Class ModelDeploymentMonitoringJob.Builder

java.lang.Object
com.google.protobuf.AbstractMessageLite.Builder
com.google.protobuf.AbstractMessage.Builder<BuilderT>
com.google.protobuf.GeneratedMessage.Builder<ModelDeploymentMonitoringJob.Builder>
com.google.cloud.aiplatform.v1.ModelDeploymentMonitoringJob.Builder
All Implemented Interfaces:
ModelDeploymentMonitoringJobOrBuilder, com.google.protobuf.Message.Builder, com.google.protobuf.MessageLite.Builder, com.google.protobuf.MessageLiteOrBuilder, com.google.protobuf.MessageOrBuilder, Cloneable
Enclosing class:
ModelDeploymentMonitoringJob

public static final class ModelDeploymentMonitoringJob.Builder extends com.google.protobuf.GeneratedMessage.Builder<ModelDeploymentMonitoringJob.Builder> implements ModelDeploymentMonitoringJobOrBuilder
 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.
 
Protobuf type google.cloud.aiplatform.v1.ModelDeploymentMonitoringJob
  • Method Details

    • getDescriptor

      public static final com.google.protobuf.Descriptors.Descriptor getDescriptor()
    • internalGetMapFieldReflection

      protected com.google.protobuf.MapFieldReflectionAccessor internalGetMapFieldReflection(int number)
      Overrides:
      internalGetMapFieldReflection in class com.google.protobuf.GeneratedMessage.Builder<ModelDeploymentMonitoringJob.Builder>
    • internalGetMutableMapFieldReflection

      protected com.google.protobuf.MapFieldReflectionAccessor internalGetMutableMapFieldReflection(int number)
      Overrides:
      internalGetMutableMapFieldReflection in class com.google.protobuf.GeneratedMessage.Builder<ModelDeploymentMonitoringJob.Builder>
    • internalGetFieldAccessorTable

      protected com.google.protobuf.GeneratedMessage.FieldAccessorTable internalGetFieldAccessorTable()
      Specified by:
      internalGetFieldAccessorTable in class com.google.protobuf.GeneratedMessage.Builder<ModelDeploymentMonitoringJob.Builder>
    • clear

      Specified by:
      clear in interface com.google.protobuf.Message.Builder
      Specified by:
      clear in interface com.google.protobuf.MessageLite.Builder
      Overrides:
      clear in class com.google.protobuf.GeneratedMessage.Builder<ModelDeploymentMonitoringJob.Builder>
    • getDescriptorForType

      public com.google.protobuf.Descriptors.Descriptor getDescriptorForType()
      Specified by:
      getDescriptorForType in interface com.google.protobuf.Message.Builder
      Specified by:
      getDescriptorForType in interface com.google.protobuf.MessageOrBuilder
      Overrides:
      getDescriptorForType in class com.google.protobuf.GeneratedMessage.Builder<ModelDeploymentMonitoringJob.Builder>
    • getDefaultInstanceForType

      public ModelDeploymentMonitoringJob getDefaultInstanceForType()
      Specified by:
      getDefaultInstanceForType in interface com.google.protobuf.MessageLiteOrBuilder
      Specified by:
      getDefaultInstanceForType in interface com.google.protobuf.MessageOrBuilder
    • build

      Specified by:
      build in interface com.google.protobuf.Message.Builder
      Specified by:
      build in interface com.google.protobuf.MessageLite.Builder
    • buildPartial

      public ModelDeploymentMonitoringJob buildPartial()
      Specified by:
      buildPartial in interface com.google.protobuf.Message.Builder
      Specified by:
      buildPartial in interface com.google.protobuf.MessageLite.Builder
    • mergeFrom

      public ModelDeploymentMonitoringJob.Builder mergeFrom(com.google.protobuf.Message other)
      Specified by:
      mergeFrom in interface com.google.protobuf.Message.Builder
      Overrides:
      mergeFrom in class com.google.protobuf.AbstractMessage.Builder<ModelDeploymentMonitoringJob.Builder>
    • mergeFrom

    • isInitialized

      public final boolean isInitialized()
      Specified by:
      isInitialized in interface com.google.protobuf.MessageLiteOrBuilder
      Overrides:
      isInitialized in class com.google.protobuf.GeneratedMessage.Builder<ModelDeploymentMonitoringJob.Builder>
    • mergeFrom

      public ModelDeploymentMonitoringJob.Builder mergeFrom(com.google.protobuf.CodedInputStream input, com.google.protobuf.ExtensionRegistryLite extensionRegistry) throws IOException
      Specified by:
      mergeFrom in interface com.google.protobuf.Message.Builder
      Specified by:
      mergeFrom in interface com.google.protobuf.MessageLite.Builder
      Overrides:
      mergeFrom in class com.google.protobuf.AbstractMessage.Builder<ModelDeploymentMonitoringJob.Builder>
      Throws:
      IOException
    • getName

      public String getName()
       Output only. Resource name of a ModelDeploymentMonitoringJob.
       
      string name = 1 [(.google.api.field_behavior) = OUTPUT_ONLY];
      Specified by:
      getName in interface ModelDeploymentMonitoringJobOrBuilder
      Returns:
      The name.
    • getNameBytes

      public com.google.protobuf.ByteString getNameBytes()
       Output only. Resource name of a ModelDeploymentMonitoringJob.
       
      string name = 1 [(.google.api.field_behavior) = OUTPUT_ONLY];
      Specified by:
      getNameBytes in interface ModelDeploymentMonitoringJobOrBuilder
      Returns:
      The bytes for name.
    • setName

       Output only. Resource name of a ModelDeploymentMonitoringJob.
       
      string name = 1 [(.google.api.field_behavior) = OUTPUT_ONLY];
      Parameters:
      value - The name to set.
      Returns:
      This builder for chaining.
    • clearName

       Output only. Resource name of a ModelDeploymentMonitoringJob.
       
      string name = 1 [(.google.api.field_behavior) = OUTPUT_ONLY];
      Returns:
      This builder for chaining.
    • setNameBytes

      public ModelDeploymentMonitoringJob.Builder setNameBytes(com.google.protobuf.ByteString value)
       Output only. Resource name of a ModelDeploymentMonitoringJob.
       
      string name = 1 [(.google.api.field_behavior) = OUTPUT_ONLY];
      Parameters:
      value - The bytes for name to set.
      Returns:
      This builder for chaining.
    • getDisplayName

      public String 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.
       
      string display_name = 2 [(.google.api.field_behavior) = REQUIRED];
      Specified by:
      getDisplayName in interface ModelDeploymentMonitoringJobOrBuilder
      Returns:
      The displayName.
    • getDisplayNameBytes

      public com.google.protobuf.ByteString getDisplayNameBytes()
       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.
       
      string display_name = 2 [(.google.api.field_behavior) = REQUIRED];
      Specified by:
      getDisplayNameBytes in interface ModelDeploymentMonitoringJobOrBuilder
      Returns:
      The bytes for displayName.
    • setDisplayName

      public ModelDeploymentMonitoringJob.Builder setDisplayName(String value)
       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.
       
      string display_name = 2 [(.google.api.field_behavior) = REQUIRED];
      Parameters:
      value - The displayName to set.
      Returns:
      This builder for chaining.
    • clearDisplayName

      public ModelDeploymentMonitoringJob.Builder clearDisplayName()
       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.
       
      string display_name = 2 [(.google.api.field_behavior) = REQUIRED];
      Returns:
      This builder for chaining.
    • setDisplayNameBytes

      public ModelDeploymentMonitoringJob.Builder setDisplayNameBytes(com.google.protobuf.ByteString value)
       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.
       
      string display_name = 2 [(.google.api.field_behavior) = REQUIRED];
      Parameters:
      value - The bytes for displayName to set.
      Returns:
      This builder for chaining.
    • getEndpoint

      public String getEndpoint()
       Required. Endpoint resource name.
       Format: `projects/{project}/locations/{location}/endpoints/{endpoint}`
       
      string endpoint = 3 [(.google.api.field_behavior) = REQUIRED, (.google.api.resource_reference) = { ... }
      Specified by:
      getEndpoint in interface ModelDeploymentMonitoringJobOrBuilder
      Returns:
      The endpoint.
    • getEndpointBytes

      public com.google.protobuf.ByteString getEndpointBytes()
       Required. Endpoint resource name.
       Format: `projects/{project}/locations/{location}/endpoints/{endpoint}`
       
      string endpoint = 3 [(.google.api.field_behavior) = REQUIRED, (.google.api.resource_reference) = { ... }
      Specified by:
      getEndpointBytes in interface ModelDeploymentMonitoringJobOrBuilder
      Returns:
      The bytes for endpoint.
    • setEndpoint

      public ModelDeploymentMonitoringJob.Builder setEndpoint(String value)
       Required. Endpoint resource name.
       Format: `projects/{project}/locations/{location}/endpoints/{endpoint}`
       
      string endpoint = 3 [(.google.api.field_behavior) = REQUIRED, (.google.api.resource_reference) = { ... }
      Parameters:
      value - The endpoint to set.
      Returns:
      This builder for chaining.
    • clearEndpoint

      public ModelDeploymentMonitoringJob.Builder clearEndpoint()
       Required. Endpoint resource name.
       Format: `projects/{project}/locations/{location}/endpoints/{endpoint}`
       
      string endpoint = 3 [(.google.api.field_behavior) = REQUIRED, (.google.api.resource_reference) = { ... }
      Returns:
      This builder for chaining.
    • setEndpointBytes

      public ModelDeploymentMonitoringJob.Builder setEndpointBytes(com.google.protobuf.ByteString value)
       Required. Endpoint resource name.
       Format: `projects/{project}/locations/{location}/endpoints/{endpoint}`
       
      string endpoint = 3 [(.google.api.field_behavior) = REQUIRED, (.google.api.resource_reference) = { ... }
      Parameters:
      value - The bytes for endpoint to set.
      Returns:
      This builder for chaining.
    • getStateValue

      public int getStateValue()
       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'.
       
