 Hi, meet Sarah. Sarah is a software developer working for an organization. Currently, she has a very difficult task at hand. Her business needs her and she is writing apps that kind of solve her business challenges right now. She finally gets her app to work, tests it and, you know, everything is working great. Sarah is excited. All Sarah wants to do now is just deploy the app, see how it works, maybe do some AP testing and get it going. Now, in order to do so, Sarah first has to convert her code into a running container image where she can then deploy it on a platform. So she first has to start off by creating a Docker file where she has to input kind of more of the runtime dependencies that her app needs, what kind of language it is, etc. And then finally she will build that application into a container image. Once she has done that, she then has to deploy that onto Kubernetes, but then she has to write a bunch of YAML, understand what how Kubernetes operates, you know, create deployments, create services, all of that stuff. Now this can be very challenging and frustrating for Sarah because all she wants to do is test her app and see how it works out. Now I'm going to introduce Sarah to the 3K. Kubernetes, K-Mative and K-Pack combined together can help solve her problem. How you ask? Let's see how this works. So the way to go about this would be if Sarah could use buildpacks to actually automatically create container images and then use K-Mative that could be running on the same Kubernetes cluster that she wants to deploy her apps to actually build out scalable microservices. These microservices could scale down to zero when there's no traffic or scale out as needed. So let's take a look at how this can be done. Now for this demo, I already have a Kubernetes cluster deployed and I am using Optin, which is an open source tool to kind of view what goes on within your Kubernetes cluster. It's pretty neat. So for that cluster, I already have K-Pack deployed on it. Installing K-Pack is pretty easy. K-Pack is basically a tool for consuming cloud-native buildpacks. So if you want to use cloud-native buildpacks, you could also use Pack, which is a CLI-based command line tool that you could install on your laptop using homebrew or something or even on any other machine. Or you could consume things using K-Pack, which actually gets deployed on a Kubernetes cluster. And for this purpose, for the purpose of this demo, I'm actually going to use K-Pack. I also have K-Native deployed over here on the same cluster. Again, installing K-Native is pretty standard. The documentation on their website covers that. There's nothing going on over here because we are not yet consuming K-Native. Now, imagine Sarah is actually working on an application called Spring Pet Clinic. This is a very popular spring boot application. And this is the repo that she's going to work on. So this is what we'll be using as an example. And then you're going to use a Docker Hub as a way to start publishing our images. So to start off with, we'll need to build a very simple spec file for K-Pack. So Sarah has to just supply a very few details over here. For example, what does she want to call her image once it's built? What tags that she want to give that image? The service account to use, which has access to the repo that she's going to use, in my case, I'm going to use Docker Hub. So this service account actually understands how to get to Docker Hub and the credentials for that. And then which get URL or where is my source code. So, you know, we are using Spring Pet Clinic for this sample. So here is this source code where I want the K-Pack to build images based on that. So it's pretty standard. So let's go ahead and apply this. So if you've noticed an opt-in, you'll start seeing images being created. Tutorial Image has started building. And to look at what's going on, this build process might take a little bit, but if you want to see what's going on, you can actually load image logs for that. So you'll see what's going on in the back end over here. All right, so it looks like the build has been successful. And if we go and check our images over here, you'll see that this image is ready. And it has actually been pushed to this particular Docker repo. So this is where image resides. So if I log on to my Docker Hub account, you'll see a new build was created just a minute ago. And it also has the latest stack. All right, so now that we have the, you know, this is the way, you know, Sarah could actually automate her image. Now we need to, you know, now she still needs to push this image to Kubernetes without having to write, you know, without having to worry about all the different objects needed to actually get her an addressable URL. So that's where we'll be using Knado. Now we already have the image name and I'm using the Knado CLI to do so. So my Knado is going to point to the Kubernetes cluster where Knado is installed. So the KNCLI will talk to that API server. And all I have to do is ask it to create a service. Let's call it let clinic and give it an image. The image is just that we created or actually Kpack built for us. Okay, so pet clinic is ready. And you can see the images created in if you go back to opt-in. I look at our Knado dashboard over here. You'll see that, you know, the service called pet clinic was created. It already has a URL that, you know, Knado went and created using Kubernetes using ingress and all of the configurations needed. You'll also see that, you know, there are boards that are now serving that particular application. At the same time, appropriate deployments, replica sets, et cetera, have been created for that service. And all of us, all of this was completely automatic. So now just to take a look at their application, how it looks within Kubernetes, all we have to do is go click the URL that Knado created for us. And there we go. So pet clinic is running within that Kubernetes cluster. It already has a URL and all the deployment properties taken care of automatically by Knado. So this is how using Kpack or cloud native build packs and Knado serving. So I could actually automate a lot of her tasks that she needs to do through a combination of Knado and cloud native build packs. Thank you for watching this demo.