 Hey, good afternoon. My name is Brian Thompson. I'm the general manager of the OpenStack private cloud business at Rackspace. I've got a brief presentation I want to walk through today, specifically about edge computing, AI, and machine learning. These are hot topics that I know everybody at the summit is really eager to learn and attend. Oh, sorry, wrong deck. No, all joking aside, I was trying to do a little click bait and grab some attention. I do want to talk about something that is specific to Rackspace and our product offering and where we've gone through our partnership with HPE to provide a pay-per-use consumption model for private cloud. So if you think about the context of how do I consume OpenStack and certainly where we've been very successful helping enterprises consume OpenStack as a private cloud, but now providing a consumption model that gives many of those unit economics and flexibility that comes from a public cloud and that utility model that many look for. So this is actually a solution offering that we announced in November through our partnership with HPE and specifically launching this industry first pay-as-you-go OpenStack private cloud solution. How do you deliver customers the capabilities of a private cloud and delivering an OpenStack platform? Either our native upstream OpenStack offering and the Red Hat OSP platform as well. So customers, we can serve depending on what they're looking to do. But now in a private cloud form factor in our data center or their data center with the unit economics and value of a consumption model, utility consumption model. So if you look at some of the key components of this value proposition, this pay-per-use, private cloud, how do I solve for that, it starts with that concept that pays you go. How do I start to make sure that I'm not committing to infrastructure and services that I'm not ready to use yet? I haven't scaled my business into that. How do I enable some amount of bursting and that capability that I might otherwise look for a public cloud purely to deliver that capability? How do I have that on-demand capacity where I can scale into that as my workloads ramp up or as different kind of changes to my business driver or growth consumption of my private cloud? I can make sure I meet that demand and I'm not capping the capacity that I can serve my cloud users with. It is a cost conversation. At the end of the day, none of us are doing this for free. Enterprise has unlimited IT budget. Infrastructure costs money. So how do you start to think about the unit economics and best workload placement? How do I drive the best overall unit economics? And with a private cloud and this consumption model, we've seen how I'll kind of talk to some of these data points where customers can actually drive a lower cost per instance, if you think about that as kind of your bar, over pure public cloud consumption. So it's actually a very compelling and powerful solution. There's also that focus of, again, part of that value of a private cloud and this operating partner solution where you can get that enterprise stability. How do I provide security, quality of service, the performance requirements that I need for my workloads and still, again, in that cloud self-service agility that I'm trying to enable for my end users? So part of this key is where these services come together. So starting with that foundation of the HPE flexible capacity solution, it gives us a pricing and financing vehicle that allows us to identify and scale out the environment that a customer might need and then charge them as they use this. And I'll kind of talk a little bit more detail of how that actually kind of breaks down. But it gives us the ability to do a roll-in rack solution. We can deliver this in any of rack spaces data centers around the world or we can provide it in a customer data center, customer prem or third party data center where it is a full managed solution. We will roll in the rack of hardware, deliver this capacity and services and then bring in the rack space managed services to actually deliver and operate the open stack software itself. So that software stack, helping design, deploy and operate that cloud infrastructure. Bringing together our best practices, our opinionated deployment of these technologies, how do we operate it at scale and with enterprise level SLAs that you're looking to consume this as a black box service. Make sure you're getting the availability, performance and scalability that you're looking for from that platform. This is really kind of bringing together those kind of best in service capabilities. Rack space, we are operators of this technology. We are the home of fanatical support for those that may be familiar with rack space as a brand. This is our focus is how do we help operate complex technologies for customers at scale and this solution gives us the ability to deliver a private cloud solution for customers and help them consume this technology and take advantage of an open stack private cloud environment. The core to that flexible cap model and this is the traditional approach. If you look at the left-hand side you'll see historically and with most IT infrastructure I have to plan for what my theoretical capacity needs to be. How am I planning for what I'm going to grow into within a reasonable amount of time but it is a step function of expansion. I am paying for all of that capacity whether I'm using it or not and this in some cases can be an economic barrier to adoption of private cloud. I know I wanna go cloud, I know I wanna consume open stack but I'm not ready to consume it 100% day one. How do I help ramp into that? How do I help build capacity and leverage the power and flexibility of cloud without committing financially into tiers that I'm not ready to consume yet? So this flexible capacity solution and our ability to partner with HPE and deliver this allows us to plan out what is my expected kind of steady state capacity I'm gonna start with and how do I then bring in a buffer if you will of additional capacity on top of that? This allows me to have that capacity available and on demand. I can light it up immediately, I can scale into it seamlessly yet I'm not charged for, I'm not paying for that capacity until I'm ready to use it. So give me both the elasticity where I can burst workloads into it and then scale them back down or to match to my steady organic growth as my cloud footprint and more and more workloads move to this cloud how do I scale that more steadily if you will. This really allows organizations to map their cost to their actual growth and usage itself. So giving the fixed capacity that I'm expecting and then in a consumption based model charge per gig of RAM if you kind of think about that kind of model of how you'll actually charge for this just as if it was a public cloud and scale into it as I organically grow. So this can be actually game changing in certain cases for organizations as they look to map their overall cost of workloads and think about workload placement decisions they have the extra capacity when they need it but they're not financially committing to it until they're ready to move into it. So it's a very powerful tool that moves into that. So it's a high level conversation. I really wanted to tee up the concept. We do have a number of rackers and other folks that are here that can speak more to this solution answer more questions you may have about it. We have the rack space booth over here. We've also been working with HPE and Ericsson on the lounge right around the corner here where we have some events planned and other activities I would love to engage for more conversation. I do have time now if there are those that might have actual questions that I can address or talk to or again would encourage you to come meet with any of our rackers and HPE partners that are here. Great, short and sweet. Now I'll get back to edge computing AI and ML. Maybe I'll be the next one. Thank you.