      .google.cloud.aiplatform.v1.JobState state = 4 [(.google.api.field_behavior) = OUTPUT_ONLY];
      Specified by:
      getStateValue in interface ModelDeploymentMonitoringJobOrBuilder
      Returns:
      The enum numeric value on the wire for state.
    • setStateValue

      public ModelDeploymentMonitoringJob.Builder setStateValue(int value)
       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'.
       
      .google.cloud.aiplatform.v1.JobState state = 4 [(.google.api.field_behavior) = OUTPUT_ONLY];
      Parameters:
      value - The enum numeric value on the wire for state to set.
      Returns:
      This builder for chaining.
    • getState

      public JobState 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'.
       
      .google.cloud.aiplatform.v1.JobState state = 4 [(.google.api.field_behavior) = OUTPUT_ONLY];
      Specified by:
      getState in interface ModelDeploymentMonitoringJobOrBuilder
      Returns:
      The state.
    • 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'.
       
      .google.cloud.aiplatform.v1.JobState state = 4 [(.google.api.field_behavior) = OUTPUT_ONLY];
      Parameters:
      value - The state to set.
      Returns:
      This builder for chaining.
    • clearState

       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'.
       
      .google.cloud.aiplatform.v1.JobState state = 4 [(.google.api.field_behavior) = OUTPUT_ONLY];
      Returns:
      This builder for chaining.
    • getScheduleStateValue

      public int getScheduleStateValue()
       Output only. Schedule state when the monitoring job is in Running state.
       
      .google.cloud.aiplatform.v1.ModelDeploymentMonitoringJob.MonitoringScheduleState schedule_state = 5 [(.google.api.field_behavior) = OUTPUT_ONLY];
      Specified by:
      getScheduleStateValue in interface ModelDeploymentMonitoringJobOrBuilder
      Returns:
      The enum numeric value on the wire for scheduleState.
    • setScheduleStateValue

      public ModelDeploymentMonitoringJob.Builder setScheduleStateValue(int value)
       Output only. Schedule state when the monitoring job is in Running state.
       
      .google.cloud.aiplatform.v1.ModelDeploymentMonitoringJob.MonitoringScheduleState schedule_state = 5 [(.google.api.field_behavior) = OUTPUT_ONLY];
      Parameters:
      value - The enum numeric value on the wire for scheduleState to set.
      Returns:
      This builder for chaining.
    • getScheduleState

       Output only. Schedule state when the monitoring job is in Running state.
       
      .google.cloud.aiplatform.v1.ModelDeploymentMonitoringJob.MonitoringScheduleState schedule_state = 5 [(.google.api.field_behavior) = OUTPUT_ONLY];
      Specified by:
      getScheduleState in interface ModelDeploymentMonitoringJobOrBuilder
      Returns:
      The scheduleState.
    • setScheduleState

       Output only. Schedule state when the monitoring job is in Running state.
       
      .google.cloud.aiplatform.v1.ModelDeploymentMonitoringJob.MonitoringScheduleState schedule_state = 5 [(.google.api.field_behavior) = OUTPUT_ONLY];
      Parameters:
      value - The scheduleState to set.
      Returns:
      This builder for chaining.
    • clearScheduleState

      public ModelDeploymentMonitoringJob.Builder clearScheduleState()
       Output only. Schedule state when the monitoring job is in Running state.
       
      .google.cloud.aiplatform.v1.ModelDeploymentMonitoringJob.MonitoringScheduleState schedule_state = 5 [(.google.api.field_behavior) = OUTPUT_ONLY];
      Returns:
      This builder for chaining.
    • hasLatestMonitoringPipelineMetadata

      public boolean hasLatestMonitoringPipelineMetadata()
       Output only. Latest triggered monitoring pipeline metadata.
       
      .google.cloud.aiplatform.v1.ModelDeploymentMonitoringJob.LatestMonitoringPipelineMetadata latest_monitoring_pipeline_metadata = 25 [(.google.api.field_behavior) = OUTPUT_ONLY];
      Specified by:
      hasLatestMonitoringPipelineMetadata in interface ModelDeploymentMonitoringJobOrBuilder
      Returns:
      Whether the latestMonitoringPipelineMetadata field is set.
    • getLatestMonitoringPipelineMetadata

      public ModelDeploymentMonitoringJob.LatestMonitoringPipelineMetadata getLatestMonitoringPipelineMetadata()
       Output only. Latest triggered monitoring pipeline metadata.
       
      .google.cloud.aiplatform.v1.ModelDeploymentMonitoringJob.LatestMonitoringPipelineMetadata latest_monitoring_pipeline_metadata = 25 [(.google.api.field_behavior) = OUTPUT_ONLY];
      Specified by:
      getLatestMonitoringPipelineMetadata in interface ModelDeploymentMonitoringJobOrBuilder
      Returns:
      The latestMonitoringPipelineMetadata.
    • setLatestMonitoringPipelineMetadata

       Output only. Latest triggered monitoring pipeline metadata.
       
      .google.cloud.aiplatform.v1.ModelDeploymentMonitoringJob.LatestMonitoringPipelineMetadata latest_monitoring_pipeline_metadata = 25 [(.google.api.field_behavior) = OUTPUT_ONLY];
    • setLatestMonitoringPipelineMetadata

       Output only. Latest triggered monitoring pipeline metadata.
       
      .google.cloud.aiplatform.v1.ModelDeploymentMonitoringJob.LatestMonitoringPipelineMetadata latest_monitoring_pipeline_metadata = 25 [(.google.api.field_behavior) = OUTPUT_ONLY];
    • mergeLatestMonitoringPipelineMetadata

       Output only. Latest triggered monitoring pipeline metadata.
       
      .google.cloud.aiplatform.v1.ModelDeploymentMonitoringJob.LatestMonitoringPipelineMetadata latest_monitoring_pipeline_metadata = 25 [(.google.api.field_behavior) = OUTPUT_ONLY];
    • clearLatestMonitoringPipelineMetadata

      public ModelDeploymentMonitoringJob.Builder clearLatestMonitoringPipelineMetadata()
       Output only. Latest triggered monitoring pipeline metadata.
       
      .google.cloud.aiplatform.v1.ModelDeploymentMonitoringJob.LatestMonitoringPipelineMetadata latest_monitoring_pipeline_metadata = 25 [(.google.api.field_behavior) = OUTPUT_ONLY];
    • getLatestMonitoringPipelineMetadataBuilder

      public ModelDeploymentMonitoringJob.LatestMonitoringPipelineMetadata.Builder getLatestMonitoringPipelineMetadataBuilder()
       Output only. Latest triggered monitoring pipeline metadata.
       
      .google.cloud.aiplatform.v1.ModelDeploymentMonitoringJob.LatestMonitoringPipelineMetadata latest_monitoring_pipeline_metadata = 25 [(.google.api.field_behavior) = OUTPUT_ONLY];
    • getLatestMonitoringPipelineMetadataOrBuilder

      public ModelDeploymentMonitoringJob.LatestMonitoringPipelineMetadataOrBuilder getLatestMonitoringPipelineMetadataOrBuilder()
       Output only. Latest triggered monitoring pipeline metadata.
       
