 All right, thanks for coming out. I'm Cameron Cedar from SUSE. I am a technology strategist, and I'm going to talk with you today about a very important topic that seems to be coming up in the field quite a bit today. And that's keys to data center modernization to infrastructure agility. Bimodal IT has been talked about for a couple years now and first introduced by Gartner. And on the surface, you don't really see exactly what's going on. But if you look a little bit deeper, there are lots of challenges and opportunities available to you in your IT organization when you talk about Bimodal IT. So the two brains of Bimodal IT, you have Mode 1 and Mode 2. Mode 1 is usually your traditional workloads, workloads that have been around a long time, monolithic applications. They have long release cycles, long life cycles. Those applications aren't really moving, aren't going anywhere fast. Your Mode 2 is more agile applications, your DevOps applications. You're moving into more cloud-native, short life cycles from weeks to days. You're moving quickly. If we take a look at the evolution of the data center from a more traditional method, if you go back years and years from mainframes and then moving from mainframes off of them over to physical servers and spinning up lots and lots of open system platforms, from there, we're moving into virtualized servers. And if you go back 10 years ago, there were lots and lots of projects spinning up for data center modernization projects. And moving into virtualization, VMware was a really big thing to get you into a more modern infrastructure where you're on more of a virtualized infrastructure. Today, we're now moving into pools of resources where you can actually utilize those resources anywhere at any time, where it's either in a public cloud or a private cloud infrastructure with OpenStack. And those compute resources could be on a number of different systems from mainframes to open systems platforms that are available today. And we're continually evolving that, where those pools of resources are available to your cloud native applications through microservices and things of that nature, serverless environments as well. Jonathan Bryce has always said that the benefits of cloud are too great to only allow new workloads onto the platform. We need to continue to evolve this platform. SUSE has an agile platform today. It's designed for the future. We have a small SUSE Linux Enterprise system called JUICE, just enough operating system. We're ideal for a bimodal IT environment. We can utilize our SUSE Linux Enterprise server environment and build upon that with OpenStack and Kubernetes and other types of microservices environments. We're designed for the future. But modernization is just more than that. It takes a lot of agility. You have to be mindful of several different things before you tackle a modernization project. You have to know your environment. You're the ones that are the customers. You know your environment the best. It's important that you take a look at it deeply and look how you can move to the future and modernize your data center. Take a look at your security, the cost of interruption to your organization. It's a bit of a change in perception as you look towards modernizing your environment. It's a change of perception inside your IT. There might be groups that wanna go one way and other group wants to go another way. But it causes a diverse level of thinking. And that diverse level of thinking is what's gonna get you to a modern data center. Now modernization of the infrastructure is already been looked at in several different ways. There are companies today that are looking at what we call lift and shift. I don't recommend it. And there's lots of reasons why. Lift and shift in the container world means I'm going to take my monolithic application I'm going to just move it into a container. That's not a good practice. If you want to be like Homer Simpson and in the end you're gonna be sitting on the couch wondering why did I do that? Not a great idea. If you look forward to workload migration, now when I'm talking about workload migration what I mean is I'm gonna take my monolithic applications I'm going to migrate that over to an open stack private cloud or I'm gonna migrate that to a public cloud environment. But I'm gonna take a look deeply at the security. I'm going to enhance the security. When I move that workload over to the cloud it's usually platform agnostic. It's also interoperable. You can move it between your private cloud and your public cloud. And it's usually right sized for your environment, for that application. From there we want to transform ourselves to workload transformation. This might not be something that you do immediately. When you're starting out with workload migration you are usually going to move applications just maybe to a virtual machine. But when you start in on a workload transformation you're moving into things like microservices. You're moving into containers. You're taking a look at that application and seeing how you can split that application up so that it's much more modern and it could work with a containerized environment. It usually takes a structured approach. And that's really what I want to portray to you today is that take a look at your requirements. What are those today? Not every application is the same. You have to take a look at each and every application in your data center today differently. There might be certain appropriate choices for your architecture. Do you want to run that on a mainframe compute host? Do you want to run that on an open systems platform? There are certain platforms that are appropriate for different solutions. You also need to plan for long-term growth and that means the infrastructure as well. You need to plan for your network infrastructure. You need to plan for your storage