Class: Google::Apis::AiplatformV1beta1::GoogleCloudAiplatformV1beta1ModelDeploymentMonitoringJob

Inherits:
Object
  • Object
show all
Includes:
Core::Hashable, Core::JsonObjectSupport
Defined in:
lib/google/apis/aiplatform_v1beta1/classes.rb,
lib/google/apis/aiplatform_v1beta1/representations.rb,
lib/google/apis/aiplatform_v1beta1/representations.rb

Overview

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.

Instance Attribute Summary collapse

Instance Method Summary collapse

Constructor Details

#initialize(**args) ⇒ GoogleCloudAiplatformV1beta1ModelDeploymentMonitoringJob

Returns a new instance of GoogleCloudAiplatformV1beta1ModelDeploymentMonitoringJob.



34788
34789
34790
 
# File 'lib/google/apis/aiplatform_v1beta1/classes.rb', line 34788

def initialize(**args)
   update!(**args)
end

Instance Attribute Details

#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. Corresponds to the JSON property analysisInstanceSchemaUri

Returns:

  • (String) 


34631
34632
34633
 
# File 'lib/google/apis/aiplatform_v1beta1/classes.rb', line 34631

def analysis_instance_schema_uri
  @analysis_instance_schema_uri
end

#bigquery_tables ⇒ Array<Google::Apis::AiplatformV1beta1::GoogleCloudAiplatformV1beta1ModelDeploymentMonitoringBigQueryTable>

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 Corresponds to the JSON property bigqueryTables

Returns:



34639
34640
34641
 
# File 'lib/google/apis/aiplatform_v1beta1/classes.rb', line 34639

def bigquery_tables
  @bigquery_tables
end

#create_time ⇒ String

Output only. Timestamp when this ModelDeploymentMonitoringJob was created. Corresponds to the JSON property createTime

Returns:

  • (String) 


34644
34645
34646
 
# File 'lib/google/apis/aiplatform_v1beta1/classes.rb', line 34644

def create_time
  @create_time
end

#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. Corresponds to the JSON property displayName

Returns:

  • (String) 


34651
34652
34653
 
# File 'lib/google/apis/aiplatform_v1beta1/classes.rb', line 34651

def display_name
  @display_name
end

#enable_monitoring_pipeline_logs ⇒ Boolean Also known as: enable_monitoring_pipeline_logs?

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. Corresponds to the JSON property enableMonitoringPipelineLogs

Returns:

  • (Boolean) 


34659
34660
34661
 
# File 'lib/google/apis/aiplatform_v1beta1/classes.rb', line 34659

def enable_monitoring_pipeline_logs
  @enable_monitoring_pipeline_logs
end

#encryption_spec ⇒ Google::Apis::AiplatformV1beta1::GoogleCloudAiplatformV1beta1EncryptionSpec

Represents a customer-managed encryption key specification that can be applied to a Vertex AI resource. Corresponds to the JSON property encryptionSpec

Returns:



34666
34667
34668
 
# File 'lib/google/apis/aiplatform_v1beta1/classes.rb', line 34666

def encryption_spec
  @encryption_spec
end

#endpoint ⇒ String

Required. Endpoint resource name. Format: projects/project/locations/ location/endpoints/endpoint` Corresponds to the JSON propertyendpoint`

Returns:

  • (String) 


34672
34673
34674
 
# File 'lib/google/apis/aiplatform_v1beta1/classes.rb', line 34672

def endpoint
  @endpoint
end

#error ⇒ Google::Apis::AiplatformV1beta1::GoogleRpcStatus

The Status type defines a logical error model that is suitable for different programming environments, including REST APIs and RPC APIs. It is used by gRPC. Each Status message contains three pieces of data: error code, error message, and error details. You can find out more about this error model and how to work with it in the API Design Guide. Corresponds to the JSON property error

Returns:



34682
34683
34684
 
# File 'lib/google/apis/aiplatform_v1beta1/classes.rb', line 34682

def error
  @error
end

#labels ⇒ Hash<String,String>

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. Corresponds to the JSON property labels

Returns:

  • (Hash<String,String>) 


34691
34692
34693
 
# File 'lib/google/apis/aiplatform_v1beta1/classes.rb', line 34691

def labels
  @labels
end

#latest_monitoring_pipeline_metadata ⇒ Google::Apis::AiplatformV1beta1::GoogleCloudAiplatformV1beta1ModelDeploymentMonitoringJobLatestMonitoringPipelineMetadata