      .google.cloud.aiplatform.v1.ModelDeploymentMonitoringJob.LatestMonitoringPipelineMetadata latest_monitoring_pipeline_metadata = 25 [(.google.api.field_behavior) = OUTPUT_ONLY];
      Specified by:
      getLatestMonitoringPipelineMetadataOrBuilder in interface ModelDeploymentMonitoringJobOrBuilder
    • getModelDeploymentMonitoringObjectiveConfigsList

      public List<ModelDeploymentMonitoringObjectiveConfig> getModelDeploymentMonitoringObjectiveConfigsList()
       Required. The config for monitoring objectives. This is a per DeployedModel
       config. Each DeployedModel needs to be configured separately.
       
      repeated .google.cloud.aiplatform.v1.ModelDeploymentMonitoringObjectiveConfig model_deployment_monitoring_objective_configs = 6 [(.google.api.field_behavior) = REQUIRED];
      Specified by:
      getModelDeploymentMonitoringObjectiveConfigsList in interface ModelDeploymentMonitoringJobOrBuilder
    • getModelDeploymentMonitoringObjectiveConfigsCount

      public int getModelDeploymentMonitoringObjectiveConfigsCount()
       Required. The config for monitoring objectives. This is a per DeployedModel
       config. Each DeployedModel needs to be configured separately.
       
      repeated .google.cloud.aiplatform.v1.ModelDeploymentMonitoringObjectiveConfig model_deployment_monitoring_objective_configs = 6 [(.google.api.field_behavior) = REQUIRED];
      Specified by:
      getModelDeploymentMonitoringObjectiveConfigsCount in interface ModelDeploymentMonitoringJobOrBuilder
    • getModelDeploymentMonitoringObjectiveConfigs

      public ModelDeploymentMonitoringObjectiveConfig getModelDeploymentMonitoringObjectiveConfigs(int index)
       Required. The config for monitoring objectives. This is a per DeployedModel
       config. Each DeployedModel needs to be configured separately.
       
      repeated .google.cloud.aiplatform.v1.ModelDeploymentMonitoringObjectiveConfig model_deployment_monitoring_objective_configs = 6 [(.google.api.field_behavior) = REQUIRED];
      Specified by:
      getModelDeploymentMonitoringObjectiveConfigs in interface ModelDeploymentMonitoringJobOrBuilder
    • setModelDeploymentMonitoringObjectiveConfigs

      public ModelDeploymentMonitoringJob.Builder setModelDeploymentMonitoringObjectiveConfigs(int index, ModelDeploymentMonitoringObjectiveConfig value)
       Required. The config for monitoring objectives. This is a per DeployedModel
       config. Each DeployedModel needs to be configured separately.
       
      repeated .google.cloud.aiplatform.v1.ModelDeploymentMonitoringObjectiveConfig model_deployment_monitoring_objective_configs = 6 [(.google.api.field_behavior) = REQUIRED];
    • setModelDeploymentMonitoringObjectiveConfigs

      public ModelDeploymentMonitoringJob.Builder setModelDeploymentMonitoringObjectiveConfigs(int index, ModelDeploymentMonitoringObjectiveConfig.Builder builderForValue)
       Required. The config for monitoring objectives. This is a per DeployedModel
       config. Each DeployedModel needs to be configured separately.
       
      repeated .google.cloud.aiplatform.v1.ModelDeploymentMonitoringObjectiveConfig model_deployment_monitoring_objective_configs = 6 [(.google.api.field_behavior) = REQUIRED];
    • addModelDeploymentMonitoringObjectiveConfigs

      public ModelDeploymentMonitoringJob.Builder addModelDeploymentMonitoringObjectiveConfigs(ModelDeploymentMonitoringObjectiveConfig value)
       Required. The config for monitoring objectives. This is a per DeployedModel
       config. Each DeployedModel needs to be configured separately.
       
      repeated .google.cloud.aiplatform.v1.ModelDeploymentMonitoringObjectiveConfig model_deployment_monitoring_objective_configs = 6 [(.google.api.field_behavior) = REQUIRED];
    • addModelDeploymentMonitoringObjectiveConfigs

      public ModelDeploymentMonitoringJob.Builder addModelDeploymentMonitoringObjectiveConfigs(int index, ModelDeploymentMonitoringObjectiveConfig value)
       Required. The config for monitoring objectives. This is a per DeployedModel
       config. Each DeployedModel needs to be configured separately.
       
      repeated .google.cloud.aiplatform.v1.ModelDeploymentMonitoringObjectiveConfig model_deployment_monitoring_objective_configs = 6 [(.google.api.field_behavior) = REQUIRED];
    • addModelDeploymentMonitoringObjectiveConfigs

      public ModelDeploymentMonitoringJob.Builder addModelDeploymentMonitoringObjectiveConfigs(ModelDeploymentMonitoringObjectiveConfig.Builder builderForValue)
       Required. The config for monitoring objectives. This is a per DeployedModel
       config. Each DeployedModel needs to be configured separately.
       
      repeated .google.cloud.aiplatform.v1.ModelDeploymentMonitoringObjectiveConfig model_deployment_monitoring_objective_configs = 6 [(.google.api.field_behavior) = REQUIRED];
    • addModelDeploymentMonitoringObjectiveConfigs

      public ModelDeploymentMonitoringJob.Builder addModelDeploymentMonitoringObjectiveConfigs(int index, ModelDeploymentMonitoringObjectiveConfig.Builder builderForValue)
       Required. The config for monitoring objectives. This is a per DeployedModel
       config. Each DeployedModel needs to be configured separately.
       
      repeated .google.cloud.aiplatform.v1.ModelDeploymentMonitoringObjectiveConfig model_deployment_monitoring_objective_configs = 6 [(.google.api.field_behavior) = REQUIRED];
    • addAllModelDeploymentMonitoringObjectiveConfigs

      public ModelDeploymentMonitoringJob.Builder addAllModelDeploymentMonitoringObjectiveConfigs(Iterable<? extends ModelDeploymentMonitoringObjectiveConfig> values)
       Required. The config for monitoring objectives. This is a per DeployedModel
       config. Each DeployedModel needs to be configured separately.
       
      repeated .google.cloud.aiplatform.v1.ModelDeploymentMonitoringObjectiveConfig model_deployment_monitoring_objective_configs = 6 [(.google.api.field_behavior) = REQUIRED];
    • clearModelDeploymentMonitoringObjectiveConfigs

      public ModelDeploymentMonitoringJob.Builder clearModelDeploymentMonitoringObjectiveConfigs()
       Required. The config for monitoring objectives. This is a per DeployedModel
       config. Each DeployedModel needs to be configured separately.
       
      repeated .google.cloud.aiplatform.v1.ModelDeploymentMonitoringObjectiveConfig model_deployment_monitoring_objective_configs = 6 [(.google.api.field_behavior) = REQUIRED];
    • removeModelDeploymentMonitoringObjectiveConfigs

      public ModelDeploymentMonitoringJob.Builder removeModelDeploymentMonitoringObjectiveConfigs(int index)
       Required. The config for monitoring objectives. This is a per DeployedModel
       config. Each DeployedModel needs to be configured separately.
       
      repeated .google.cloud.aiplatform.v1.ModelDeploymentMonitoringObjectiveConfig model_deployment_monitoring_objective_configs = 6 [(.google.api.field_behavior) = REQUIRED];
    • getModelDeploymentMonitoringObjectiveConfigsBuilder

      public ModelDeploymentMonitoringObjectiveConfig.Builder getModelDeploymentMonitoringObjectiveConfigsBuilder(int index)
       Required. The config for monitoring objectives. This is a per DeployedModel
       config. Each DeployedModel needs to be configured separately.
       
      repeated .google.cloud.aiplatform.v1.ModelDeploymentMonitoringObjectiveConfig model_deployment_monitoring_objective_configs = 6 [(.google.api.field_behavior) = REQUIRED];
    • getModelDeploymentMonitoringObjectiveConfigsOrBuilder

      public ModelDeploymentMonitoringObjectiveConfigOrBuilder getModelDeploymentMonitoringObjectiveConfigsOrBuilder(int index)
       Required. The config for monitoring objectives. This is a per DeployedModel
       config. Each DeployedModel needs to be configured separately.
       
      repeated .google.cloud.aiplatform.v1.ModelDeploymentMonitoringObjectiveConfig model_deployment_monitoring_objective_configs = 6 [(.google.api.field_behavior) = REQUIRED];
      Specified by:
      getModelDeploymentMonitoringObjectiveConfigsOrBuilder in interface ModelDeploymentMonitoringJobOrBuilder
    • getModelDeploymentMonitoringObjectiveConfigsOrBuilderList

      public List<? extends ModelDeploymentMonitoringObjectiveConfigOrBuilder> getModelDeploymentMonitoringObjectiveConfigsOrBuilderList()
       Required. The config for monitoring objectives. This is a per DeployedModel
       config. Each DeployedModel needs to be configured separately.
       
