 Live from New York, it's theCUBE. Covering theCUBE, New York City, 2018. Brought to you by SiliconANGLE Media and its ecosystem partners. Hello everyone, welcome back. This is theCUBE live in New York City for CUBE NYC, hashtag CUBE NYC. This is our ninth year covering the big data ecosystem, which has now merged into cloud. All things kind of coming together. It's really about AI, it's about developers, about operations, about data scientists. I'm John Furrier with my co-host, Dave Vellante. Our next guest is Brent, Compton Technical Marketing Director for Storage Business at Red Hat. As you know, we cover Red Hat Summit and great to have the conversation open source. DevOps is the theme here. Brent, thanks for joining us. Thanks for coming on. My pleasure, thank you. So we've been talking about the role of AI and AI needs data, data needs storage is what you do. If you look at what's going on in the marketplace, kind of an architectural shift. I mean, it's harder to find a cloud architect than it is find diamonds these days. It's like you can't find a good cloud architect. Cloud is driving a lot of the action, data is a big part of that. What's Red Hat doing in this area and what's emerging for you guys in this data landscape? They're really the days of specialists that are over. You mentioned it's more difficult to find a cloud architect than find diamonds. What we see is the infrastructure, it's become less about compute and storage and networking. It's the architect that can bring the confluence of those specialties together. One of the things that we see is people bringing their analytics workloads onto the same, onto the common platforms where they've been running the rest of their enterprise applications. So for instance, if they have, if they're running a lot of their enterprise applications on AWS, of course they want to run their analytics workloads on AWS. And that's EMRs long since in the history books. Likewise, if they're running a lot of their enterprise applications on OpenStack, it's natural that they want to run a lot of their analytics workloads on the same type of dynamically provisioned infrastructure. And emerging, of course, we just announced on Monday this week with Hortonworks and IBM, if they're running a lot of their enterprise applications on a Kubernetes substrate like OpenShift, they want to run their analytics workloads on that same kind of agile infrastructure. Tell me about the private cloud impact and hybrid cloud. Obviously we just talked to the CEO of Hortonworks. And normally it's about early days about Hadoop, data lakes and then data planes. They had a good vision, they're years into it. So I like what the Hortonworks is doing. But he said Kubernetes, and we knew it was a data show, Kubernetes, Kubernetes is a multi-cloud, hybrid cloud concept containers. This is really enabling a lot of value. And you guys have OpenShift, which became very successful over the past few years. The growth has been phenomenal, so congratulations. But it's pointing to a bigger trend. And that is that the infrastructure software, the platform as a service is becoming the middleware, the glue, if you will. And Kubernetes and containers are facilitating kind of a new architecture for developers and operators. How important is that for you guys? And what's the impact of the customer when they think, okay, I'm going to have an agile DevOps environment at workload portability. But do I have to build that out? You mentioned people don't have to necessarily do that anymore, the trend has become on premise. What's the impact of the customers as they hear Kubernetes and containers and the data conversation? So you mentioned agile DevOps environment, workload portability. So one of the things that customers come to us for is having that same thing, but infrastructure agnostic. They say, I don't want to be locked in, love AWS, love Azure, but I don't want to be locked into those platforms, I want to have an abstraction layer for my Kubernetes layer that sits on top of those infrastructure platforms. And as I bring my workloads one by one, custom DevOps from a lift and shift of legacy apps onto that substrate, I want to have it be independent. So private cloud or public cloud, and if time permitting we'll go into more details about what we've seen happening in the private cloud with analytics as well, which is effectively what brought us here today is the pattern that we discovered with a lot of our large customers who are saying, hey, we want to bring, we're running OpenStack, they're large institutions that for lots of reasons they store a lot of their data on premises, saying we want to use the utility compute model that OpenStack gives us, as well as the common, the shared data context that Ceph gives us, we want to use that same thing for our analytics workload. So effectively, some of our large