Deleting a deployment (Watson Machine Learning)

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.

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 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'

Parent topic: Managing predictive deployments