      repeated .google.cloud.aiplatform.v1.ModelDeploymentMonitoringObjectiveConfig model_deployment_monitoring_objective_configs = 6 [(.google.api.field_behavior) = REQUIRED];
      Specified by:
      getModelDeploymentMonitoringObjectiveConfigsOrBuilderList in interface ModelDeploymentMonitoringJobOrBuilder
    • addModelDeploymentMonitoringObjectiveConfigsBuilder

      public ModelDeploymentMonitoringObjectiveConfig.Builder addModelDeploymentMonitoringObjectiveConfigsBuilder()
       Required. The config for monitoring objectives. This is a per DeployedModel
       config. Each DeployedModel needs to be configured separately.
       
      repeated .google.cloud.aiplatform.v1.ModelDeploymentMonitoringObjectiveConfig model_deployment_monitoring_objective_configs = 6 [(.google.api.field_behavior) = REQUIRED];
    • addModelDeploymentMonitoringObjectiveConfigsBuilder

      public ModelDeploymentMonitoringObjectiveConfig.Builder addModelDeploymentMonitoringObjectiveConfigsBuilder(int index)
       Required. The config for monitoring objectives. This is a per DeployedModel
       config. Each DeployedModel needs to be configured separately.
       
      repeated .google.cloud.aiplatform.v1.ModelDeploymentMonitoringObjectiveConfig model_deployment_monitoring_objective_configs = 6 [(.google.api.field_behavior) = REQUIRED];
    • getModelDeploymentMonitoringObjectiveConfigsBuilderList

      public List<ModelDeploymentMonitoringObjectiveConfig.Builder> getModelDeploymentMonitoringObjectiveConfigsBuilderList()
       Required. The config for monitoring objectives. This is a per DeployedModel
       config. Each DeployedModel needs to be configured separately.
       
      repeated .google.cloud.aiplatform.v1.ModelDeploymentMonitoringObjectiveConfig model_deployment_monitoring_objective_configs = 6 [(.google.api.field_behavior) = REQUIRED];
    • hasModelDeploymentMonitoringScheduleConfig

      public boolean hasModelDeploymentMonitoringScheduleConfig()
       Required. Schedule config for running the monitoring job.
       
      .google.cloud.aiplatform.v1.ModelDeploymentMonitoringScheduleConfig model_deployment_monitoring_schedule_config = 7 [(.google.api.field_behavior) = REQUIRED];
      Specified by:
      hasModelDeploymentMonitoringScheduleConfig in interface ModelDeploymentMonitoringJobOrBuilder
      Returns:
      Whether the modelDeploymentMonitoringScheduleConfig field is set.
    • getModelDeploymentMonitoringScheduleConfig

      public ModelDeploymentMonitoringScheduleConfig getModelDeploymentMonitoringScheduleConfig()
       Required. Schedule config for running the monitoring job.
       
      .google.cloud.aiplatform.v1.ModelDeploymentMonitoringScheduleConfig model_deployment_monitoring_schedule_config = 7 [(.google.api.field_behavior) = REQUIRED];
      Specified by:
      getModelDeploymentMonitoringScheduleConfig in interface ModelDeploymentMonitoringJobOrBuilder
      Returns:
      The modelDeploymentMonitoringScheduleConfig.
    • setModelDeploymentMonitoringScheduleConfig

      public ModelDeploymentMonitoringJob.Builder setModelDeploymentMonitoringScheduleConfig(ModelDeploymentMonitoringScheduleConfig value)
       Required. Schedule config for running the monitoring job.
       
      .google.cloud.aiplatform.v1.ModelDeploymentMonitoringScheduleConfig model_deployment_monitoring_schedule_config = 7 [(.google.api.field_behavior) = REQUIRED];
    • setModelDeploymentMonitoringScheduleConfig

      public ModelDeploymentMonitoringJob.Builder setModelDeploymentMonitoringScheduleConfig(ModelDeploymentMonitoringScheduleConfig.Builder builderForValue)
       Required. Schedule config for running the monitoring job.
       
      .google.cloud.aiplatform.v1.ModelDeploymentMonitoringScheduleConfig model_deployment_monitoring_schedule_config = 7 [(.google.api.field_behavior) = REQUIRED];
    • mergeModelDeploymentMonitoringScheduleConfig

      public ModelDeploymentMonitoringJob.Builder mergeModelDeploymentMonitoringScheduleConfig(ModelDeploymentMonitoringScheduleConfig value)
       Required. Schedule config for running the monitoring job.
       
      .google.cloud.aiplatform.v1.ModelDeploymentMonitoringScheduleConfig model_deployment_monitoring_schedule_config = 7 [(.google.api.field_behavior) = REQUIRED];
    • clearModelDeploymentMonitoringScheduleConfig

      public ModelDeploymentMonitoringJob.Builder clearModelDeploymentMonitoringScheduleConfig()
       Required. Schedule config for running the monitoring job.
       
      .google.cloud.aiplatform.v1.ModelDeploymentMonitoringScheduleConfig model_deployment_monitoring_schedule_config = 7 [(.google.api.field_behavior) = REQUIRED];
    • getModelDeploymentMonitoringScheduleConfigBuilder

      public ModelDeploymentMonitoringScheduleConfig.Builder getModelDeploymentMonitoringScheduleConfigBuilder()
       Required. Schedule config for running the monitoring job.
       
      .google.cloud.aiplatform.v1.ModelDeploymentMonitoringScheduleConfig model_deployment_monitoring_schedule_config = 7 [(.google.api.field_behavior) = REQUIRED];
    • getModelDeploymentMonitoringScheduleConfigOrBuilder

      public ModelDeploymentMonitoringScheduleConfigOrBuilder getModelDeploymentMonitoringScheduleConfigOrBuilder()
       Required. Schedule config for running the monitoring job.
       
      .google.cloud.aiplatform.v1.ModelDeploymentMonitoringScheduleConfig model_deployment_monitoring_schedule_config = 7 [(.google.api.field_behavior) = REQUIRED];
      Specified by:
      getModelDeploymentMonitoringScheduleConfigOrBuilder in interface ModelDeploymentMonitoringJobOrBuilder
    • hasLoggingSamplingStrategy

      public boolean hasLoggingSamplingStrategy()
       Required. Sample Strategy for logging.
       
      .google.cloud.aiplatform.v1.SamplingStrategy logging_sampling_strategy = 8 [(.google.api.field_behavior) = REQUIRED];
      Specified by:
      hasLoggingSamplingStrategy in interface ModelDeploymentMonitoringJobOrBuilder
      Returns:
      Whether the loggingSamplingStrategy field is set.
    • getLoggingSamplingStrategy

      public SamplingStrategy getLoggingSamplingStrategy()
       Required. Sample Strategy for logging.
       
      .google.cloud.aiplatform.v1.SamplingStrategy logging_sampling_strategy = 8 [(.google.api.field_behavior) = REQUIRED];
      Specified by:
      getLoggingSamplingStrategy in interface ModelDeploymentMonitoringJobOrBuilder
      Returns:
      The loggingSamplingStrategy.
    • setLoggingSamplingStrategy

      public ModelDeploymentMonitoringJob.Builder setLoggingSamplingStrategy(SamplingStrategy value)
       Required. Sample Strategy for logging.
       
      .google.cloud.aiplatform.v1.SamplingStrategy logging_sampling_strategy = 8 [(.google.api.field_behavior) = REQUIRED];
    • setLoggingSamplingStrategy

      public ModelDeploymentMonitoringJob.Builder setLoggingSamplingStrategy(SamplingStrategy.Builder builderForValue)
       Required. Sample Strategy for logging.
       
      .google.cloud.aiplatform.v1.SamplingStrategy logging_sampling_strategy = 8 [(.google.api.field_behavior) = REQUIRED];
    • mergeLoggingSamplingStrategy

      public ModelDeploymentMonitoringJob.Builder mergeLoggingSamplingStrategy(SamplingStrategy value)
       Required. Sample Strategy for logging.
       
      .google.cloud.aiplatform.v1.SamplingStrategy logging_sampling_strategy = 8 [(.google.api.field_behavior) = REQUIRED];
    • clearLoggingSamplingStrategy

      public ModelDeploymentMonitoringJob.Builder clearLoggingSamplingStrategy()
       Required. Sample Strategy for logging.
       
      .google.cloud.aiplatform.v1.SamplingStrategy logging_sampling_strategy = 8 [(.google.api.field_behavior) = REQUIRED];
    • getLoggingSamplingStrategyBuilder

      public SamplingStrategy.Builder getLoggingSamplingStrategyBuilder()
       Required. Sample Strategy for logging.
       
      .google.cloud.aiplatform.v1.SamplingStrategy logging_sampling_strategy = 8 [(.google.api.field_behavior) = REQUIRED];
    • getLoggingSamplingStrategyOrBuilder

      public SamplingStrategyOrBuilder getLoggingSamplingStrategyOrBuilder()
       Required. Sample Strategy for logging.
       