customers taught us this. So they're building analytical infrastructure, infrastructure for analytics, essentially. That's what it is. So one of the challenges with that is the data is everywhere, it's all in silos, sort of locked to maybe in some server somewhere. How, first of all, am I overstating that problem and how are you seeing customers deal with that? What are some of the challenges that they're having and how are you guys helping? Perfectly to one of the, in fact, one of our large government customers. They recently sent us an unsolicited email after they deployed. They're the first 10 petabytes in a DecaPetabyte solution. It's OpenStack-based as well as Ceph-based. Three taglines in their email. The first was releasing the lock on data. The second was releasing the lock on compute. And the third was releasing the lock on innovation. Now that sounds a bit buzzwordy, but when it comes from a customer. It came from a customer. To you. Sounds like a marketing department wrote that. So in the details, as you know, traditional HDFS clusters, traditional Hadoop clusters, Spark clusters or whatever, HDFS is not shared between clusters. One of our large customers has 50 plus analytic clusters. So they're data platforms team, employee a maze of scripts to copy data from one cluster to the other. And if you're a scientist or an engineer, you say, I'm trying to obtain these types of answers, I need access to data sets A, B, C, and D, but data sets A and B are only on this cluster. I've got to go contact the data platform, seem to have them copied over and ensure that it's up to date and in sync. So it's just messy, messy. So that's why the one customer said unlocking the, releasing the lock on data because now it's in a shared. So similar paradigm is AWS with EMR. So the data is in a shared context in S3. You spin up your analytics workloads on EC2, same paradigm that this customer has with OpenStack. You're spinning up your analytics workloads via OpenStack virtualization. And they're sourcing a shared data context inside of S3 compatible SEP. So same architecture. And I love his last bit, the one that sounds most buzzwordy which was releasing lock innovation. His words were, and this individual English was not this person's first language. So love the words said, our developers no longer fear experimentation. Because it's so easy in minutes they can spin up an analytics cluster with a shared data context. They get the wrong mix of things. They shut it down and spin it up again. And the previous example you used the HTFS clusters, so many trip wires, right? You can break something, so fragile scripts, like scripts. And you don't want to tinker with that. You don't want to get their hands wet. There's also the recognition that innovation comes from data, right? That's what my takeaway is, the customer saying, okay, now we can innovate because we have access to the data. We can apply intelligence to that data, whether it's machine intelligence or analytics, et cetera. So this is the trend in infrastructure. You mentioned the shared concept. What are the observations and learnings have you guys come to as Red Hat starts to get more customer interactions around analytical infrastructure? As an IT problem, you mentioned abstracting away different infrastructures, that means multi-clouds probably set up for you guys in a big way. But what does that mean for a customer if you had to explain infrastructure analytics? What needs to get done? What does a customer need to do? How do you describe that? I love the term that industry uses of multi-tenant workload isolation with shared data context. That's such a concise term to describe what we talk to our customers about. And most of them, that's what they're looking for. They've got their data scientist teams that don't want their workloads mixed in with the long-running batch workloads. They say, listen, I'm on deadline. I've got an hour to get these answers. They're working with them, Paul. They're working with Presto. They need rapid, they iterate. They don't know exactly the pattern they're looking for. So having to take a long time because their jobs are mixed in with these long, map-reduced jobs, they need to be able to spin up infrastructure. Workload isolation, meaning they have their own space, shared context. They don't want to be placing calls over to the platform. People say, hey, I need data sets, cD&e, could you please send them over? I'm on deadline here. That phrase, I think, captures so nicely what customers are really looking to do with their analytics infrastructure. It's so, analytics tools, they'll still do their thing, but the infrastructure underneath analytics, delivering this new type of agility is giving that multi-tenant workload isolation with shared data context. You know, as funny as we were talking that the kickoff, we were looking back