Reference documentation and code samples for the Google Cloud Ai Platform V1 Client class ModelDeploymentMonitoringJob.
Represents a job that runs periodically to monitor the deployed models in an endpoint. It will analyze the logged training & prediction data to detect any abnormal behaviors.
Generated from protobuf message google.cloud.aiplatform.v1.ModelDeploymentMonitoringJob
Methods
__construct
Constructor.
| Parameters | |
|---|---|
| Name | Description |
data |
array
Optional. Data for populating the Message object. |
↳ name |
string
Output only. Resource name of a ModelDeploymentMonitoringJob. |
↳ display_name |
string
Required. The user-defined name of the ModelDeploymentMonitoringJob. The name can be up to 128 characters long and can consist of any UTF-8 characters. Display name of a ModelDeploymentMonitoringJob. |
↳ endpoint |
string
Required. Endpoint resource name. Format: |
↳ state |
int
Output only. The detailed state of the monitoring job. When the job is still creating, the state will be 'PENDING'. Once the job is successfully created, the state will be 'RUNNING'. Pause the job, the state will be 'PAUSED'. Resume the job, the state will return to 'RUNNING'. |
↳ schedule_state |
int
Output only. Schedule state when the monitoring job is in Running state. |
↳ latest_monitoring_pipeline_metadata |
Google\Cloud\AIPlatform\V1\ModelDeploymentMonitoringJob\LatestMonitoringPipelineMetadata
Output only. Latest triggered monitoring pipeline metadata. |
↳ model_deployment_monitoring_objective_configs |
array<Google\Cloud\AIPlatform\V1\ModelDeploymentMonitoringObjectiveConfig>
Required. The config for monitoring objectives. This is a per DeployedModel config. Each DeployedModel needs to be configured separately. |
↳ model_deployment_monitoring_schedule_config |
Google\Cloud\AIPlatform\V1\ModelDeploymentMonitoringScheduleConfig
Required. Schedule config for running the monitoring job. |
↳ logging_sampling_strategy |
Google\Cloud\AIPlatform\V1\SamplingStrategy
Required. Sample Strategy for logging. |
↳ model_monitoring_alert_config |
Google\Cloud\AIPlatform\V1\ModelMonitoringAlertConfig
Alert config for model monitoring. |
↳ predict_instance_schema_uri |
string
YAML schema file uri describing the format of a single instance, which are given to format this Endpoint's prediction (and explanation). If not set, we will generate predict schema from collected predict requests. |
↳ sample_predict_instance |
Google\Protobuf\Value
Sample Predict instance, same format as PredictRequest.instances, this can be set as a replacement of ModelDeploymentMonitoringJob.predict_instance_schema_uri. If not set, we will generate predict schema from collected predict requests. |
↳ analysis_instance_schema_uri |
string
YAML schema file uri describing the format of a single instance that you want Tensorflow Data Validation (TFDV) to analyze. If this field is empty, all the feature data types are inferred from predict_instance_schema_uri, meaning that TFDV will use the data in the exact format(data type) as prediction request/response. If there are any data type differences between predict instance and TFDV instance, this field can be used to override the schema. For models trained with Vertex AI, this field must be set as all the fields in predict instance formatted as string. |
↳ bigquery_tables |
array<Google\Cloud\AIPlatform\V1\ModelDeploymentMonitoringBigQueryTable>
Output only. The created bigquery tables for the job under customer project. Customer could do their own query & analysis. There could be 4 log tables in maximum: 1. Training data logging predict request/response 2. Serving data logging predict request/response |
↳ log_ttl |
Google\Protobuf\Duration
The TTL of BigQuery tables in user projects which stores logs. A day is the basic unit of the TTL and we take the ceil of TTL/86400(a day). e.g. { second: 3600} indicates ttl = 1 day. |
↳ labels |
array|Google\Protobuf\Internal\MapField