      .google.cloud.aiplatform.v1.SamplingStrategy logging_sampling_strategy = 8 [(.google.api.field_behavior) = REQUIRED];
      Specified by:
      getLoggingSamplingStrategyOrBuilder in interface ModelDeploymentMonitoringJobOrBuilder
    • hasModelMonitoringAlertConfig

      public boolean hasModelMonitoringAlertConfig()
       Alert config for model monitoring.
       
      .google.cloud.aiplatform.v1.ModelMonitoringAlertConfig model_monitoring_alert_config = 15;
      Specified by:
      hasModelMonitoringAlertConfig in interface ModelDeploymentMonitoringJobOrBuilder
      Returns:
      Whether the modelMonitoringAlertConfig field is set.
    • getModelMonitoringAlertConfig

      public ModelMonitoringAlertConfig getModelMonitoringAlertConfig()
       Alert config for model monitoring.
       
      .google.cloud.aiplatform.v1.ModelMonitoringAlertConfig model_monitoring_alert_config = 15;
      Specified by:
      getModelMonitoringAlertConfig in interface ModelDeploymentMonitoringJobOrBuilder
      Returns:
      The modelMonitoringAlertConfig.
    • setModelMonitoringAlertConfig

      public ModelDeploymentMonitoringJob.Builder setModelMonitoringAlertConfig(ModelMonitoringAlertConfig value)
       Alert config for model monitoring.
       
      .google.cloud.aiplatform.v1.ModelMonitoringAlertConfig model_monitoring_alert_config = 15;
    • setModelMonitoringAlertConfig

      public ModelDeploymentMonitoringJob.Builder setModelMonitoringAlertConfig(ModelMonitoringAlertConfig.Builder builderForValue)
       Alert config for model monitoring.
       
      .google.cloud.aiplatform.v1.ModelMonitoringAlertConfig model_monitoring_alert_config = 15;
    • mergeModelMonitoringAlertConfig

      public ModelDeploymentMonitoringJob.Builder mergeModelMonitoringAlertConfig(ModelMonitoringAlertConfig value)
       Alert config for model monitoring.
       
      .google.cloud.aiplatform.v1.ModelMonitoringAlertConfig model_monitoring_alert_config = 15;
    • clearModelMonitoringAlertConfig

      public ModelDeploymentMonitoringJob.Builder clearModelMonitoringAlertConfig()
       Alert config for model monitoring.
       
      .google.cloud.aiplatform.v1.ModelMonitoringAlertConfig model_monitoring_alert_config = 15;
    • getModelMonitoringAlertConfigBuilder

      public ModelMonitoringAlertConfig.Builder getModelMonitoringAlertConfigBuilder()
       Alert config for model monitoring.
       
      .google.cloud.aiplatform.v1.ModelMonitoringAlertConfig model_monitoring_alert_config = 15;
    • getModelMonitoringAlertConfigOrBuilder

      public ModelMonitoringAlertConfigOrBuilder getModelMonitoringAlertConfigOrBuilder()
       Alert config for model monitoring.
       
      .google.cloud.aiplatform.v1.ModelMonitoringAlertConfig model_monitoring_alert_config = 15;
      Specified by:
      getModelMonitoringAlertConfigOrBuilder in interface ModelDeploymentMonitoringJobOrBuilder
    • getPredictInstanceSchemaUri

      public String 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.
       
      string predict_instance_schema_uri = 9;
      Specified by:
      getPredictInstanceSchemaUri in interface ModelDeploymentMonitoringJobOrBuilder
      Returns:
      The predictInstanceSchemaUri.
    • getPredictInstanceSchemaUriBytes

      public com.google.protobuf.ByteString getPredictInstanceSchemaUriBytes()
       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.
       
      string predict_instance_schema_uri = 9;
      Specified by:
      getPredictInstanceSchemaUriBytes in interface ModelDeploymentMonitoringJobOrBuilder
      Returns:
      The bytes for predictInstanceSchemaUri.
    • setPredictInstanceSchemaUri

      public ModelDeploymentMonitoringJob.Builder setPredictInstanceSchemaUri(String value)
       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.
       
      string predict_instance_schema_uri = 9;
      Parameters:
      value - The predictInstanceSchemaUri to set.
      Returns:
      This builder for chaining.
    • clearPredictInstanceSchemaUri

      public ModelDeploymentMonitoringJob.Builder clearPredictInstanceSchemaUri()
       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.
       
      string predict_instance_schema_uri = 9;
      Returns:
      This builder for chaining.
    • setPredictInstanceSchemaUriBytes

      public ModelDeploymentMonitoringJob.Builder setPredictInstanceSchemaUriBytes(com.google.protobuf.ByteString value)
       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.
       
      string predict_instance_schema_uri = 9;
      Parameters:
      value - The bytes for predictInstanceSchemaUri to set.
      Returns:
      This builder for chaining.
    • hasSamplePredictInstance

      public boolean hasSamplePredictInstance()
       Sample Predict instance, same format as
       [PredictRequest.instances][google.cloud.aiplatform.v1.PredictRequest.instances],
       this can be set as a replacement of
       [ModelDeploymentMonitoringJob.predict_instance_schema_uri][google.cloud.aiplatform.v1.ModelDeploymentMonitoringJob.predict_instance_schema_uri].
       If not set, we will generate predict schema from collected predict
       requests.
       
      .google.protobuf.Value sample_predict_instance = 19;
      Specified by:
      hasSamplePredictInstance in interface ModelDeploymentMonitoringJobOrBuilder
      Returns:
      Whether the samplePredictInstance field is set.
    • getSamplePredictInstance

      public com.google.protobuf.Value getSamplePredictInstance()
       Sample Predict instance, same format as
       [PredictRequest.instances][google.cloud.aiplatform.v1.PredictRequest.instances],
       this can be set as a replacement of
       [ModelDeploymentMonitoringJob.predict_instance_schema_uri][google.cloud.aiplatform.v1.ModelDeploymentMonitoringJob.predict_instance_schema_uri].
       If not set, we will generate predict schema from collected predict
       requests.
       
      .google.protobuf.Value sample_predict_instance = 19;
      Specified by:
      getSamplePredictInstance in interface ModelDeploymentMonitoringJobOrBuilder
      Returns:
      The samplePredictInstance.
    • setSamplePredictInstance

      public ModelDeploymentMonitoringJob.Builder setSamplePredictInstance(com.google.protobuf.Value value)
       Sample Predict instance, same format as
       [PredictRequest.instances][google.cloud.aiplatform.v1.PredictRequest.instances],
       this can be set as a replacement of
       [ModelDeploymentMonitoringJob.predict_instance_schema_uri][google.cloud.aiplatform.v1.ModelDeploymentMonitoringJob.predict_instance_schema_uri].
       If not set, we will generate predict schema from collected predict
       requests.
       
      .google.protobuf.Value sample_predict_instance = 19;
    • setSamplePredictInstance

      public ModelDeploymentMonitoringJob.Builder setSamplePredictInstance(com.google.protobuf.Value.Builder builderForValue)
       Sample Predict instance, same format as
       [PredictRequest.instances][google.cloud.aiplatform.v1.PredictRequest.instances],
       this can be set as a replacement of
       [ModelDeploymentMonitoringJob.predict_instance_schema_uri][google.cloud.aiplatform.v1.ModelDeploymentMonitoringJob.predict_instance_schema_uri].
       If not set, we will generate predict schema from collected predict
       requests.
       
      .google.protobuf.Value sample_predict_instance = 19;
    • mergeSamplePredictInstance

      public ModelDeploymentMonitoringJob.Builder mergeSamplePredictInstance(com.google.protobuf.Value value)
       Sample Predict instance, same format as
       [PredictRequest.instances][google.cloud.aiplatform.v1.PredictRequest.instances],
       this can be set as a replacement of
       [ModelDeploymentMonitoringJob.predict_instance_schema_uri][google.cloud.aiplatform.v1.ModelDeploymentMonitoringJob.predict_instance_schema_uri].
       If not set, we will generate predict schema from collected predict
       requests.
       
      .google.protobuf.Value sample_predict_instance = 19;
    • clearSamplePredictInstance

      public ModelDeploymentMonitoringJob.Builder clearSamplePredictInstance()
       Sample Predict instance, same format as
       [PredictRequest.instances][google.cloud.aiplatform.v1.PredictRequest.instances],
       this can be set as a replacement of
       [ModelDeploymentMonitoringJob.predict_instance_schema_uri][google.cloud.aiplatform.v1.ModelDeploymentMonitoringJob.predict_instance_schema_uri].
       If not set, we will generate predict schema from collected predict
       requests.
       
      .google.protobuf.Value sample_predict_instance = 19;
    • getSamplePredictInstanceBuilder

      public com.google.protobuf.Value.Builder getSamplePredictInstanceBuilder()
       Sample Predict instance, same format as
       [PredictRequest.instances][google.cloud.aiplatform.v1.PredictRequest.instances],
       this can be set as a replacement of
       [ModelDeploymentMonitoringJob.predict_instance_schema_uri][google.cloud.aiplatform.v1.ModelDeploymentMonitoringJob.predict_instance_schema_uri].
       If not set, we will generate predict schema from collected predict
       requests.
       
