As we switch over to our AWS environment, you see that we have our four servers running. There's two login servers, one for the cloud and one for the simulated on-prem environment. And then there's an LSF uh server in both the cloud and on the on-rem. So we have two versions of FSX running, one on-prem and one in the cloud. You'll see that this is the on-prem virtual private cloud. You can administer this with a management endpoint and the intercluster IP address are available. Uh it's running a single virtual machine and I already have a few volumes pre-provisioned for this workshop. Looking at FSX instance, what we see is this is the cloud instance. It also has administration ports and it's got its own virtual machine as well as some storage uh provisioned already. Okay, so let's go ahead. Here we are on our onrem server. If we take a look at our FSX environment, this is our mount points. You'll see that I have a project workspace provisioned already. this there is an AWS FPGA uh demo design. There's also ESP directory and ESP is a risk five open source risk 5 design. Uh this was created to demonstrate a real development workspace. It's about 12 gig in size represents about 28,000 files spread across 17,000 directories. So this is a fairly big um environment is we're going to make this environment available these project files available in the cloud and we're going to do that by creating a flex cache in the cloud. So now we're going to switch over to our cloud environment here. And if we move to the FSX directory here and we look, you'll see there is a project directory already created. But if we look at df do, you'll see that that's just a local file system. So what we're going to do is in real time we're going to go ahead and create a flex cache which is going to um provision a volume that's defined as a flex cache volume but it's going to use the onrem cache as its source volume. As soon as this volume is created, this flex cache volume is created all of the metadata, all of the files are immediately visible to the user in the cloud. And so now if we go into that project directory, um I'm sorry, we're in the project directory. Uh we need to mount this. And now if we go into that project directory and we do at df again, you'll see that it's now mounted um as a new volume. And if I do an ls immediately, they are all the same files that we have available to us. And if we go into that ESP directory, you'll see that immediately I can see all the files. And if I wanted to edit that readme file, I could immediately open it and that file is available to me to edit in the cloud. Now to give you an idea of this environment, let's go back to the onrem environment here and let's take a look at let's go find some big files in this uh workings area. So I'm going to go list the top 10 largest files. This is going to take just a minute. And there we go. And there are the uh some very large files here. So now let's if we go and take a look at this first very large 2.3 gig size file. [snorts] If we come and say well how long does it take to go and read that file in just to do some little benchmarking. So if we go and run that we'll see that it takes about 34 seconds to read that. If we run that same command again here in the cloud environment the 2.6 or 3.6 6 gig file has not been loaded into the cloud until that first read. And so as you see, it took about 4 seconds to read that file. But once it is loaded into the cloud, once it's cached into the cloud, if we run it again, you'll see now that it performs at exactly the same speed as alocal file. And so you get that kind of performance.