Create a Deployment via the CLI

To create Deployments from the CLI, be sure first to install the CLI.

The Gradient CLI contains the following subcommands for Deployments: create, list, start, stop. You can always see the available subcommands simply by entering gradient deployments, and you can always learn more about any command by appending --help to it.

Available Deployments Commands

Create a Deployment

To create a new Deployment, you must first create a Model. With a Model available, use the create subcommand and specify all of the following parameters: deployment type, base image, name, machine type, and container image for serving, as well as the instance count:

A sample command to create the same Deployment as in the UI example would be:

gradient deployments create \
--deploymentType TFServing \
--modelId <your-model-id> \
--name "Sample Model"
--machineType K80
--imageUrl tensorflow/serving:latest-gpu
--instanceCount 2

To obtain your Model ID, you can use the command gradient models list and copy the target Model ID from your available Models.

List Deployments

To list your Deployments with optional filtering, use the list subcommand:

For example, to view all running deployments in your team, run:

gradient list --state RUNNING

Start a Deployment

To start a previously created but Stopped deployment by ID, use the start subcommand:

gradient deployments start --id <your-deployment-id>

Stop a Deployment

To stop a Running deployment by ID, use the stop subcommand:

gradient deployments stop --id <your-deployment-id>