      .google.protobuf.Value sample_predict_instance = 19;
    • getSamplePredictInstanceOrBuilder

      public com.google.protobuf.ValueOrBuilder getSamplePredictInstanceOrBuilder()
       Sample Predict instance, same format as
       [PredictRequest.instances][google.cloud.aiplatform.v1.PredictRequest.instances],
       this can be set as a replacement of
       [ModelDeploymentMonitoringJob.predict_instance_schema_uri][google.cloud.aiplatform.v1.ModelDeploymentMonitoringJob.predict_instance_schema_uri].
       If not set, we will generate predict schema from collected predict
       requests.
       
      .google.protobuf.Value sample_predict_instance = 19;
      Specified by:
      getSamplePredictInstanceOrBuilder in interface ModelDeploymentMonitoringJobOrBuilder
    • getAnalysisInstanceSchemaUri

      public String 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][google.cloud.aiplatform.v1.ModelDeploymentMonitoringJob.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.
       
      string analysis_instance_schema_uri = 16;
      Specified by:
      getAnalysisInstanceSchemaUri in interface ModelDeploymentMonitoringJobOrBuilder
      Returns:
      The analysisInstanceSchemaUri.
    • getAnalysisInstanceSchemaUriBytes

      public com.google.protobuf.ByteString getAnalysisInstanceSchemaUriBytes()
       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][google.cloud.aiplatform.v1.ModelDeploymentMonitoringJob.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.
       
      string analysis_instance_schema_uri = 16;
      Specified by:
      getAnalysisInstanceSchemaUriBytes in interface ModelDeploymentMonitoringJobOrBuilder
      Returns:
      The bytes for analysisInstanceSchemaUri.
    • setAnalysisInstanceSchemaUri

      public ModelDeploymentMonitoringJob.Builder setAnalysisInstanceSchemaUri(String value)
       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][google.cloud.aiplatform.v1.ModelDeploymentMonitoringJob.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.
       
      string analysis_instance_schema_uri = 16;
      Parameters:
      value - The analysisInstanceSchemaUri to set.
      Returns:
      This builder for chaining.
    • clearAnalysisInstanceSchemaUri

      public ModelDeploymentMonitoringJob.Builder clearAnalysisInstanceSchemaUri()
       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][google.cloud.aiplatform.v1.ModelDeploymentMonitoringJob.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.
       
      string analysis_instance_schema_uri = 16;
      Returns:
      This builder for chaining.
    • setAnalysisInstanceSchemaUriBytes

      public ModelDeploymentMonitoringJob.Builder setAnalysisInstanceSchemaUriBytes(com.google.protobuf.ByteString value)
       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][google.cloud.aiplatform.v1.ModelDeploymentMonitoringJob.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.
       
      string analysis_instance_schema_uri = 16;
      Parameters:
      value - The bytes for analysisInstanceSchemaUri to set.
      Returns:
      This builder for chaining.
    • getBigqueryTablesList

      public List<ModelDeploymentMonitoringBigQueryTable> getBigqueryTablesList()
       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
       
      repeated .google.cloud.aiplatform.v1.ModelDeploymentMonitoringBigQueryTable bigquery_tables = 10 [(.google.api.field_behavior) = OUTPUT_ONLY];
      Specified by:
      getBigqueryTablesList in interface ModelDeploymentMonitoringJobOrBuilder
    • getBigqueryTablesCount

      public int getBigqueryTablesCount()
       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
       
      repeated .google.cloud.aiplatform.v1.ModelDeploymentMonitoringBigQueryTable bigquery_tables = 10 [(.google.api.field_behavior) = OUTPUT_ONLY];
      Specified by:
      getBigqueryTablesCount in interface ModelDeploymentMonitoringJobOrBuilder
    • getBigqueryTables

      public ModelDeploymentMonitoringBigQueryTable getBigqueryTables(int index)
       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
       
      repeated .google.cloud.aiplatform.v1.ModelDeploymentMonitoringBigQueryTable bigquery_tables = 10 [(.google.api.field_behavior) = OUTPUT_ONLY];
      Specified by:
      getBigqueryTables in interface ModelDeploymentMonitoringJobOrBuilder
    • 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:
       1. Training data logging predict request/response
       2. Serving data logging predict request/response
       
      repeated .google.cloud.aiplatform.v1.ModelDeploymentMonitoringBigQueryTable bigquery_tables = 10 [(.google.api.field_behavior) = OUTPUT_ONLY];
    • setBigqueryTables

      public ModelDeploymentMonitoringJob.Builder setBigqueryTables(int index, ModelDeploymentMonitoringBigQueryTable.Builder builderForValue)
       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
       
      repeated .google.cloud.aiplatform.v1.ModelDeploymentMonitoringBigQueryTable bigquery_tables = 10 [(.google.api.field_behavior) = OUTPUT_ONLY];
    • addBigqueryTables

       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
       
      repeated .google.cloud.aiplatform.v1.ModelDeploymentMonitoringBigQueryTable bigquery_tables = 10 [(.google.api.field_behavior) = OUTPUT_ONLY];
    • addBigqueryTables

       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
       
      repeated .google.cloud.aiplatform.v1.ModelDeploymentMonitoringBigQueryTable bigquery_tables = 10 [(.google.api.field_behavior) = OUTPUT_ONLY];
    • addBigqueryTables

       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
       
      repeated .google.cloud.aiplatform.v1.ModelDeploymentMonitoringBigQueryTable bigquery_tables = 10 [(.google.api.field_behavior) = OUTPUT_ONLY];
    • addBigqueryTables

      public ModelDeploymentMonitoringJob.Builder addBigqueryTables(int index, ModelDeploymentMonitoringBigQueryTable.Builder builderForValue)
       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
       
      repeated .google.cloud.aiplatform.v1.ModelDeploymentMonitoringBigQueryTable bigquery_tables = 10 [(.google.api.field_behavior) = OUTPUT_ONLY];
    • addAllBigqueryTables

       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
       
      repeated .google.cloud.aiplatform.v1.ModelDeploymentMonitoringBigQueryTable bigquery_tables = 10 [(.google.api.field_behavior) = OUTPUT_ONLY];
    • clearBigqueryTables

      public ModelDeploymentMonitoringJob.Builder clearBigqueryTables()
       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
       
      repeated .google.cloud.aiplatform.v1.ModelDeploymentMonitoringBigQueryTable bigquery_tables = 10 [(.google.api.field_behavior) = OUTPUT_ONLY];
    • removeBigqueryTables

      public ModelDeploymentMonitoringJob.Builder removeBigqueryTables(int index)
       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
       
      repeated .google.cloud.aiplatform.v1.ModelDeploymentMonitoringBigQueryTable bigquery_tables = 10 [(.google.api.field_behavior) = OUTPUT_ONLY];
    • getBigqueryTablesBuilder

      public ModelDeploymentMonitoringBigQueryTable.Builder getBigqueryTablesBuilder(int index)
       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
       
      repeated .google.cloud.aiplatform.v1.ModelDeploymentMonitoringBigQueryTable bigquery_tables = 10 [(.google.api.field_behavior) = OUTPUT_ONLY];
    • getBigqueryTablesOrBuilder

      public ModelDeploymentMonitoringBigQueryTableOrBuilder getBigqueryTablesOrBuilder(int index)
       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
       
      repeated .google.cloud.aiplatform.v1.ModelDeploymentMonitoringBigQueryTable bigquery_tables = 10 [(.google.api.field_behavior) = OUTPUT_ONLY];
      Specified by:
      getBigqueryTablesOrBuilder in interface ModelDeploymentMonitoringJobOrBuilder
    • getBigqueryTablesOrBuilderList

      public List<? extends ModelDeploymentMonitoringBigQueryTableOrBuilder> getBigqueryTablesOrBuilderList()
       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
       
      repeated .google.cloud.aiplatform.v1.ModelDeploymentMonitoringBigQueryTable bigquery_tables = 10 [(.google.api.field_behavior) = OUTPUT_ONLY];
      Specified by:
      getBigqueryTablesOrBuilderList in interface ModelDeploymentMonitoringJobOrBuilder
    • addBigqueryTablesBuilder

      public ModelDeploymentMonitoringBigQueryTable.Builder addBigqueryTablesBuilder()
       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
       
      repeated .google.cloud.aiplatform.v1.ModelDeploymentMonitoringBigQueryTable bigquery_tables = 10 [(.google.api.field_behavior) = OUTPUT_ONLY];
    • addBigqueryTablesBuilder

      public ModelDeploymentMonitoringBigQueryTable.Builder addBigqueryTablesBuilder(int index)
       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
       
      repeated .google.cloud.aiplatform.v1.ModelDeploymentMonitoringBigQueryTable bigquery_tables = 10 [(.google.api.field_behavior) = OUTPUT_ONLY];
    • getBigqueryTablesBuilderList

      public List<ModelDeploymentMonitoringBigQueryTable.Builder> getBigqueryTablesBuilderList()
       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
       
      repeated .google.cloud.aiplatform.v1.ModelDeploymentMonitoringBigQueryTable bigquery_tables = 10 [(.google.api.field_behavior) = OUTPUT_ONLY];
    • hasLogTtl

      public boolean hasLogTtl()
       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.
       