All metadata of most recent monitoring pipelines. Corresponds to the JSON property latestMonitoringPipelineMetadata

Returns:



34696
34697
34698
 
# File 'lib/google/apis/aiplatform_v1beta1/classes.rb', line 34696

def latest_monitoring_pipeline_metadata
  @latest_monitoring_pipeline_metadata
end

#log_ttl ⇒ String

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. Corresponds to the JSON property logTtl

Returns:

  • (String) 


34703
34704
34705
 
# File 'lib/google/apis/aiplatform_v1beta1/classes.rb', line 34703

def log_ttl
  @log_ttl
end

#logging_sampling_strategy ⇒ Google::Apis::AiplatformV1beta1::GoogleCloudAiplatformV1beta1SamplingStrategy

Sampling Strategy for logging, can be for both training and prediction dataset. Corresponds to the JSON property loggingSamplingStrategy

Returns:



34708
34709
34710
 
# File 'lib/google/apis/aiplatform_v1beta1/classes.rb', line 34708

def logging_sampling_strategy
  @logging_sampling_strategy
end

#model_deployment_monitoring_objective_configs ⇒ Array<Google::Apis::AiplatformV1beta1::GoogleCloudAiplatformV1beta1ModelDeploymentMonitoringObjectiveConfig>

Required. The config for monitoring objectives. This is a per DeployedModel config. Each DeployedModel needs to be configured separately. Corresponds to the JSON property modelDeploymentMonitoringObjectiveConfigs

Returns:



34714
34715
34716
 
# File 'lib/google/apis/aiplatform_v1beta1/classes.rb', line 34714

def model_deployment_monitoring_objective_configs
  @model_deployment_monitoring_objective_configs
end

#model_deployment_monitoring_schedule_config ⇒ Google::Apis::AiplatformV1beta1::GoogleCloudAiplatformV1beta1ModelDeploymentMonitoringScheduleConfig

The config for scheduling monitoring job. Corresponds to the JSON property modelDeploymentMonitoringScheduleConfig

Returns:



34719
34720
34721
 
# File 'lib/google/apis/aiplatform_v1beta1/classes.rb', line 34719

def model_deployment_monitoring_schedule_config
  @model_deployment_monitoring_schedule_config
end

#model_monitoring_alert_config ⇒ Google::Apis::AiplatformV1beta1::GoogleCloudAiplatformV1beta1ModelMonitoringAlertConfig

The alert config for model monitoring. Corresponds to the JSON property modelMonitoringAlertConfig

Returns:



34724
34725
34726
 
# File 'lib/google/apis/aiplatform_v1beta1/classes.rb', line 34724

def model_monitoring_alert_config
  @model_monitoring_alert_config
end

#name ⇒ String

Output only. Resource name of a ModelDeploymentMonitoringJob. Corresponds to the JSON property name

Returns:

  • (String) 


34729
34730
34731
 
# File 'lib/google/apis/aiplatform_v1beta1/classes.rb', line 34729

def name
  @name
end

#next_schedule_time ⇒ String

Output only. Timestamp when this monitoring pipeline will be scheduled to run for the next round. Corresponds to the JSON property nextScheduleTime

Returns:

  • (String) 


34735
34736
34737
 
# File 'lib/google/apis/aiplatform_v1beta1/classes.rb', line 34735

def next_schedule_time
  @next_schedule_time
end

#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. Corresponds to the JSON property predictInstanceSchemaUri

Returns:

  • (String) 


34742
34743
34744
 
# File 'lib/google/apis/aiplatform_v1beta1/classes.rb', line 34742

def predict_instance_schema_uri
  @predict_instance_schema_uri
end

#sample_predict_instance ⇒ Object

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. Corresponds to the JSON property samplePredictInstance

Returns:

  • (Object) 


34750
34751
34752
 
# File 'lib/google/apis/aiplatform_v1beta1/classes.rb', line 34750

def sample_predict_instance
  @sample_predict_instance
end

#satisfies_pzi ⇒ Boolean Also known as: satisfies_pzi?

Output only. Reserved for future use. Corresponds to the JSON property satisfiesPzi

Returns:

  • (Boolean) 


34755
34756
34757
 
# File 'lib/google/apis/aiplatform_v1beta1/classes.rb', line 34755

def satisfies_pzi
  @satisfies_pzi
end

#satisfies_pzs ⇒ Boolean Also known as: satisfies_pzs?

