Deleting a deployment (Watson Machine Learning)

When you are done with a deployment, it is a best practice to delete 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:

  1. Open the Deployments page of your deployment space.
  2. Choose Delete from the action menu for the deployment name.
    Deleting a deployment

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 example:

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