      .google.protobuf.Duration log_ttl = 17;
      Specified by:
      hasLogTtl in interface ModelDeploymentMonitoringJobOrBuilder
      Returns:
      Whether the logTtl field is set.
    • getLogTtl

      public com.google.protobuf.Duration 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.
       
      .google.protobuf.Duration log_ttl = 17;
      Specified by:
      getLogTtl in interface ModelDeploymentMonitoringJobOrBuilder
      Returns:
      The logTtl.
    • setLogTtl

      public ModelDeploymentMonitoringJob.Builder setLogTtl(com.google.protobuf.Duration value)
       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.
       
      .google.protobuf.Duration log_ttl = 17;
    • setLogTtl

      public ModelDeploymentMonitoringJob.Builder setLogTtl(com.google.protobuf.Duration.Builder builderForValue)
       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.
       
      .google.protobuf.Duration log_ttl = 17;
    • mergeLogTtl

      public ModelDeploymentMonitoringJob.Builder mergeLogTtl(com.google.protobuf.Duration value)
       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.
       
      .google.protobuf.Duration log_ttl = 17;
    • clearLogTtl

       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.
       
      .google.protobuf.Duration log_ttl = 17;
    • getLogTtlBuilder

      public com.google.protobuf.Duration.Builder getLogTtlBuilder()
       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.
       
      .google.protobuf.Duration log_ttl = 17;
    • getLogTtlOrBuilder

      public com.google.protobuf.DurationOrBuilder getLogTtlOrBuilder()
       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.
       
      .google.protobuf.Duration log_ttl = 17;
      Specified by:
      getLogTtlOrBuilder in interface ModelDeploymentMonitoringJobOrBuilder
    • getLabelsCount

      public int getLabelsCount()
      Description copied from interface: ModelDeploymentMonitoringJobOrBuilder
       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.
       
      map<string, string> labels = 11;
      Specified by:
      getLabelsCount in interface ModelDeploymentMonitoringJobOrBuilder
    • containsLabels

      public boolean containsLabels(String key)
       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.
       
      map<string, string> labels = 11;
      Specified by:
      containsLabels in interface ModelDeploymentMonitoringJobOrBuilder
    • getLabels

      @Deprecated public Map<String,String> getLabels()
      Deprecated.
      Use getLabelsMap() instead.
      Specified by:
      getLabels in interface ModelDeploymentMonitoringJobOrBuilder
    • getLabelsMap

      public Map<String,String> getLabelsMap()
       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.
       
      map<string, string> labels = 11;
      Specified by:
      getLabelsMap in interface ModelDeploymentMonitoringJobOrBuilder
    • getLabelsOrDefault

      public String getLabelsOrDefault(String key, String defaultValue)
       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.
       
      map<string, string> labels = 11;
      Specified by:
      getLabelsOrDefault in interface ModelDeploymentMonitoringJobOrBuilder
    • getLabelsOrThrow

      public String getLabelsOrThrow(String key)
       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.
       
      map<string, string> labels = 11;
      Specified by:
      getLabelsOrThrow in interface ModelDeploymentMonitoringJobOrBuilder
    • clearLabels

    • removeLabels

      public ModelDeploymentMonitoringJob.Builder removeLabels(String key)
       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.
       
      map<string, string> labels = 11;
    • getMutableLabels

      @Deprecated public Map<String,String> getMutableLabels()
      Deprecated.
      Use alternate mutation accessors instead.
    • putLabels

      public ModelDeploymentMonitoringJob.Builder putLabels(String key, String value)
       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.
       
      map<string, string> labels = 11;
    • putAllLabels

      public ModelDeploymentMonitoringJob.Builder putAllLabels(Map<String,String> values)
       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.
       
      map<string, string> labels = 11;
    • hasCreateTime

      public boolean hasCreateTime()
       Output only. Timestamp when this ModelDeploymentMonitoringJob was created.
       
      .google.protobuf.Timestamp create_time = 12 [(.google.api.field_behavior) = OUTPUT_ONLY];
      Specified by:
      hasCreateTime in interface ModelDeploymentMonitoringJobOrBuilder
      Returns:
      Whether the createTime field is set.
    • getCreateTime

      public com.google.protobuf.Timestamp getCreateTime()
       Output only. Timestamp when this ModelDeploymentMonitoringJob was created.
       
      .google.protobuf.Timestamp create_time = 12 [(.google.api.field_behavior) = OUTPUT_ONLY];
      Specified by:
      getCreateTime in interface ModelDeploymentMonitoringJobOrBuilder
      Returns:
      The createTime.
    • setCreateTime

      public ModelDeploymentMonitoringJob.Builder setCreateTime(com.google.protobuf.Timestamp value)
       Output only. Timestamp when this ModelDeploymentMonitoringJob was created.
       
      .google.protobuf.Timestamp create_time = 12 [(.google.api.field_behavior) = OUTPUT_ONLY];
    • setCreateTime

      public ModelDeploymentMonitoringJob.Builder setCreateTime(com.google.protobuf.Timestamp.Builder builderForValue)
       Output only. Timestamp when this ModelDeploymentMonitoringJob was created.
       
      .google.protobuf.Timestamp create_time = 12 [(.google.api.field_behavior) = OUTPUT_ONLY];
    • mergeCreateTime

      public ModelDeploymentMonitoringJob.Builder mergeCreateTime(com.google.protobuf.Timestamp value)
       Output only. Timestamp when this ModelDeploymentMonitoringJob was created.
       
      .google.protobuf.Timestamp create_time = 12 [(.google.api.field_behavior) = OUTPUT_ONLY];
    • clearCreateTime

      public ModelDeploymentMonitoringJob.Builder clearCreateTime()
       Output only. Timestamp when this ModelDeploymentMonitoringJob was created.
       
      .google.protobuf.Timestamp create_time = 12 [(.google.api.field_behavior) = OUTPUT_ONLY];
    • getCreateTimeBuilder

      public com.google.protobuf.Timestamp.Builder getCreateTimeBuilder()
       Output only. Timestamp when this ModelDeploymentMonitoringJob was created.
       
      .google.protobuf.Timestamp create_time = 12 [(.google.api.field_behavior) = OUTPUT_ONLY];
    • getCreateTimeOrBuilder

      public com.google.protobuf.TimestampOrBuilder getCreateTimeOrBuilder()
       Output only. Timestamp when this ModelDeploymentMonitoringJob was created.
       
      .google.protobuf.Timestamp create_time = 12 [(.google.api.field_behavior) = OUTPUT_ONLY];
      Specified by:
      getCreateTimeOrBuilder in interface ModelDeploymentMonitoringJobOrBuilder
    • hasUpdateTime

      public boolean hasUpdateTime()
       Output only. Timestamp when this ModelDeploymentMonitoringJob was updated
       most recently.
       
      .google.protobuf.Timestamp update_time = 13 [(.google.api.field_behavior) = OUTPUT_ONLY];
      Specified by:
      hasUpdateTime in interface ModelDeploymentMonitoringJobOrBuilder
      Returns:
      Whether the updateTime field is set.
    • getUpdateTime

      public com.google.protobuf.Timestamp getUpdateTime()
       Output only. Timestamp when this ModelDeploymentMonitoringJob was updated
       most recently.
       
      .google.protobuf.Timestamp update_time = 13 [(.google.api.field_behavior) = OUTPUT_ONLY];
      Specified by:
      getUpdateTime in interface ModelDeploymentMonitoringJobOrBuilder
      Returns:
      The updateTime.
    • setUpdateTime

      public ModelDeploymentMonitoringJob.Builder setUpdateTime(com.google.protobuf.Timestamp value)
       Output only. Timestamp when this ModelDeploymentMonitoringJob was updated
       most recently.
       
      .google.protobuf.Timestamp update_time = 13 [(.google.api.field_behavior) = OUTPUT_ONLY];
    • setUpdateTime

      public ModelDeploymentMonitoringJob.Builder setUpdateTime(com.google.protobuf.Timestamp.Builder builderForValue)
       Output only. Timestamp when this ModelDeploymentMonitoringJob was updated
       most recently.
       