The labels with user-defined metadata to organize your ModelDeploymentMonitoringJob. Label keys and values can be no longer than 64 characters (Unicode codepoints), can only contain lowercase letters, numeric characters, underscores and dashes. International characters are allowed. See https://goo.gl/xmQnxf for more information and examples of labels. |
↳ create_time |
Google\Protobuf\Timestamp
Output only. Timestamp when this ModelDeploymentMonitoringJob was created. |
↳ update_time |
Google\Protobuf\Timestamp
Output only. Timestamp when this ModelDeploymentMonitoringJob was updated most recently. |
↳ next_schedule_time |
Google\Protobuf\Timestamp
Output only. Timestamp when this monitoring pipeline will be scheduled to run for the next round. |
↳ stats_anomalies_base_directory |
Google\Cloud\AIPlatform\V1\GcsDestination
Stats anomalies base folder path. |
↳ encryption_spec |
Google\Cloud\AIPlatform\V1\EncryptionSpec
Customer-managed encryption key spec for a ModelDeploymentMonitoringJob. If set, this ModelDeploymentMonitoringJob and all sub-resources of this ModelDeploymentMonitoringJob will be secured by this key. |
↳ enable_monitoring_pipeline_logs |
bool
If true, the scheduled monitoring pipeline logs are sent to Google Cloud Logging, including pipeline status and anomalies detected. Please note the logs incur cost, which are subject to Cloud Logging pricing. |
↳ error |
Google\Rpc\Status
Output only. Only populated when the job's state is |
getName
Output only. Resource name of a ModelDeploymentMonitoringJob.
| Returns | |
|---|---|
| Type | Description |
string | |
setName
Output only. Resource name of a ModelDeploymentMonitoringJob.
| Parameter | |
|---|---|
| Name | Description |
var |
string
|
| Returns | |
|---|---|
| Type | Description |
$this | |
getDisplayName
Required. The user-defined name of the ModelDeploymentMonitoringJob.
The name can be up to 128 characters long and can consist of any UTF-8 characters. Display name of a ModelDeploymentMonitoringJob.
| Returns | |
|---|---|
| Type | Description |
string | |
setDisplayName
Required. The user-defined name of the ModelDeploymentMonitoringJob.
The name can be up to 128 characters long and can consist of any UTF-8 characters. Display name of a ModelDeploymentMonitoringJob.
| Parameter | |
|---|---|
| Name | Description |
var |
string
|
| Returns | |
|---|---|
| Type | Description |
$this | |
getEndpoint
Required. Endpoint resource name.
Format: projects/{project}/locations/{location}/endpoints/{endpoint}
| Returns | |
|---|---|
| Type | Description |
string | |
setEndpoint
Required. Endpoint resource name.
Format: projects/{project}/locations/{location}/endpoints/{endpoint}
| Parameter | |
|---|---|
| Name | Description |
var |
string
|
| Returns | |
|---|---|
| Type | Description |
$this | |
getState
Output only. The detailed state of the monitoring job.
When the job is still creating, the state will be 'PENDING'. Once the job is successfully created, the state will be 'RUNNING'. Pause the job, the state will be 'PAUSED'. Resume the job, the state will return to 'RUNNING'.
| Returns | |
|---|---|
| Type | Description |
int | |
setState
Output only. The detailed state of the monitoring job.
When the job is still creating, the state will be 'PENDING'. Once the job is successfully created, the state will be 'RUNNING'. Pause the job, the state will be 'PAUSED'. Resume the job, the state will return to 'RUNNING'.
| Parameter | |
|---|---|
| Name | Description |
var |
int
|
| Returns | |
|---|---|
| Type | Description |
$this | |
getScheduleState
Output only. Schedule state when the monitoring job is in Running state.
| Returns | |
|---|---|
| Type | Description |
int | |
setScheduleState
Output only. Schedule state when the monitoring job is in Running state.
| Parameter | |
|---|---|
| Name | Description |
var |
int
|
| Returns | |
|---|---|
| Type | Description |
$this | |
getLatestMonitoringPipelineMetadata
Output only. Latest triggered monitoring pipeline metadata.
