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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:
- 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 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 deployments