 Hi, this is Hospil Bhartia and welcome to another episode of TO5 Let's See or demos. And today we have with us once again, Mike Peterson, Senior Technical Marketing Engineer at Love Labs. Mike, it's great to have you on the show. Hey, I'm gonna show off DevPod today. It's great to be here. Thanks for having me. So this is DevPod. We're looking at right now our workspaces. Workspaces are GitHub repositories that we have linked up to a provider. So let me show you what a provider is too. So provider is something like Docker or Kubernetes or any of these providers. Plus, there's the ability to add a custom and other providers if you don't see what you're using here. So like say you wanna use like AWS provider. What that'll do is launch a virtual machine and install Docker and then we'll be able to run the workspace in there. Let's go ahead and walk through the workspace demo since we already have a couple of providers. Right now I've got provider of Docker that's running locally and then I got a Kubernetes server that's actually running in a server in my house. So let's create a new workspace. So what we'll start out with is a Quick Starts example. So we're gonna run a Python example. It's just github.com, Microsoft. VS Code, remote try Python. So it's just a basic environment where we can test bringing up VS Code with this. So we're gonna create the workspace with the provider of Docker and our ID we're gonna use is VS Code. So basically just hit create workspace. This GitHub repository could be something that you're working on. It could be anything besides this. This is just the example one. All right, so create a workspace and what that's gonna do is it's gonna create the dev container for us. It's gonna download the dev pod agent because all of these things in the UI are backed up by a CLI. So you can do a lot of this stuff on the command line too which I'll show after we show this off. And what this is gonna bring what it's gonna do is it's gonna bring up VS Code and it's gonna bring up that repository for us and as soon as it comes up. All right, so what it's doing is it's bringing up a container in Docker and it's setting up SSH to it. So it's gonna SSH into it and then we're gonna be able to see our repository over here and we'll make some changes. Okay, so right now we've got the Python application open and it's just like I said, it's just an example application so it's just a default like Flask app and it's just serving up, VS Code can do that, yes it can. So what we can do is we can run the application and what that's gonna do is it's gonna port forward for us. So this is running in Docker locally but it could be running in Kubernetes or something like that. It'll port forward for us so that we can look at our changes on our local machine. So say I open this up in a browser. All right, so we can actually see real-time changes too. So if we go in here and we say it's even better with dev pod and save go over here and refresh then we can see it's even better with dev pod shows up. And that's just showing that we can make changes and they'll be saved within the container. Now, once we're done, we can just close out of VS Code and go back to dev pod and we can see that it's running currently here. So what we can do is we can stop it and then we wanna work on it again later in Docker. We can do that. We can just hit open and it'll open back up. But let's create the same thing but say we wanna do it now in a Kubernetes cluster instead of doing it locally. So we'll do Python. We'll pick a provider of Kubernetes. We'll use VS Code as our default IDE and then we'll create a workspace. And what this is gonna do is it's actually gonna run it in my Kubernetes instance that's up down in my basement. And then this is just gonna run in a pod and it's gonna have a container created for it. And then what we can do is basically the same thing as what we're doing in Docker but we're doing it in Kubernetes. So say you've got access Kubernetes clusters you wanna run there instead of running locally like you want faster tests or something like that or you want a little bit more power than your laptop has. This is a great way to do that. All right, now it's coming up. See the pods coming up right now. And then once it's up it'll set up a remote connection into it and then it'll be just like Docker. So this is running, like I said, not on my local machine this is running somewhere else. All right, let's trust. All right, let's open up the same stuff that we had open in the other one. And you see this is empty. We have, there's no updates here because this is actually a brand new container with a different state than the one we were running in Docker. Let's go ahead and run the application again. And then we can say even on Kubernetes. And then save this. And then we can open this and our changes are there. So this was running Kubernetes. The other one was running in Docker. We can go between the two that we wanna work in a different environment. And then we also have other providers that you can add in say you don't wanna work off of Docker or Kubernetes and you wanna work off of AWS. Well, in AWS what it's gonna do is it's gonna create a virtual machine and then on that virtual machine it'll install Docker and then it'll use the same dev container configuration to bring up your environment there. So what you would do is just add an AWS provider you would put in your region and then you would go down to options and put in your access key ID, your secret access key ID. And if you wanna use a specific AMI you could use that and then you can say what instance type you wanna use. So you can use something smaller or much larger and then say you wanna use like a graphics card or something like that. You could do something like that too. Like say you have development that needs a graphics card to test stuff out. Like maybe like doing some inference. There's also a command line for Dev Pod so you can do a lot of this via the command line which makes it a little bit easier to automate some of the setup and the configuration. So if we go to the CLI, we can do Dev Pod and we can see a bunch of the commands. We can say Dev Pod list and that'll show us the different things that we're running and the repositories that are connected to them. We can do Dev Pod provider list and that'll show us the different providers we've got set up. We have Docker and Kubernetes running. I was like Azure's an alpha. And then we can also start what we have running. So we can say Dev Pod up and then we can do Dev Pod Docker which is one of the things that I have running. And what that'll do is bring up the Dev Pod GitHub repository and VS code which is my default IDE. We also have multiple other IDEs that you can use if you looked at when we create a workspace. So say you're, you know, GoLand, PyCharm or any of these other ones, you can use that. We've got VS code in the browser which I can show that off to real quick. Let's go back and we'll create a works, okay, we'll start from here. We'll create a workspace. We'll create a Go workspace and we'll go to the VS code browser. We'll put this in Docker and create workspace. What this is gonna do is it's gonna bring up a different ID than we've been using. Our default is VS code. But like I said, you could run it in a browser if you want to instead or you can use a different provider or different IDEs like GoLand or whatever, you know whatever your favorite are from like JetBrains. All right, so it's gonna take a minute just cause it's a new one. All right, and now VS code's coming up in a browser and there we go. Same, same deal. So you can use whatever you wanna use. You can use a browser if you want to maybe eventually we'll have an iPad app and you can develop from your iPad but right now everything is desktop stuff. And that's pretty much the demo showing off like the CLI and all that stuff. Why would someone prefer DevPod versus you know other solutions out there? So DevPod is agent only so you don't have to install something on a remote server or anything like that to get this running. I think that's one of the downsides maybe of some of the other options out there is that the platform team and stuff defines where you wanna run this or say you're just a developer and you wanna run locally in Docker or you wanna run on a Kubernetes cluster or you have running or you have access to AWS or cloud resources. You can run this anywhere without having an agent audience or without having something already installed server side. So basically it's agent driven. Also it's open source so if you wanna write your own provider and make customizations for that you could do that and I mean it's pretty new so hopefully the development of this continues to make it easier for users to use something like this. Of course we have seen how it works. Now can you also share with us how folks can get started with DevPod? Okay, yeah, yeah. So you can go to devpod.sh and that's gonna give you links to GitHub. It's gonna have a video and other information about how to use DevPod DevPods on our GitHub too. It's actually right here. GitHub.com, loft-shdevpod. You can go there too and star it, take a look at it, get it running but if you go to devpod.sh that's gonna give you a way to install and get started and it'll give you a link to the docs. If you have questions or you need help or anything like that just join our Slack, slack.loft.sh and join the DevPod channel and we're in there and we can help out if you run any problems or open something in GitHub like open a creating issue or something like that if you run into any problems. Mike, thank you so much for joining me today. Show us how DevPod works and I would love to chat with you again soon. Thank you. Awesome, thank you.