| Returns | |
|---|---|
| Type | Description |
Google\Cloud\AIPlatform\V1\ModelDeploymentMonitoringJob\LatestMonitoringPipelineMetadata|null | |
hasLatestMonitoringPipelineMetadata
clearLatestMonitoringPipelineMetadata
setLatestMonitoringPipelineMetadata
Output only. Latest triggered monitoring pipeline metadata.
| Parameter | |
|---|---|
| Name | Description |
var |
Google\Cloud\AIPlatform\V1\ModelDeploymentMonitoringJob\LatestMonitoringPipelineMetadata
|
| Returns | |
|---|---|
| Type | Description |
$this | |
getModelDeploymentMonitoringObjectiveConfigs
Required. The config for monitoring objectives. This is a per DeployedModel config. Each DeployedModel needs to be configured separately.
| Returns | |
|---|---|
| Type | Description |
Google\Protobuf\Internal\RepeatedField | |
setModelDeploymentMonitoringObjectiveConfigs
Required. The config for monitoring objectives. This is a per DeployedModel config. Each DeployedModel needs to be configured separately.
| Parameter | |
|---|---|
| Name | Description |
var |
array<Google\Cloud\AIPlatform\V1\ModelDeploymentMonitoringObjectiveConfig>
|
| Returns | |
|---|---|
| Type | Description |
$this | |
getModelDeploymentMonitoringScheduleConfig
Required. Schedule config for running the monitoring job.
| Returns | |
|---|---|
| Type | Description |
Google\Cloud\AIPlatform\V1\ModelDeploymentMonitoringScheduleConfig|null | |
hasModelDeploymentMonitoringScheduleConfig
clearModelDeploymentMonitoringScheduleConfig
setModelDeploymentMonitoringScheduleConfig
Required. Schedule config for running the monitoring job.
| Parameter | |
|---|---|
| Name | Description |
var |
Google\Cloud\AIPlatform\V1\ModelDeploymentMonitoringScheduleConfig
|
| Returns | |
|---|---|
| Type | Description |
$this | |
getLoggingSamplingStrategy
Required. Sample Strategy for logging.
| Returns | |
|---|---|
| Type | Description |
Google\Cloud\AIPlatform\V1\SamplingStrategy|null | |
hasLoggingSamplingStrategy
clearLoggingSamplingStrategy
setLoggingSamplingStrategy
Required. Sample Strategy for logging.
| Parameter | |
|---|---|
| Name | Description |
var |
Google\Cloud\AIPlatform\V1\SamplingStrategy
|
| Returns | |
|---|---|
| Type | Description |
$this | |
getModelMonitoringAlertConfig
Alert config for model monitoring.
| Returns | |
|---|---|
| Type | Description |
Google\Cloud\AIPlatform\V1\ModelMonitoringAlertConfig|null | |
hasModelMonitoringAlertConfig
clearModelMonitoringAlertConfig
setModelMonitoringAlertConfig
Alert config for model monitoring.
| Parameter | |
|---|---|
| Name | Description |
var |
Google\Cloud\AIPlatform\V1\ModelMonitoringAlertConfig
|
| Returns | |
|---|---|
| Type | Description |
$this | |
getPredictInstanceSchemaUri
YAML schema file uri describing the format of a single instance, which are given to format this Endpoint's prediction (and explanation).
If not set, we will generate predict schema from collected predict requests.
| Returns | |
|---|---|
| Type | Description |
string | |
setPredictInstanceSchemaUri
YAML schema file uri describing the format of a single instance, which are given to format this Endpoint's prediction (and explanation).
If not set, we will generate predict schema from collected predict requests.
| Parameter | |
|---|---|
| Name | Description |
var |
string
|
| Returns | |
|---|---|
| Type | Description |
$this | |
getSamplePredictInstance
Sample Predict instance, same format as PredictRequest.instances, this can be set as a replacement of ModelDeploymentMonitoringJob.predict_instance_schema_uri.
If not set, we will generate predict schema from collected predict requests.
| Returns | |
|---|---|
| Type | Description |
Google\Protobuf\Value|null | |
hasSamplePredictInstance
clearSamplePredictInstance
setSamplePredictInstance
Sample Predict instance, same format as PredictRequest.instances, this can be set as a replacement of ModelDeploymentMonitoringJob.predict_instance_schema_uri.