Output only. Reserved for future use. Corresponds to the JSON property satisfiesPzs

Returns:

  • (Boolean) 


34761
34762
34763
 
# File 'lib/google/apis/aiplatform_v1beta1/classes.rb', line 34761

def satisfies_pzs
  @satisfies_pzs
end

#schedule_state ⇒ String

Output only. Schedule state when the monitoring job is in Running state. Corresponds to the JSON property scheduleState

Returns:

  • (String) 


34767
34768
34769
 
# File 'lib/google/apis/aiplatform_v1beta1/classes.rb', line 34767

def schedule_state
  @schedule_state
end

#state ⇒ String

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'. Corresponds to the JSON property state

Returns:

  • (String) 


34775
34776
34777
 
# File 'lib/google/apis/aiplatform_v1beta1/classes.rb', line 34775

def state
  @state
end

#stats_anomalies_base_directory ⇒ Google::Apis::AiplatformV1beta1::GoogleCloudAiplatformV1beta1GcsDestination

The Google Cloud Storage location where the output is to be written to. Corresponds to the JSON property statsAnomaliesBaseDirectory

Returns:



34780
34781
34782
 
# File 'lib/google/apis/aiplatform_v1beta1/classes.rb', line 34780

def stats_anomalies_base_directory
  @stats_anomalies_base_directory
end

#update_time ⇒ String

Output only. Timestamp when this ModelDeploymentMonitoringJob was updated most recently. Corresponds to the JSON property updateTime

Returns:

  • (String) 


34786
34787
34788
 
# File 'lib/google/apis/aiplatform_v1beta1/classes.rb', line 34786

def update_time
  @update_time
end

Instance Method Details

#update!(**args) ⇒ Object

Update properties of this object



34793
34794
34795
34796
34797
34798
34799
34800
34801
34802
34803
34804
34805
34806
34807
34808
34809
34810
34811
34812
34813
34814
34815
34816
34817
34818
34819
 
# File 'lib/google/apis/aiplatform_v1beta1/classes.rb', line 34793

def update!(**args)
  @analysis_instance_schema_uri = args[:analysis_instance_schema_uri] if args.key?(:analysis_instance_schema_uri)
  @bigquery_tables = args[:bigquery_tables] if args.key?(:bigquery_tables)
  @create_time = args[:create_time] if args.key?(:create_time)
  @display_name = args[:display_name] if args.key?(:display_name)
  @enable_monitoring_pipeline_logs = args[:enable_monitoring_pipeline_logs] if args.key?(:enable_monitoring_pipeline_logs)
  @encryption_spec = args[:encryption_spec] if args.key?(:encryption_spec)
  @endpoint = args[:endpoint] if args.key?(:endpoint)
  @error = args[:error] if args.key?(:error)
  @labels = args[:labels] if args.key?(:labels)
  @latest_monitoring_pipeline_metadata = args[:latest_monitoring_pipeline_metadata] if args.key?(:latest_monitoring_pipeline_metadata)
  @log_ttl = args[:log_ttl] if args.key?(:log_ttl)
  @logging_sampling_strategy = args[:logging_sampling_strategy] if args.key?(:logging_sampling_strategy)
  @model_deployment_monitoring_objective_configs = args[:model_deployment_monitoring_objective_configs] if args.key?(:model_deployment_monitoring_objective_configs)
  @model_deployment_monitoring_schedule_config = args[:model_deployment_monitoring_schedule_config] if args.key?(:model_deployment_monitoring_schedule_config)
  @model_monitoring_alert_config = args[:model_monitoring_alert_config] if args.key?(:model_monitoring_alert_config)
  @name = args[:name] if args.key?(:name)
  @next_schedule_time = args[:next_schedule_time] if args.key?(:next_schedule_time)
  @predict_instance_schema_uri = args[:predict_instance_schema_uri] if args.key?(:predict_instance_schema_uri)
  @sample_predict_instance = args[:sample_predict_instance] if args.key?(:sample_predict_instance)
  @satisfies_pzi = args[:satisfies_pzi] if args.key?(:satisfies_pzi)
  @satisfies_pzs = args[:satisfies_pzs] if args.key?(:satisfies_pzs)
  @schedule_state = args[:schedule_state] if args.key?(:schedule_state)
  @state = args[:state] if args.key?(:state)
  @stats_anomalies_base_directory = args[:stats_anomalies_base_directory] if args.key?(:stats_anomalies_base_directory)
  @update_time = args[:update_time] if args.key?(:update_time)
end