infrastructure. You need to take a look at long-term what that might look like because you might be consolidating pools of resources like your storage, like your compute infrastructure. So you might need an advanced networking infrastructure today in order to get to that spot in the future. Pay attention to reliability, availability, and serviceability. Make sure that you're mindful of that when you're doing workload migration. Make sure that you're securing your infrastructure. Make sure that you have a compliance strategy. If you've got one today, make sure it's also ready for that modernization when you move towards your private cloud infrastructure. Make sure that you have monitoring strategy ready to go. Backup and disaster recovery, usually something that's put on the back burner and people don't pay attention to, but it's very important that you have that strategy ready to go. There are some general characteristics. When we take a look at tools for migration and transformation, okay? These general characteristics are across all these tools. Data center analysis. These tools will allow you to analyze your applications and the infrastructure that you're running on top of. Hardware analysis, your infrastructure, your networking. You'll be able to do image rendering, building, rebuilding of those images across the infrastructure. It needs to be agnostic. It needs to be agnostic across your infrastructure, distributions. It will allow you to re-architect your infrastructure. You'll be able to have workflow changes. It's pluggable. Operating system security hardening is built in. Compliance is at the top of the list there. And also operating system integrated. If we take those characteristics and we split those apart and take a look at the tools available today for workload migration, that gives us configuration discovery. We have tools like machinery. Machinery will allow you to discover a configuration. That configuration could be on a virtual machine. It could be a physical machine. It could be a container. It doesn't matter. It will spit out what we call a system description file that will tell you all about that system, how it's configured, what's installed on it, what the hardware is like. And then you can take that and move that anywhere you want. Take a bare metal system and migrate it to a virtual machine. Take a virtual machine and migrate it to a public or private cloud. It allows you to have service migration abilities. We can take advantage of things like Kiwi, which do the building process for images, creating lean OSs built specifically and right size specifically for your application. It's important that we have what we call multi-distro outputs. So you can build it for many of the distributions that are out there today. Multiple format outputs. So it will allow you to run in the Azure cloud, in the Amazon cloud, on OpenStack with QCOW 2 formats in VMware, if you're continuing to use VMware with OpenStack, multiple formats. And also integrating Bastille so you can security harden your environment as well, all while building an image that is capable of running anywhere you wanna put it. Once you've achieved that workload migration and you've migrated those workloads to your private cloud, or you've migrated them to a public cloud possibly, you're then going to look at workload transformation. And when I talk about transformation, that means you're moving into microservices, you're moving into containers, you're moving into serverless environments. Those characteristics change just a little bit, but it also inherits things from the workload migration characteristics. We have workflow development by using Jenkins, integrating that with your process and changing the workflow the way that those applications are deployed, automating that workflow. You have on-demand services, incorporating Kubernetes to be able to scale up and scale down your infrastructure. Application resiliency is built right into that kind of infrastructure. You have automation engines, configuration management like Salt and Ansible. You have an automated build system environment, such as the OpenBuild service where you can take packages and check them in from your source, build RPM packages for multiple distributions. It could be Ubuntu, it could be Red Hat, it could be SUSE. Taking those sources and automating the build process with Kiwi and outputting your images that can be then pushed out into a private cloud or a public cloud, automating that whole entire process. Then of course, log aggregation, atomic updates, which will give you the resiliency and the compliance that you need in your containerized environment. Moving into a more DevOps-like environment. Here's kind of an example of a workload transformation. It's a more simplified one. It's got a lot of SUSE tools there, of course, but this could be enhanced to add in things like Jenkins, other types of workload automation. I've got another diagram that's really, really busy that kind of gets crazy for looking at, but this could get much more complex. But these are the basics of it, okay? Couple of resources that you can take a look at. I have a video online. If you wanna watch that, it uses machinery to do an entire workload migration from a virtual machine environment that's actually a SLEZ 11. And it changes that SLEZ 11 environment with a workload running there to a SLEZ 12 environment that you can actually publish in a private cloud. Some links there for Kiwi, the tools that are available from SUSE. There, of course, are other open source projects that you might wanna incorporate here as well. And then we also have the open build service. You can go out there and try it at opensusa.org. And then, of course, the openbuildservice.org. And then, of course, you can follow me on GitHub and Twitter. And you can grab me anytime after for any questions. Thank you.