Deleting a deployment
Delete your deployment when you no longer need it to free up resources. You can delete a deployment from a deployment space, or programmatically, by using the Python client or Watson Machine Learning APIs.
Before you begin
You must set up your task credentials by generating an API key. For more information, see Managing task credentials.
Deleting a deployment from a space
To remove a deployment:
- Open the Deployments page of your deployment space.
- Choose Delete from the action menu for the deployment name.
Deleting a deployment programmatically
You can delete a deployment programmatically by using the watsonx.ai Python client library, Watson Machine Learning API, or CPDCTL.
Deleting a deployment by using the Python client
Use the following method to delete the deployment.
client.deployments.delete(deployment_uid)
Returns a SUCCESS message. To check that the deployment was removed, you can list deployments and make sure that the deleted deployment is no longer listed.
client.deployments.list()
Returns:
GUID NAME STATE CREATED ARTIFACT_TYPE
Deleting a deployment by using the REST API
Use the DELETE method for deleting a deployment.
DELETE /ml/v4/deployments/{deployment_id}
For more information, see Delete.
For example, see the following code snippet:
curl --location --request DELETE 'https://us-south.ml.cloud.ibm.com/ml/v4/deployments/:deployment_id?space_id=<string>&version=2020-09-01'
Deleting a deployment by using CPDCTL
You can delete your deployment space by using the ml deployment delete command in CPDCTL and passing your deployment space ID. For more information, see CPDCTL command reference.
Parent topic: Managing predictive deployments