--- url: /en/self_host/docker/deploy.md --- # Deploying with Docker To deploy SwanLab Community Edition privately, follow the installation steps below. ![logo](https://swanlab-docs-1301372061.cos.ap-beijing.myqcloud.com/assets/en/guide_cloud/self_host/docker-deploy/swanlab-docker.jpg) ## Prerequisites > Before installing SwanLab, ensure your machine meets the following minimum system requirements: > > * CPU >= 2 cores > * Memory >= 4GB > * Storage space >= 20GB SwanLab Community Edition requires **Docker Compose** for installation and deployment. Refer to the table below to select the correct Docker and Compose versions based on your operating system. **If Docker is already installed, skip this step.** | Operating System | Software | Notes | | ---------------------------- | --------------------------------------------------- | ------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------ | | macOS 10.14 or later | Docker Desktop | Configure the Docker VM to use at least 2 vCPUs and 8 GB of initial memory. Otherwise, installation may fail. For more details, refer to the [Docker Desktop for Mac Installation Guide](https://docs.docker.com/desktop/install/mac-install/). | | Windows (with WSL 2 enabled) | Docker Desktop | We recommend storing source code and other Linux container-bound data in the Linux filesystem rather than the Windows filesystem. For more details, refer to the [How to install Linux on Windows with WSL](https://learn.microsoft.com/en-us/windows/wsl/install) and [Docker Desktop for Windows with WSL 2 Backend Installation Guide](https://docs.docker.com/desktop/setup/install/windows-install/#wsl-2-backend). | | Linux | Docker 19.03 or later, Docker Compose 1.28 or later | For installation instructions, refer to the [Docker Installation Guide](https://docs.docker.com/engine/install/) and [Docker Compose Installation Guide](https://docs.docker.com/compose/install/). | > If Docker is not installed, you can run the provided [installation script](https://docs.docker.com/desktop/install/mac-install/). *** **Port Configuration** If you deploy SwanLab on a server and want to remotely access and view experiment records, ensure that the server opens the following two ports: | Port | Configurable | Description | | ---- | ------------ | ----------------------------------------------------------------------------------------------------- | | 8000 | Yes | Gateway service port. Handles external requests. For public deployments, consider setting it to `80`. | | 9000 | No | MinIO signature port for object storage access. This port is fixed and cannot be changed. | > Since the gateway service port (default `8000`) can be modified before and after deployment, please ensure that you have opened the final modified port. ## 1. Clone the Repository Clone the `self-hosted` repository using Git: ```bash git clone https://github.com/SwanHubX/self-hosted.git cd self-hosted ``` ## 2. One-Click Installation > If you are using Windows, please make sure you have installed and enabled WSL2 and Docker Desktop. > Execute the `.sh` installation script in the WSL2 filesystem. The default installation script is located at `docker/install.sh`. Execute it to install all required containers and perform initial configurations. ```bash cd ./docker ./install.sh ``` The default script link uses a mirror source in China, so the download speed in China is very fast! If you prefer to use [DockerHub](https://hub.docker.com/) as the image registry, run the following script: ```bash ./install-dockerhub.sh ``` ## 3. Activate the Primary Account SwanLab Community Edition uses port `8000` by default. If using the default configuration, access it at: `http://localhost:8000`. > If the community edition is deployed on a different port, open Docker Desktop, locate the port mapping for the `traefik` container (e.g., `64703:80`), and access `http://localhost:64703`. ![](https://swanlab-docs-1301372061.cos.ap-beijing.myqcloud.com/assets/en/guide_cloud/self_host/docker-deploy/create-account.png) Now, activate your primary account. Activation requires 1 License, which can be obtained for free from the [SwanLab Official Website](https://swanlab.cn) for personal use. :::warning Offline Verification In versions > `v1.1` of private deployment, it supports verifying the License in an offline environment. ::: ![](https://swanlab-docs-1301372061.cos.ap-beijing.myqcloud.com/assets/en/guide_cloud/self_host/docker-deploy/apply-license.png) Once you have the License, return to the activation page, enter your username, password, confirm password, and License, then click "Activate" to complete the setup. ![](https://swanlab-docs-1301372061.cos.ap-beijing.myqcloud.com/assets/en/guide_cloud/self_host/docker-deploy/quick-start.png) ## 4. Start Your First Experiment Log in using the Python SDK: ```bash swanlab login --host ``` > If you have previously logged in and wish to re-login, use: > `swanlab login --host --relogin`. Press Enter, enter your API Key, and complete the login. Your SwanLab experiments will now be uploaded to your private SwanLab instance by default. *** Test Script: ```bash import swanlab import random # Create a SwanLab project swanlab.init( # Set project name project="my-awesome-project", # Set hyperparameters config={ "learning_rate": 0.02, "architecture": "CNN", "dataset": "CIFAR-100", "epochs": 10 } ) # Simulate a training session epochs = 10 offset = random.random() / 5 for epoch in range(2, epochs): acc = 1 - 2 ** -epoch - random.random() / epoch - offset loss = 2 ** -epoch + random.random() / epoch + offset # Log training metrics swanlab.log({"acc": acc, "loss": loss}) # [Optional] Complete the training, necessary in notebook environments swanlab.finish() ``` View the experiment on the web after running: ![](https://swanlab-docs-1301372061.cos.ap-beijing.myqcloud.com/assets/en/guide_cloud/self_host/docker-deploy/test-experiment.png) ## Upgrade Version If you want to upgrade your local self-hosted deployment to the latest version, use the following commands: ```bash # Navigate to your previously deployed self-hosted project directory cd ./docker ./upgrade.sh ``` Command-line output after a successful upgrade: ![](https://swanlab-docs-1301372061.cos.ap-beijing.myqcloud.com/assets/en/guide_cloud/self_host/docker-deploy/upgrade.png)