- NAME
-
- gcloud alpha ai model-monitoring-jobs update - update an Vertex AI model deployment monitoring job
- SYNOPSIS
-
-
gcloud alpha ai model-monitoring-jobs update
(MONITORING_JOB
:--region
=REGION
) [--analysis-instance-schema
=ANALYSIS_INSTANCE_SCHEMA
] [--[no-]anomaly-cloud-logging
] [--display-name
=DISPLAY_NAME
] [--emails
=[EMAILS
,…]] [--log-ttl
=LOG_TTL
] [--monitoring-frequency
=MONITORING_FREQUENCY
] [--notification-channels
=[NOTIFICATION_CHANNELS
,…]] [--prediction-sampling-rate
=PREDICTION_SAMPLING_RATE
] [--update-labels
=[KEY
=VALUE
,…]] [--clear-labels
|--remove-labels
=[KEY
,…]] [--monitoring-config-from-file
=MONITORING_CONFIG_FROM_FILE
|--feature-attribution-thresholds
=[KEY
=VALUE
,…]--feature-thresholds
=[KEY
=VALUE
,…]] [GCLOUD_WIDE_FLAG …
]
-
- DESCRIPTION
-
(ALPHA)
Update an Vertex AI model deployment monitoring job. - EXAMPLES
-
To update display name of model deployment monitoring job
123
under projectexample
in regionus-central1
, run:gcloud alpha ai model-monitoring-jobs update 123 --display-name=new-name --project=example --region=us-central1
- POSITIONAL ARGUMENTS
-
-
Monitoring job resource - The model deployment monitoring job to update. The
arguments in this group can be used to specify the attributes of this resource.
(NOTE) Some attributes are not given arguments in this group but can be set in
other ways.
To set the
project
attribute:-
provide the argument
monitoring_job
on the command line with a fully specified name; -
provide the argument
--project
on the command line; -
set the property
core/project
.
This must be specified.
MONITORING_JOB
-
ID of the monitoring_job or fully qualified identifier for the monitoring_job.
To set the
name
attribute:-
provide the argument
monitoring_job
on the command line.
This positional argument must be specified if any of the other arguments in this group are specified.
-
provide the argument
--region
=REGION
-
Cloud region for the monitoring_job.
To set the
region
attribute:-
provide the argument
monitoring_job
on the command line with a fully specified name; -
provide the argument
--region
on the command line; -
set the property
ai/region
; - choose one from the prompted list of available regions.
-
provide the argument
-
provide the argument
-
Monitoring job resource - The model deployment monitoring job to update. The
arguments in this group can be used to specify the attributes of this resource.
(NOTE) Some attributes are not given arguments in this group but can be set in
other ways.
- FLAGS
-
--analysis-instance-schema
=ANALYSIS_INSTANCE_SCHEMA
- YAML schema file uri(Google Cloud Storage) describing the format of a single instance that you want Tensorflow Data Validation (TFDV) to analyze.
--[no-]anomaly-cloud-logging
-
If true, anomaly will be sent to Cloud Logging. Use
--anomaly-cloud-logging
to enable and--no-anomaly-cloud-logging
to disable. --display-name
=DISPLAY_NAME
- Display name of the model deployment monitoring job.
--emails
=[EMAILS
,…]- Comma-separated email address list. e.g. --emails=a@gmail.com,b@gmail.com
--log-ttl
=LOG_TTL
- TTL of BigQuery tables in user projects which stores logs(Day-based unit).
--monitoring-frequency
=MONITORING_FREQUENCY
- Monitoring frequency, unit is 1 hour.
--notification-channels
=[NOTIFICATION_CHANNELS
,…]- Comma-separated notification channel list. e.g. --notification-channels=projects/fake-project/notificationChannels/123,projects/fake-project/notificationChannels/456
--prediction-sampling-rate
=PREDICTION_SAMPLING_RATE
- Prediction sampling rate.
--update-labels
=[KEY
=VALUE
,…]-
List of label KEY=VALUE pairs to update. If a label exists, its value is
modified. Otherwise, a new label is created.
Keys must start with a lowercase character and contain only hyphens (
-
), underscores (_
), lowercase characters, and numbers. Values must contain only hyphens (-
), underscores (_
), lowercase characters, and numbers. -
At most one of these can be specified:
--clear-labels
-
Remove all labels. If
--update-labels
is also specified then--clear-labels
is applied first.For example, to remove all labels:
gcloud alpha ai model-monitoring-jobs update --clear-labels
To remove all existing labels and create two new labels,
andfoo
:baz
gcloud alpha ai model-monitoring-jobs update --clear-labels --update-labels foo=bar,baz=qux
--remove-labels
=[KEY
,…]-
List of label keys to remove. If a label does not exist it is silently ignored.
If
--update-labels
is also specified then--update-labels
is applied first.
-
At most one of these can be specified:
--monitoring-config-from-file
=MONITORING_CONFIG_FROM_FILE
-
Path to the model monitoring objective config file. This file should be a YAML
document containing a
ModelDeploymentMonitoringJob
(https://cloud.google.com/vertex-ai/docs/reference/rest/v1beta1/projects.locations.modelDeploymentMonitoringJobs#ModelDeploymentMonitoringJob), but only the ModelDeploymentMonitoringObjectiveConfig needs to be configured.Note: Only one of --monitoring-config-from-file and other objective config set, like --feature-thresholds, --feature-attribution-thresholds needs to be set.
Example(YAML):
modelDeploymentMonitoringObjectiveConfigs: - deployedModelId: '5251549009234886656' objectiveConfig: trainingDataset: dataFormat: csv gcsSource: uris: - gs://fake-bucket/training_data.csv targetField: price trainingPredictionSkewDetectionConfig: skewThresholds: feat1: value: 0.9 feat2: value: 0.8 - deployedModelId: '2945706000021192704' objectiveConfig: predictionDriftDetectionConfig: driftThresholds: feat1: value: 0.3 feat2: value: 0.4
--feature-attribution-thresholds
=[KEY
=VALUE
,…]-
List of feature-attribution score threshold value pairs(Apply for all the
deployed models under the endpoint, if you want to specify different thresholds
for different deployed model, please use flag --monitoring-config-from-file or
call API directly). If only feature name is set, the default threshold value
would be 0.3.
For example:
feature-attribution-thresholds=feat1=0.1,feat2,feat3=0.2
--feature-thresholds
=[KEY
=VALUE
,…]-
List of feature-threshold value pairs(Apply for all the deployed models under
the endpoint, if you want to specify different thresholds for different deployed
model, please use flag --monitoring-config-from-file or call API directly). If
only feature name is set, the default threshold value would be 0.3.
For example:
--feature-thresholds=feat1=0.1,feat2,feat3=0.2
- GCLOUD WIDE FLAGS
-
These flags are available to all commands:
--access-token-file
,--account
,--billing-project
,--configuration
,--flags-file
,--flatten
,--format
,--help
,--impersonate-service-account
,--log-http
,--project
,--quiet
,--trace-token
,--user-output-enabled
,--verbosity
.Run
$ gcloud help
for details. - NOTES
-
This command is currently in alpha and might change without notice. If this
command fails with API permission errors despite specifying the correct project,
you might be trying to access an API with an invitation-only early access
allowlist. These variants are also available:
gcloud ai model-monitoring-jobs update
gcloud beta ai model-monitoring-jobs update
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Last updated 2024-02-06 UTC.