nine years, we've been at this sort of event for nine years now, and we made the prediction, there will be no red hat of big data than John years ago said, unless it's red hat. And you guys kind of got dragged into this by your customers, really, is how it came about. Customers and partners. Of course, you're with your recent guest from Hortonworks, the announcement that red hat Hortonworks and IBM had on Monday this week, and just dying it up even further with you, taking the agility. Okay, OpenStack is great for agility, private cloud, utility-based computing and storage with OpenStack and Ceph great, but OpenShift takes and dials up that agility another notch, and that's, of course, we heard from the CEO of Hortonworks, how much they love the agility that a Kubernetes-based substrate provides their analytics customers. So that's essentially how you're creating that sort of same, same experience between on-prem and multi-cloud, is that right? OpenShift is deployed pervasively on AWS, on premises, on Azure, on GCE. It's a multi-cloud world, we see that for sure, and again, the validation was that BM world AWS's CEO Andy Jassy announced RDS, which is their product on VMware, on premises, which they've never done, Amazon's never done any product on premises. We expect that it would be a hardware device, but we've missed that one, but it's software, but this is the validation. Seamless cloud operations on premise in the cloud really is the what do people want? They want one standard operating model, and they want abstract away the infrastructure, as you were saying, as the big trend. The question that we have is, okay, go to the next level. From a developer standpoint, what is this modern developer using for tools and the infrastructure? How can they get that agility and spinning up isolated, multi-tenant infrastructure kind of concepts all the time? This is kind of the demand we're seeing. So that's an evolution. Question for Red Hat is, how does that change your partnership strategy? Because you mentioned Rob Bearden on, they've been hardcore enterprise, and you guys are hardcore enterprise. You kind of know the little things that customers want that might not be on obvious people, compliance, certification, decade of support. How is Red Hat's partnership model changing with this changing landscape, if you will? You mentioned IBM and Hortonworks released this week, but what in general, how's the partnership strategy look for you? The more it changes, the more it looks the same. When you go back like 20 years ago, what Red Hat has always stood for is, any application on any infrastructure. I mean, but back in the day it was, we had N thousand of applications that were certified on Red Hat Linux, and we ran on anybody's server, exactly, running on a box, exactly. So very similar, I mean, it's a similar play, just in 2018, in the world of hybrid, multi-cloud architectures. Well, you guys have done some serious heavy lifting. I mean, don't hate me for saying this, but you're kind of like the mules of the industry. I mean, you do a lot of stuff that nobody either wants to do or knows how to do, and it's really paid off. I mean, you just look at the ascendancy of the company, it's been amazing. Well, multi-cloud is hard. I mean, look at what it takes to do multi-cloud in DevOps, it's not easy. And so a lot of pretenders will fall out of the way you guys have done well. So what's next for you guys? What's in the horizon, what's happening for you guys this next couple months for Red Hat and technology? Any new announcements coming? What's the vision, what's happening? One of the announcements that you saw last week was Red Hat, Cloudera, and EuroTech, as analytics in the data center is great. The world increasingly, the world's businesses run on decisions, data-driven decisions. That's great, but analytics at the edge for more real-time, industrial automation, et cetera, et cetera. So per the announcements we did with Cloudera and EuroTech about the use of, we haven't even talked about the Red Hat's middleware platforms, such as AMQ Streams, now based on Kafka, a Kafka distribution, Fuse, an integration master. So effectively bringing Red Hat technology to the edge of analytics so that you have the ability to do some processing in real time before back calling all the way back to the data center. And so that's an area that you'll also see is pushing some analytics to the edge through our partnerships, such as announced with Cloudera and EuroTech. You guys got the Red Hat Summit coming up next year. We'll be, the queue will be there as usual. It's great to cover Red Hat. Thanks for coming on theCUBE, Brent. Appreciate it. Thanks for spending the time. Thank you. We're here in New York City live. I'm John Furrier, Dave Vellada. Stay with us all day coverage today and tomorrow in New York City. We'll be right back.