Updates a ModelDeploymentMonitoringJob.
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 | |
---|---|
name |
Required. Output only. Resource name of a ModelDeploymentMonitoringJob. |
updateMask |
Required. The update mask is used to specify the fields to be overwritten in the ModelDeploymentMonitoringJob resource by the update. The fields specified in the update_mask are relative to the resource, not the full request. A field will be overwritten if it is in the mask. If the user does not provide a mask then only the non-empty fields present in the request will be overwritten. Set the update_mask to |
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
- patch: call: googleapis.aiplatform.v1beta1.projects.locations.modelDeploymentMonitoringJobs.patch args: name: ... updateMask: ... region: ... body: analysisInstanceSchemaUri: ... displayName: ... enableMonitoringPipelineLogs: ... encryptionSpec: kmsKeyName: ... endpoint: ... labels: ... logTtl: ... loggingSamplingStrategy: randomSampleConfig: sampleRate: ... modelDeploymentMonitoringObjectiveConfigs: ... modelDeploymentMonitoringScheduleConfig: monitorInterval: ... monitorWindow: ... modelMonitoringAlertConfig: emailAlertConfig: userEmails: ... enableLogging: ... notificationChannels: ... predictInstanceSchemaUri: ... samplePredictInstance: ... statsAnomaliesBaseDirectory: outputUriPrefix: ... result: patchResult
JSON
[ { "patch": { "call": "googleapis.aiplatform.v1beta1.projects.locations.modelDeploymentMonitoringJobs.patch", "args": { "name": "...", "updateMask": "...", "region": "...", "body": { "analysisInstanceSchemaUri": "...", "displayName": "...", "enableMonitoringPipelineLogs": "...", "encryptionSpec": { "kmsKeyName": "..." }, "endpoint": "...", "labels": "...", "logTtl": "...", "loggingSamplingStrategy": { "randomSampleConfig": { "sampleRate": "..." } }, "modelDeploymentMonitoringObjectiveConfigs": "...", "modelDeploymentMonitoringScheduleConfig": { "monitorInterval": "...", "monitorWindow": "..." }, "modelMonitoringAlertConfig": { "emailAlertConfig": { "userEmails": "..." }, "enableLogging": "...", "notificationChannels": "..." }, "predictInstanceSchemaUri": "...", "samplePredictInstance": "...", "statsAnomaliesBaseDirectory": { "outputUriPrefix": "..." } } }, "result": "patchResult" } } ]