- gcloud alpha ai-platform models add-iam-policy-binding - add IAM policy binding for a model
(ALPHA)Adds a policy binding to the IAM policy of a ML engine model, given a model ID and the binding. One binding consists of a member, a role, and an optional condition.
- POSITIONAL ARGUMENTS
- Name of the model.
- REQUIRED FLAGS
The member to add the binding for. Should be of the form
Can also be one of the following special values:
allUsers- Special identifier that represents anyone who is on the internet, with or without a Google account.
allAuthenticatedUsers- Special identifier that represents anyone who is authenticated with a Google account or a service account.
- Define the role of the member.
- OPTIONAL FLAGS
Google Cloud region of the regional endpoint to use for this command. If
unspecified, the command uses the global endpoint of the AI Platform Training
and Prediction API.
Learn more about regional endpoints and see a list of available regions: https://cloud.google.com/ai-platform/prediction/docs/regional-endpoints
REGIONmust be one of:
At most one of these may be specified:
Condition of the binding to be added. When condition is explicitly specified as
None(e.g. --condition=None), a binding without a condition is added. When --condition is specified and is not a
--rolecannot be a primitive role. Primitive roles are
- (Required) Expression of the condition which evaluates to True or False. This uses a subset of Common Expression Language syntax.
- (Required) Title for the expression, i.e. a short string describing its purpose.
(Optional) Description for the expression. This is a longer text which describes
NOTE: An unsatisfied condition will not allow access via this binding.
Path to a local JSON or YAML file that defines the condition. To see available
fields, see the help for
- GCLOUD WIDE FLAGS
These flags are available to all commands: --account, --billing-project, --configuration, --flags-file, --flatten, --format, --help, --impersonate-service-account,
--log-http, --project, --quiet, --trace-token, --user-output-enabled,
$ gcloud helpfor details.
To add an IAM policy binding for the role of 'roles/ml.admin' for the user
'email@example.com' on a model with identifier 'my_model', run:
$ gcloud alpha ai-platform models add-iam-policy-binding my_model \ --member='user:firstname.lastname@example.org' --role='roles/ml.admin'
To add an IAM policy binding for the role of 'roles/ml.admin' to the service account 'email@example.com', run:
$ gcloud alpha ai-platform models add-iam-policy-binding my_model \ --member='serviceAccount:firstname.lastname@example.org' \ --role='roles/ml.admin'
To add an IAM policy binding for the role of 'roles/ml.admin' for all authenticated users on a model with identifier 'my_model', run:
$ gcloud alpha ai-platform models add-iam-policy-binding my_model \ --member='allAuthenticatedUsers' --role='roles/ml.admin'To add an IAM policy binding which expires at the end of the year 2018 for the role of 'roles/ml.admin' and the user 'email@example.com' on a model with identifier 'my_model', run:
$ gcloud alpha ai-platform models add-iam-policy-binding my_model \ --member='user:firstname.lastname@example.org' --role='roles/ml.admin' \ --condition='expression=request.time < timestamp("2019-01-01T00:00:00Z"),title=expires_end_of_2018,descrip\ tion=Expires at midnight on 2018-12-31'
See https://cloud.google.com/iam/docs/managing-policies for details of policy role and member types.
- This command is currently in ALPHA and may change without notice. If this command fails with API permission errors despite specifying the right project, you may be trying to access an API with an invitation-only early access whitelist. These variants are also available:
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Last updated 2020-05-27.