# Clone and deploy the Hello World Topo Project ## In this learning path - [Introduction](https://learn.arm.com/learning-paths/cross-platform/create-your-own-topo-project/) - [Learn about Topo Projects](https://learn.arm.com/learning-paths/cross-platform/create-your-own-topo-project/overview/) - [Clone and deploy the Hello World Topo Project](https://learn.arm.com/learning-paths/cross-platform/create-your-own-topo-project/hello-world-project/) - [Modify the Hello World Topo Project](https://learn.arm.com/learning-paths/cross-platform/create-your-own-topo-project/modifying-hello-world/) - [Create a new Topo Project from an empty directory](https://learn.arm.com/learning-paths/cross-platform/create-your-own-topo-project/creating-a-new-project/) - [Use Agent Skills to author Topo Projects](https://learn.arm.com/learning-paths/cross-platform/create-your-own-topo-project/agent-skills/) - [Next Steps](https://learn.arm.com/learning-paths/cross-platform/create-your-own-topo-project/_next-steps/) ## Clone the Hello World Topo Project On your host machine, use the terminal to clone the “Hello World” Topo Project into your home directory to confirm your setup: ``` topo clone [https://github.com/Arm-Examples/topo-welcome.git](https://github.com/Arm-Examples/topo-welcome.git) ~/topo-welcome ``` The “Hello World” Topo Project follows the same deployment pattern as the “CPU LLM Chat” Topo Project covered in [Deploy containerized workloads to Arm-based Linux targets with Topo](https://learn.arm.com/learning-paths/cross-platform/deploy-containerized-workloads-with-topo/). The output is similar to: ``` __output__ ┌─ Copy files ────────────────────────────────────────── __output__ Cloning into '/home/user/topo-welcome'... __output__ remote: Enumerating objects: 12, done. __output__ remote: Counting objects: 100% (12/12), done. __output__ remote: Compressing objects: 100% (9/9), done. __output__ remote: Total 12 (delta 0), reused 8 (delta 0), pack-reused 0 (from 0) __output__ Receiving objects: 100% (12/12), 62.64 KiB | 2.61 MiB/s, done. __output__ ┌─ Configure project ─────────────────────────────────── __output__ Provide: The text to use in the greeting message __output__ Example: Markus __output__ Default: World __output__ GREETING_NAME (required)> ``` Provide a name for the `GREETING_NAME` parameter, for example, `Tomas`, and then Press Enter. The output is similar to: ``` __output__ ┌─ Project ready ─────────────────────────────────────── __output__ Created in '/home/user/topo-welcome' __output__ Now run: __output__ cd ~/topo-welcome __output__ topo deploy ``` ## Prepare your target Topo Projects are meant to be deployed to Arm-based Linux targets. In this Learning Path, use the Arm-based Linux target you prepared in the previous Learning Path. The target can be a Raspberry Pi, an Arm-based Amazon EC2 instance, or another Arm-based Linux target accessible over SSH. Confirm that Topo can inspect your target, and that there are no compatibility issues: ``` topo health --target user@my-target ``` If your host machine is a Linux machine and you want to use it as the target, you can use `--target localhost`. ## Deploy the project to your target You can now deploy the project to your target: ``` cd ~/topo-welcome topo deploy --target user@my-target ``` Wait for the build and deploy to complete. The output is similar to: ``` __output__ ┌─ Build images ──────────────────────────────────────── __output__ [+] Building 6.4s (11/11) FINISHED __output__ => [internal] load local bake definitions 0.0s __output__ => => reading from stdin 654B 0.0s __output__ => [internal] load build definition from Dockerfile 0.0s __output__ => => transferring dockerfile: 223B 0.0s __output__ => [internal] load metadata for docker.io/library/nginx:alpine 1.4s __output__ => [internal] load .dockerignore 0.1s __output__ => => transferring context: 2B 0.0s __output__ => [internal] load build context 0.1s __output__ => => transferring context: 3.76kB 0.0s __output__ => [1/3] FROM docker.io/library/ __output__ (...) __output__ [+] build 1/1 ✔ Image topo-welcome-app Built 6.4s __output__ ┌─ Pull images ───────────────────────────────────────── __output__ ┌─ Start services ────────────────────────────────────── __output__ [+] up 2/2 __output__ ┌─ Deployment Success ────────────────────────────────── 0.1s __output__ Run `topo ps` to see deployed containers 0.2s ``` Confirm that the container is running correctly: ``` topo ps --target user@my-target ``` The `topo ps` command lists the services that Topo deployed to the target. The output is similar to: ``` __output__ Image Status Processing Domain Address __output__ topo-welcome-app Up 58 seconds Linux Host my-target:8000, [::]:8000 ``` The columns show: - `Image`: the container image or service that Topo started - `Status`: whether the service is running, and how long it has been running - `Processing Domain`: where the workload is running, such as the Linux host on the target - `Address`: the exposed address and port for the service ### View the application If the target is reachable on your network, open `http://:8000/` in your browser. If you prefer to forward the port over SSH, run: ``` ssh -L 8000:localhost:8000 user@my-target ``` Then open `http://localhost:8000/` in your browser. The “Hello World” application appears as follows: ![Hello World web interface](https://learn.arm.com/learning-paths/cross-platform/create-your-own-topo-project/hello_tomas.png) Hello World web interface ## What you’ve accomplished and what’s next You’ve now deployed the “Hello World” Topo Project to an Arm-based Linux target and confirmed the application is accessible in your browser. Next, you’ll modify the project to add a new configurable clone-time argument.