Creates a ModelMonitor.
This method waits—the workflow execution is paused—until the operation is
complete, fails, or times out. The default timeout value is 1800 seconds (30
minutes) and can be changed to a maximum value of 31536000 seconds (one year)
for long-running operations using the connector_params field. See the
Connectors reference.
The connector uses polling to monitor the long-running operation, which might generate additional billable steps. For more information about retries and long-running operations, refer to Understand connectors.
The polling policy for the long-running operation can be configured. To set the
connector-specific parameters (connector_params), refer to
Invoke a connector call.
Arguments
| Parameters | |
|---|---|
parent |
Required. The resource name of the Location to create the ModelMonitor in. Format: |
modelMonitorId |
Optional. The ID to use for the Model Monitor, which will become the final component of the model monitor resource name. The maximum length is 63 characters, and valid characters are |
region |
Required. Region of the HTTP endpoint. For example, if region is set to |
body |
Required. |
Raised exceptions
| Exceptions | |
|---|---|
ConnectionError |
In case of a network problem (such as DNS failure or refused connection). |
HttpError |
If the response status is >= 400 (excluding 429 and 503). |
TimeoutError |
If a long-running operation takes longer to finish than the specified timeout limit. |
TypeError |
If an operation or function receives an argument of the wrong type. |
ValueError |
If an operation or function receives an argument of the right type but an inappropriate value. For example, a negative timeout. |
OperationError |
If the long-running operation finished unsuccessfully. |
ResponseTypeError |
If the long-running operation returned a response of the wrong type. |
Response
If successful, the response contains an instance of GoogleLongrunningOperation.
Subworkflow snippet
Some fields might be optional or required. To identify required fields, refer to the API documentation.
YAML
- create: call: googleapis.aiplatform.v1beta1.projects.locations.modelMonitors.create args: parent: ... modelMonitorId: ... region: ... body: displayName: ... explanationSpec: metadata: featureAttributionsSchemaUri: ... inputs: ... latentSpaceSource: ... outputs: ... parameters: examples: exampleGcsSource: dataFormat: ... gcsSource: uris: ... gcsSource: ... nearestNeighborSearchConfig: ... neighborCount: ... presets: modality: ... query: ... integratedGradientsAttribution: blurBaselineConfig: maxBlurSigma: ... smoothGradConfig: featureNoiseSigma: noiseSigma: ... noiseSigma: ... noisySampleCount: ... stepCount: ... outputIndices: ... sampledShapleyAttribution: pathCount: ... topK: ... xraiAttribution: blurBaselineConfig: ... smoothGradConfig: ... stepCount: ... modelMonitoringSchema: featureFields: ... groundTruthFields: ... predictionFields: ... modelMonitoringTarget: vertexModel: model: ... modelVersionId: ... name: ... notificationSpec: emailConfig: userEmails: ... enableCloudLogging: ... notificationChannelConfigs: ... outputSpec: gcsBaseDirectory: outputUriPrefix: ... tabularObjective: featureAttributionSpec: batchExplanationDedicatedResources: machineSpec: acceleratorCount: ... acceleratorType: ... machineType: ... tpuTopology: ... maxReplicaCount: ... startingReplicaCount: ... defaultAlertCondition: threshold: ... featureAlertConditions: ... features: ... featureDriftSpec: categoricalMetricType: ... defaultCategoricalAlertCondition: ... defaultNumericAlertCondition: ... featureAlertConditions: ... features: ... numericMetricType: ... predictionOutputDriftSpec: ... trainingDataset: batchPredictionOutput: batchPredictionJob: ... columnizedDataset: bigquerySource: query: ... tableUri: ... gcsSource: format: ... gcsUri: ... timestampField: ... vertexDataset: ... timeInterval: endTime: ... startTime: ... timeOffset: offset: ... window: ... vertexEndpointLogs: endpoints: ... result: createResult
JSON
[ { "create": { "call": "googleapis.aiplatform.v1beta1.projects.locations.modelMonitors.create", "args": { "parent": "...", "modelMonitorId": "...", "region": "...", "body": { "displayName": "...", "explanationSpec": { "metadata": { "featureAttributionsSchemaUri": "...", "inputs": "...", "latentSpaceSource": "...", "outputs": "..." }, "parameters": { "examples": { "exampleGcsSource": { "dataFormat": "...", "gcsSource": { "uris": "..." } }, "gcsSource": "...", "nearestNeighborSearchConfig": "...", "neighborCount": "...", "presets": { "modality": "...", "query": "..." } }, "integratedGradientsAttribution": { "blurBaselineConfig": { "maxBlurSigma": "..." }, "smoothGradConfig": { "featureNoiseSigma": { "noiseSigma": "..." }, "noiseSigma": "...", "noisySampleCount": "..." }, "stepCount": "..." }, "outputIndices": "...", "sampledShapleyAttribution": { "pathCount": "..." }, "topK": "...", "xraiAttribution": { "blurBaselineConfig": "...", "smoothGradConfig": "...", "stepCount": "..." } } }, "modelMonitoringSchema": { "featureFields": "...", "groundTruthFields": "...", "predictionFields": "..." }, "modelMonitoringTarget": { "vertexModel": { "model": "...", "modelVersionId": "..." } }, "name": "...", "notificationSpec": { "emailConfig": { "userEmails": "..." }, "enableCloudLogging": "...", "notificationChannelConfigs": "..." }, "outputSpec": { "gcsBaseDirectory": { "outputUriPrefix": "..." } }, "tabularObjective": { "featureAttributionSpec": { "batchExplanationDedicatedResources": { "machineSpec": { "acceleratorCount": "...", "acceleratorType": "...", "machineType": "...", "tpuTopology": "..." }, "maxReplicaCount": "...", "startingReplicaCount": "..." }, "defaultAlertCondition": { "threshold": "..." }, "featureAlertConditions": "...", "features": "..." }, "featureDriftSpec": { "categoricalMetricType": "...", "defaultCategoricalAlertCondition": "...", "defaultNumericAlertCondition": "...", "featureAlertConditions": "...", "features": "...", "numericMetricType": "..." }, "predictionOutputDriftSpec": "..." }, "trainingDataset": { "batchPredictionOutput": { "batchPredictionJob": "..." }, "columnizedDataset": { "bigquerySource": { "query": "...", "tableUri": "..." }, "gcsSource": { "format": "...", "gcsUri": "..." }, "timestampField": "...", "vertexDataset": "..." }, "timeInterval": { "endTime": "...", "startTime": "..." }, "timeOffset": { "offset": "...", "window": "..." }, "vertexEndpointLogs": { "endpoints": "..." } } } }, "result": "createResult" } } ]