanced systems approach across as we distribute data, as we distribute processing, as we create a cloud experience that isn't in one place, but is in more places. >> Well, this ties exactly to the point I made around it's not just accelerated compute, which we've all talked about a lot over the years, it's also about accelerated storage, accelerated networking, and accelerated memories, right. This is really, the point being, that the compute, if you don't have a fast pipeline into the processor from all of this wonderful storage and flash technology, there's going to be a choke point in the network, or they'll be a choke point once the data gets to the server, you're choked then. So, a lot of our focus has been, first of all, partnering with a company like Mellanox which builds extremely high bandwidth, high-speed >> And EOF. >> Right, right, and I'm using one as an example right. >> Sure. >> I'm using one as an example and that's where the large partnerships, we have like 300 partnerships, as Ken talked about in the OpenPOWER foundation. Those partnerships is because we brought together all of these technology providers. We believe that no one company can own the agenda of technology. No one company can invest enough to continue to give us the performance we need to meet the needs of the AI workloads, and that's why we want to partner with all these technology vendors who've all invested billions of dollars to provide the best systems and software for AI and data. >> But fundamentally, >> It's the whole construct of data centric systems, right? >> Right. >> I mean, sometimes you got to process the data in the network, right? Sometimes you got to process the data in the storage. It's not just at the CPU, the GPUs a huge place for processing that data. >> Sure. >> How do you do that all coherently and how do things work together in a system environment is crucial versus a vertically integrated capability where the CPU provider continues to put more and more into the processor and disenfranchise the rest of the ecosystem. >> Well, that was the counter building strategies that we want to talk about. You have Intel who wants to put as much on the die as possible. It's worked quite well for Intel over the years. You had to take a different strategy. If you tried to take Intel on with that strategy, you would have failed. So, talk about the different philosophies, but really I'm interested in what it means for things like alternative processing and your relationship in your ecosystem. >> This is not about company strategies, right. I mean, Intel is a semiconductor company and they think like a semiconductor company. We're a systems and software company, we think like that, but this is not about company strategy. This is about what the market needs, what client workloads need, and if you start there, you start with a data centric strategy. You start with data centric systems. You think about moving data around and making sure there is heritage in this computer, there is accelerated computer, you have very fast networks. So, we just built the US's fastest supercomputer. We're currently building the US's fastest supercomputer which is the project name is Coral, but there are two supercomputers, one at Oak Ridge National Labs and one at Lawrence Livermore. These are the ultimate HPC and AI machines, right. Its computer's a very important part of them, but networking and storage is just as important. The file system is just as important. The cluster management software is just as important, right, because if you are serving data scientists and a biologist, they don't want to deal with, "How many servers do I need to launch this job on? "How do I manage the jobs, how do I manage the server?" You want them to just scale, right. So, we do a lot of work on our scalability. We do a lot of work in using Apache Spark to enable cluster virtualization and user virtualization. >> Well, if we think about, I don't like the term data gravity, it's wrong a lot of different perspectives, but if we think about it, you guys are trying to build systems in a world that's centered on data, as opposed to a world that's centered on the server. >> That's exactly right. >> That's right. >> You got that, right? >> That's exactly right. >> Yeah, absolutely. >> Alright, you guys got to go, we got to wrap, but I just want to close with, I mean, always says infrastructure matters. You got Z growing, you got power growing, you got storage growing, it's given a good tailwind to IBM, so, guys, great work. Congratulations, got a lot more to do, I know, but thanks for >> It's going to be a fun year. comin' on the Cube, appreciate it. >> Thank you very much. >> Thank you. >> Appreciate you having us. >> Alright, keep it right there, everybody. We'll be back with our next guest. You're watching the Cube live from IBM Think 2018. We'll be right back. (techno beat)