 Hello everyone, my name is Anya Keenan. I'm a developer advocate intern here at Red Hat and today I'm going to be giving you an introduction to the Podman desktop application and how we can use it to deploy pods to the developer sandbox hosted by Red Hat. If you do not already have the developer sandbox extension downloaded let's go ahead and do that now. Podman desktop will provide a number of featured extensions as seen here but if you want more you can head over to settings desktop extensions and enter the extensions OCI image name and you'll be able to pull it and add it. I've added the live charts extension and the Grafana extension. Under settings and resources we can go ahead and create a new Kubernetes context of the developer sandbox. You'll be sent straight to login to the OpenShift web console from here. The developer sandbox has 14 gigabytes of RAM and 40 gigabytes of memory. The trial will last for 30 days and you can renew it at the end. Under the username we'll be able to find our OpenShift login command that we can paste into Podman desktop. So when we copy this over we'll also be able to add our name for our developer sandbox. I will name this AK Sandbox. As well as this command working in Podman desktop we can also run it in the terminal to get logged in. We've connected to our developer sandbox so let's go ahead and deploy some Kubernetes pods onto it. When we head over to the images tab we'll notice this pull an image button and we'll be asked to input the image name. Here I have a registry quay with the image just like how you would normally write podman pull and the image name. Here we can just copy the image name and insert it into podman desktop. We have this integrated terminal that will show us the logs and it'll pull the image for us. Here is the image that we pulled. You can go ahead and start it to create a container. You can enter a custom name or leave a blank to have one generated for you. I'll name this Python app. The rest of this I will leave to the default configurations that Podman desktop has chosen. Here under containers we can see that our Python container is running. When we click on it we can see the logs and the summary that holds its ID and what ports it's running on. Under inspect we can see the low-level information about the container in JSON format. One of the coolest parts about the Podman desktop is that a Kubernetes manifest will automatically be generated for you. A Kubernetes manifest to create a pod will be generated for any containers, pods or volumes that you have. We also have an integrated terminal here. Let's go ahead and make a pod. We already have one container running so let's make this a bit more fun and pull another image and get another container running. When the containers you'd like to combine together to make a pod are selected this pod icon will give you a quick summary of which containers will be replicated and it will allow you to name your pod. When a pod is created Podman desktop automatically generates the Kubernetes manifest. Let's go ahead and deploy this pod to the sandbox. When we head to the top of our screen we can select the Kubernetes context we'd like to deploy to. As we created earlier I'll deploy to AK sandbox. This rocket ship icon will allow us one more chance to add the name of our pod. I'll say hello at the end and then we can click deploy. Here we can see that the pods are pending and now they're running and when we head over to our sandbox Python Redis hello is there. Just like in Podman desktop when you click on a pod you can view more information about it including its networking. When we click on the exposure tool provided in the sandbox our application is alive and well. If you haven't already take some time to explore Red Hat developer sandbox. It provides some really cool tools like observing your clusters and Red Hat OpenShift Dev Spaces which allows you to edit your code right in the browser. Podman desktop was created to reduce the friction that developers feel between their local environment and the Kubernetes deployment environment. As you can see here even on a small scale of just deploying to the developer sandbox the process is relatively easy and frictionless. We hope this will help you in deploying to your bigger OpenShift clusters as well.