 Live from the Julia Morgan Ballroom in San Francisco, extracting the signal from the noise, it's theCUBE covering structure 2015. Hi, welcome, Jeff Frick here with theCUBE. We are live on the ground at the Julia Morgan Ballroom in downtown San Francisco for the structure event. It's back, there's a little bit of a hiatus, but structure is back. This is the first one that they're kind of relaunching. I think it's about 400 or 500 people here packed into the Julia Morgan Ballroom. They've got a full slate of a who's who's of people in technology all around cloud and also big data and some other topics, but really a heavy cloud focus. And we're excited to be here covered. It's the first time theCUBE's been to structure, George. So we're going to be here for two days of wall-to-wall coverage. Get some of the smartest people we can find, sit down, extract the signal from the noise and bring you the content that you're looking for. So joined here by George Gilbert, analyst from Wikibon. Hey, George. Good to be here, Jeff. So I know we did about 80 events this year, but I know you were particularly looking forward to structure. What gets you so charged up about structure? Well, structure? Well, for one, I was part of GigaOM for several years before coming over to Wikibon and theCUBE, but structure was an iconic event because it was really one of the first ones that tried to define cloud computing back when it was just a bunch of definitions and not a lot of reality. And so that's what brought sort of the thought leadership circle into the orbit of the conference and sort of into the orbit of GigaOM at the time. And it's really a lot of the shows that we go to now, there's usually a primary sponsor or kind of a one or two primary sponsors. Really don't have that here. It's really still an industry show, a thought leadership show with a broad representation. So what are some of the things you're looking forward to learning while we're here for the next couple of days? Well, traditionally, the way it was defined is structure started out as a cloud infrastructure. And then they spun off another conference, structure data, which was around emerging big data. And that too started to define that sort of class of solutions. And then more recently, they spun off structure connect, which was about internet of things. But it's not going to be just cloud infrastructure and software defined sort of data centers here. It's, I mean, just a sample of some of the folks we're talking to, the EMC owned VCE, converged infrastructure company. We're going to be talking to CoreOS, the guys who've made a lot of noise around streamlined applications, sort of containers and orchestration. Apsara, one of the sort of industry luminaries who's pioneered the platform as a service market and who had much colorful history before that. Puppet and configuration management. It goes through hot and cold phases. It's hot again. Data gravity, which is doing something where it's almost like data loss prevention, which used to be just on the client, but now they make sure your data stays and doesn't go anywhere it shouldn't go, even in a shared server environment. And two things that are really outside the cloud infrastructure realm, SAP and Azure, Microsoft platform and applications as a service. And we have lots of interesting questions to ask of all these guys. So it's interesting that you talked about really cloud, big data and IoT really being separate tracks, but really the three of those things combined together that are giving really the driving force in the marketplace. And it's interesting you mentioned SAP. We're actually going to be at an SAP event at the Hanahauts in Palo Alto later tonight where they're introducing their cloud Hanah IoT solution. So these things are all coming together and they all help enable one another. So I don't know, can we really separate them anymore? Or do you have to blend them all together? If you try to separate it, it's kind of like splitting a warm cookie. The boundaries not quite that clean. In the 2008, 2009 timeframe, when some of the big cloud data centers were being built out, most of the volume was still based on web clients, but rapidly that converted to serving mobile devices as those exploded in volume and in their demands for backend cycles. And the same thing's happening with internet of things in that the amount of machine generated data is just dwarfing what we collected in sort of corporate applications in the past. And that's why you're seeing some overlap on all these areas. And at the end of the day, those are all infrastructure components and ways to do things different and integrate more data into your solutions. But at the end of the day, it's still about applications and solutions. And one of the hypothesis or topics that you write on extensively is systems of engagement. So how is the marriage of these three trends really enabling and accelerating systems of engagement versus historically what we're always systems of record? I have to needle you and remind you that, like I like to call them systems of intelligence because the systems of engagement I view as a richer UI and a richer end user experience, but I distinguish it from systems of intelligence because that's where there's in a set of analytics that automates some or all of the decision process. So like a vendor, you wouldn't have someone in the call center, you know, assisting a user on the website. It would, the vendor's application would automatically make a next best offer or try and prevent a churn advance for a telco. But going back to what's driving it. So yes, just the way mobile took off and drove, you know, like the number of data centers that Google and Facebook are building because of the traffic volume on mobile is more advanced systems, whether on mobile devices or on the web. They require data as their raw material and analytics as the recipe for mixing it. And that's requiring an amount of infrastructure that we couldn't have imagined before. Just by way of example, I spoke to the COO of GE's central IT group and now they're a rather decentralized organization. But they said they have roughly 30 petabytes of data right now from traditional applications. They said in short order, the data coming off their machines in the field and not the ones they own, but the ones they've sold is going to just dwarf that. And so, you know, so yes, there is a link to, you know, the structure infrastructure that we're talking about here. Right, and Bill Rue and the team have a huge presence now of San Ramon with a software group that was really built around the platform of connecting the various GE business units and now they're building applications on top of that. Diane Bryant just really kicked off structure here, talking about obviously data centers are at the heart of this whole thing and, you know, seems to be where Intel maybe missed the game a little bit on mobile devices. They're not going to do that again in servers and in data centers and are really all in. We're seeing them everywhere. Now, I'm a software guy, but I like to poke around a little bit in hardware where, you know, there's something interesting going on. And a lot of people have talked about Moore's law kind of slowing down or even ending, but that's with the old definition, which was the transistor density on a chip. But when you put them in data centers and you put how many transistors in a rack, you know, in a refrigerator size rack, that number is actually accelerating. You know, it's a different way of looking at it. Well, you know, we've talked to Kim Stevenson about Moore's law at Intel. She really talked about Moore's law really as being a way of thinking, a way of developing, a way of kind of setting expectations in the way things move as opposed to just purely around silicon. But at the same time, when we talked to John Fowler from Oracle talking about next gen spark chips, he's talking about moving more and more functionality into silicon to continue to accelerate that. So we've got to break here in a minute, last kind of thought before we jump in and start interviewing our guests. I think the most interesting thing is viewers will see today us talk all the way from the infrastructure layer, hardware, all the way up to the applications that consume that. One example, SAP, as you mentioned, we're going down to cover their internet of things in memory database rollout. That database was made possible by the changing relative price performance between memory and CPU. And when we have memory rich environments, we can totally rethink how databases work so they're much faster, contain much more data. So we'll see that gamut today. And then rethink the application, right? And the solution, what you can do today that you couldn't do before. So it's exciting times with George Gilbert, Jeff Rick. We're going to be here all day tomorrow and the next day. We're at Structure in downtown San Francisco. We'll be back with our next guest after this short break. Thanks for watching.