If not set, we will generate predict schema from collected predict requests.
| Parameter | |
|---|---|
| Name | Description |
var |
Google\Protobuf\Value
|
| Returns | |
|---|---|
| Type | Description |
$this | |
getAnalysisInstanceSchemaUri
YAML schema file uri describing the format of a single instance that you want Tensorflow Data Validation (TFDV) to analyze.
If this field is empty, all the feature data types are inferred from predict_instance_schema_uri, meaning that TFDV will use the data in the exact format(data type) as prediction request/response. If there are any data type differences between predict instance and TFDV instance, this field can be used to override the schema. For models trained with Vertex AI, this field must be set as all the fields in predict instance formatted as string.
| Returns | |
|---|---|
| Type | Description |
string | |
setAnalysisInstanceSchemaUri
YAML schema file uri describing the format of a single instance that you want Tensorflow Data Validation (TFDV) to analyze.
If this field is empty, all the feature data types are inferred from predict_instance_schema_uri, meaning that TFDV will use the data in the exact format(data type) as prediction request/response. If there are any data type differences between predict instance and TFDV instance, this field can be used to override the schema. For models trained with Vertex AI, this field must be set as all the fields in predict instance formatted as string.
| Parameter | |
|---|---|
| Name | Description |
var |
string
|
| Returns | |
|---|---|
| Type | Description |
$this | |
getBigqueryTables
Output only. The created bigquery tables for the job under customer project. Customer could do their own query & analysis. There could be 4 log tables in maximum:
- Training data logging predict request/response
- Serving data logging predict request/response
| Returns | |
|---|---|
| Type | Description |
Google\Protobuf\Internal\RepeatedField | |
setBigqueryTables
Output only. The created bigquery tables for the job under customer project. Customer could do their own query & analysis. There could be 4 log tables in maximum:
- Training data logging predict request/response
- Serving data logging predict request/response
| Parameter | |
|---|---|
| Name | Description |
var |
array<Google\Cloud\AIPlatform\V1\ModelDeploymentMonitoringBigQueryTable>
|
| Returns | |
|---|---|
| Type | Description |
$this | |
getLogTtl
The TTL of BigQuery tables in user projects which stores logs.
A day is the basic unit of the TTL and we take the ceil of TTL/86400(a day). e.g. { second: 3600} indicates ttl = 1 day.
| Returns | |
|---|---|
| Type | Description |
Google\Protobuf\Duration|null | |
hasLogTtl
clearLogTtl
setLogTtl
The TTL of BigQuery tables in user projects which stores logs.
A day is the basic unit of the TTL and we take the ceil of TTL/86400(a day). e.g. { second: 3600} indicates ttl = 1 day.
| Parameter | |
|---|---|
| Name | Description |
var |
Google\Protobuf\Duration
|
| Returns | |
|---|---|
| Type | Description |
$this | |
getLabels
The labels with user-defined metadata to organize your ModelDeploymentMonitoringJob.
Label keys and values can be no longer than 64 characters (Unicode codepoints), can only contain lowercase letters, numeric characters, underscores and dashes. International characters are allowed. See https://goo.gl/xmQnxf for more information and examples of labels.
| Returns | |
|---|---|
| Type | Description |
Google\Protobuf\Internal\MapField | |
setLabels
The labels with user-defined metadata to organize your ModelDeploymentMonitoringJob.
