> For the complete documentation index, see [llms.txt](https://docs.roboflow.com/llms.txt). Markdown versions of documentation pages are available by appending `.md` to page URLs; this page is available as [Markdown](https://docs.roboflow.com/deploy/dedicated-deployments/create-a-dedicated-deployment.md). # Create a Dedicated Deployment {% hint style="warning" %} Dedicated Deployments are not available on Public (free) tier. {% endhint %} ### Create a Deployment in the Web Interface Open your workspace dashboard page, click **Deployments** on the left panel:
Click the **New Deployment** button, it brings up the **Create a Dedicated Deployment** dialog as shown below:

Configure properties for your dedicated deployment.

Each of the properties in the dialog are described in the table below. Fill the dialog and click on the **Create Dedicated Deployment** button. It may take anywhere from a few seconds to a few minutes to provision your deployment.
PropertyDescription
Name

Choose a unique name (5-15 characters) to identify your Dedicated Deployment. This name will also become the subdomain for your deployment endpoint (e.g., dev-testing.roboflow.cloud).

  • Easy to Remember: Pick a name that clearly reflects your deployment's purpose (e.g., "prod-inference", "dev-testing").
  • Unique within Workspace: If your chosen name is already taken, a short random code will be added to create a unique subdomain.

Tips:

  • Use lowercase letters, numbers, and hyphens (-) for your name.
  • Avoid special characters or spaces.
Machine TypeWhether a CPU-only or a GPU dedicated deployment is needed.
Deployment Type

Development: ideal for development or experimental purpose, automatically expires in 3 hours.

Production: ideal for serving production requests, permanent until manually deleted.

AutoscalingThis feature is only for prod-cpu and prod-gpu.
### Create a Dedicated Deployment with the CLI The `roboflow deployment` command provides a set of subcommands to manage your Roboflow Dedicated Deployments. Before you proceed, please ensure you have the `roboflow` CLI installed and configured with your API key, as documented [here.](https://docs.roboflow.com/roboflow-cli/roboflow-cli-documentation) #### **Subcommands** * **`machine_type`**: List available machine types for your Dedicated Deployments. Currently, we support `dev-cpu, dev-gpu, prod-cpu, prod-gpu`. * **`add`**: Create a new Dedicated Deployment. * **`get`**: Get detailed information about a specific Dedicated Deployment. * **`list`**: List all Dedicated Deployments in your workspace. * **`usage_workspace`**: Get usage statistics for all Dedicated Deployments in your workspace. * **`usage_deployment`**: Get usage statistics for a specific Dedicated Deployment. * **`delete`**: Delete a Dedicated Deployment. * **`log`**: View logs for a specific Dedicated Deployment. #### **Subcommand Examples** * **Create a new deployment** ``` roboflow deployment add my-deployment -m prod-gpu -e YOUR_EMAIL@aaa.com ``` * **Get deployment information** ``` roboflow deployment get my-deployment ``` * **List all deployments** ``` roboflow deployment list ``` Use code with caution. * **Get workspace usage** ``` roboflow deployment usage_workspace ``` * **Get deployment usage** ``` roboflow deployment usage_deployment my-deployment ``` * **Delete a deployment** ``` roboflow deployment delete my-deployment ``` * **View deployment logs** ``` roboflow deployment log my-deployment -t 60 -n 20 ``` #### **Additional Notes** * For more detailed information and options for each subcommand, use the `--help` flag.