Label keys and values can be no longer than 64 characters (Unicode codepoints), can only contain lowercase letters, numeric characters, underscores and dashes. International characters are allowed. See https://goo.gl/xmQnxf for more information and examples of labels.
| Parameter | |
|---|---|
| Name | Description |
var |
array|Google\Protobuf\Internal\MapField
|
| Returns | |
|---|---|
| Type | Description |
$this | |
getCreateTime
Output only. Timestamp when this ModelDeploymentMonitoringJob was created.
| Returns | |
|---|---|
| Type | Description |
Google\Protobuf\Timestamp|null | |
hasCreateTime
clearCreateTime
setCreateTime
Output only. Timestamp when this ModelDeploymentMonitoringJob was created.
| Parameter | |
|---|---|
| Name | Description |
var |
Google\Protobuf\Timestamp
|
| Returns | |
|---|---|
| Type | Description |
$this | |
getUpdateTime
Output only. Timestamp when this ModelDeploymentMonitoringJob was updated most recently.
| Returns | |
|---|---|
| Type | Description |
Google\Protobuf\Timestamp|null | |
hasUpdateTime
clearUpdateTime
setUpdateTime
Output only. Timestamp when this ModelDeploymentMonitoringJob was updated most recently.
| Parameter | |
|---|---|
| Name | Description |
var |
Google\Protobuf\Timestamp
|
| Returns | |
|---|---|
| Type | Description |
$this | |
getNextScheduleTime
Output only. Timestamp when this monitoring pipeline will be scheduled to run for the next round.
| Returns | |
|---|---|
| Type | Description |
Google\Protobuf\Timestamp|null | |
hasNextScheduleTime
clearNextScheduleTime
setNextScheduleTime
Output only. Timestamp when this monitoring pipeline will be scheduled to run for the next round.
| Parameter | |
|---|---|
| Name | Description |
var |
Google\Protobuf\Timestamp
|
| Returns | |
|---|---|
| Type | Description |
$this | |
getStatsAnomaliesBaseDirectory
Stats anomalies base folder path.
| Returns | |
|---|---|
| Type | Description |
Google\Cloud\AIPlatform\V1\GcsDestination|null | |
hasStatsAnomaliesBaseDirectory
clearStatsAnomaliesBaseDirectory
setStatsAnomaliesBaseDirectory
Stats anomalies base folder path.
| Parameter | |
|---|---|
| Name | Description |
var |
Google\Cloud\AIPlatform\V1\GcsDestination
|
| Returns | |
|---|---|
| Type | Description |
$this | |
getEncryptionSpec
Customer-managed encryption key spec for a ModelDeploymentMonitoringJob. If set, this ModelDeploymentMonitoringJob and all sub-resources of this ModelDeploymentMonitoringJob will be secured by this key.
| Returns | |
|---|---|
| Type | Description |
Google\Cloud\AIPlatform\V1\EncryptionSpec|null | |
hasEncryptionSpec
clearEncryptionSpec
setEncryptionSpec
Customer-managed encryption key spec for a ModelDeploymentMonitoringJob. If set, this ModelDeploymentMonitoringJob and all sub-resources of this ModelDeploymentMonitoringJob will be secured by this key.
| Parameter | |
|---|---|
| Name | Description |
var |
Google\Cloud\AIPlatform\V1\EncryptionSpec
|
| Returns | |
|---|---|
| Type | Description |
$this | |
getEnableMonitoringPipelineLogs
If true, the scheduled monitoring pipeline logs are sent to Google Cloud Logging, including pipeline status and anomalies detected.
Please note the logs incur cost, which are subject to Cloud Logging pricing.
| Returns | |
|---|---|
| Type | Description |
bool | |
setEnableMonitoringPipelineLogs
If true, the scheduled monitoring pipeline logs are sent to Google Cloud Logging, including pipeline status and anomalies detected.
Please note the logs incur cost, which are subject to Cloud Logging pricing.
| Parameter | |
|---|---|
| Name | Description |
var |
bool
|
| Returns | |
|---|---|
| Type | Description |
$this | |
getError
Output only. Only populated when the job's state is JOB_STATE_FAILED or
JOB_STATE_CANCELLED.
| Returns | |
|---|---|
| Type | Description |
Google\Rpc\Status|null | |
hasError
clearError
setError
Output only. Only populated when the job's state is JOB_STATE_FAILED or
JOB_STATE_CANCELLED.
| Parameter | |
|---|---|
| Name | Description |
var |
Google\Rpc\Status
|
| Returns | |
|---|---|
| Type | Description |
$this | |