      .google.protobuf.Timestamp update_time = 13 [(.google.api.field_behavior) = OUTPUT_ONLY];
    • mergeUpdateTime

      public ModelDeploymentMonitoringJob.Builder mergeUpdateTime(com.google.protobuf.Timestamp value)
       Output only. Timestamp when this ModelDeploymentMonitoringJob was updated
       most recently.
       
      .google.protobuf.Timestamp update_time = 13 [(.google.api.field_behavior) = OUTPUT_ONLY];
    • clearUpdateTime

      public ModelDeploymentMonitoringJob.Builder clearUpdateTime()
       Output only. Timestamp when this ModelDeploymentMonitoringJob was updated
       most recently.
       
      .google.protobuf.Timestamp update_time = 13 [(.google.api.field_behavior) = OUTPUT_ONLY];
    • getUpdateTimeBuilder

      public com.google.protobuf.Timestamp.Builder getUpdateTimeBuilder()
       Output only. Timestamp when this ModelDeploymentMonitoringJob was updated
       most recently.
       
      .google.protobuf.Timestamp update_time = 13 [(.google.api.field_behavior) = OUTPUT_ONLY];
    • getUpdateTimeOrBuilder

      public com.google.protobuf.TimestampOrBuilder getUpdateTimeOrBuilder()
       Output only. Timestamp when this ModelDeploymentMonitoringJob was updated
       most recently.
       
      .google.protobuf.Timestamp update_time = 13 [(.google.api.field_behavior) = OUTPUT_ONLY];
      Specified by:
      getUpdateTimeOrBuilder in interface ModelDeploymentMonitoringJobOrBuilder
    • hasNextScheduleTime

      public boolean hasNextScheduleTime()
       Output only. Timestamp when this monitoring pipeline will be scheduled to
       run for the next round.
       
      .google.protobuf.Timestamp next_schedule_time = 14 [(.google.api.field_behavior) = OUTPUT_ONLY];
      Specified by:
      hasNextScheduleTime in interface ModelDeploymentMonitoringJobOrBuilder
      Returns:
      Whether the nextScheduleTime field is set.
    • getNextScheduleTime

      public com.google.protobuf.Timestamp getNextScheduleTime()
       Output only. Timestamp when this monitoring pipeline will be scheduled to
       run for the next round.
       
      .google.protobuf.Timestamp next_schedule_time = 14 [(.google.api.field_behavior) = OUTPUT_ONLY];
      Specified by:
      getNextScheduleTime in interface ModelDeploymentMonitoringJobOrBuilder
      Returns:
      The nextScheduleTime.
    • setNextScheduleTime

      public ModelDeploymentMonitoringJob.Builder setNextScheduleTime(com.google.protobuf.Timestamp value)
       Output only. Timestamp when this monitoring pipeline will be scheduled to
       run for the next round.
       
      .google.protobuf.Timestamp next_schedule_time = 14 [(.google.api.field_behavior) = OUTPUT_ONLY];
    • setNextScheduleTime

      public ModelDeploymentMonitoringJob.Builder setNextScheduleTime(com.google.protobuf.Timestamp.Builder builderForValue)
       Output only. Timestamp when this monitoring pipeline will be scheduled to
       run for the next round.
       
      .google.protobuf.Timestamp next_schedule_time = 14 [(.google.api.field_behavior) = OUTPUT_ONLY];
    • mergeNextScheduleTime

      public ModelDeploymentMonitoringJob.Builder mergeNextScheduleTime(com.google.protobuf.Timestamp value)
       Output only. Timestamp when this monitoring pipeline will be scheduled to
       run for the next round.
       
      .google.protobuf.Timestamp next_schedule_time = 14 [(.google.api.field_behavior) = OUTPUT_ONLY];
    • clearNextScheduleTime

      public ModelDeploymentMonitoringJob.Builder clearNextScheduleTime()
       Output only. Timestamp when this monitoring pipeline will be scheduled to
       run for the next round.
       
      .google.protobuf.Timestamp next_schedule_time = 14 [(.google.api.field_behavior) = OUTPUT_ONLY];
    • getNextScheduleTimeBuilder

      public com.google.protobuf.Timestamp.Builder getNextScheduleTimeBuilder()
       Output only. Timestamp when this monitoring pipeline will be scheduled to
       run for the next round.
       
      .google.protobuf.Timestamp next_schedule_time = 14 [(.google.api.field_behavior) = OUTPUT_ONLY];
    • getNextScheduleTimeOrBuilder

      public com.google.protobuf.TimestampOrBuilder getNextScheduleTimeOrBuilder()
       Output only. Timestamp when this monitoring pipeline will be scheduled to
       run for the next round.
       
      .google.protobuf.Timestamp next_schedule_time = 14 [(.google.api.field_behavior) = OUTPUT_ONLY];
      Specified by:
      getNextScheduleTimeOrBuilder in interface ModelDeploymentMonitoringJobOrBuilder
    • hasStatsAnomaliesBaseDirectory

      public boolean hasStatsAnomaliesBaseDirectory()
       Stats anomalies base folder path.
       
      .google.cloud.aiplatform.v1.GcsDestination stats_anomalies_base_directory = 20;
      Specified by:
      hasStatsAnomaliesBaseDirectory in interface ModelDeploymentMonitoringJobOrBuilder
      Returns:
      Whether the statsAnomaliesBaseDirectory field is set.
    • getStatsAnomaliesBaseDirectory

      public GcsDestination getStatsAnomaliesBaseDirectory()
       Stats anomalies base folder path.
       
      .google.cloud.aiplatform.v1.GcsDestination stats_anomalies_base_directory = 20;
      Specified by:
      getStatsAnomaliesBaseDirectory in interface ModelDeploymentMonitoringJobOrBuilder
      Returns:
      The statsAnomaliesBaseDirectory.
    • setStatsAnomaliesBaseDirectory

      public ModelDeploymentMonitoringJob.Builder setStatsAnomaliesBaseDirectory(GcsDestination value)
       Stats anomalies base folder path.
       
      .google.cloud.aiplatform.v1.GcsDestination stats_anomalies_base_directory = 20;
    • setStatsAnomaliesBaseDirectory

      public ModelDeploymentMonitoringJob.Builder setStatsAnomaliesBaseDirectory(GcsDestination.Builder builderForValue)
       Stats anomalies base folder path.
       
      .google.cloud.aiplatform.v1.GcsDestination stats_anomalies_base_directory = 20;
    • mergeStatsAnomaliesBaseDirectory

      public ModelDeploymentMonitoringJob.Builder mergeStatsAnomaliesBaseDirectory(GcsDestination value)
       Stats anomalies base folder path.
       
      .google.cloud.aiplatform.v1.GcsDestination stats_anomalies_base_directory = 20;
    • clearStatsAnomaliesBaseDirectory

      public ModelDeploymentMonitoringJob.Builder clearStatsAnomaliesBaseDirectory()
       Stats anomalies base folder path.
       
      .google.cloud.aiplatform.v1.GcsDestination stats_anomalies_base_directory = 20;
    • getStatsAnomaliesBaseDirectoryBuilder

      public GcsDestination.Builder getStatsAnomaliesBaseDirectoryBuilder()
       Stats anomalies base folder path.
       
      .google.cloud.aiplatform.v1.GcsDestination stats_anomalies_base_directory = 20;
    • getStatsAnomaliesBaseDirectoryOrBuilder

      public GcsDestinationOrBuilder getStatsAnomaliesBaseDirectoryOrBuilder()
       Stats anomalies base folder path.
       
      .google.cloud.aiplatform.v1.GcsDestination stats_anomalies_base_directory = 20;
      Specified by:
      getStatsAnomaliesBaseDirectoryOrBuilder in interface ModelDeploymentMonitoringJobOrBuilder
    • hasEncryptionSpec

      public boolean hasEncryptionSpec()
       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.
       
      .google.cloud.aiplatform.v1.EncryptionSpec encryption_spec = 21;
      Specified by:
      hasEncryptionSpec in interface ModelDeploymentMonitoringJobOrBuilder
      Returns:
      Whether the encryptionSpec field is set.
    • getEncryptionSpec

      public EncryptionSpec 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.
       
      .google.cloud.aiplatform.v1.EncryptionSpec encryption_spec = 21;
      Specified by:
      getEncryptionSpec in interface ModelDeploymentMonitoringJobOrBuilder
      Returns:
      The encryptionSpec.
    • setEncryptionSpec

      public ModelDeploymentMonitoringJob.Builder setEncryptionSpec(EncryptionSpec value)
       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.
       
      .google.cloud.aiplatform.v1.EncryptionSpec encryption_spec = 21;
    • setEncryptionSpec

      public ModelDeploymentMonitoringJob.Builder setEncryptionSpec(EncryptionSpec.Builder builderForValue)
       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.
       
      .google.cloud.aiplatform.v1.EncryptionSpec encryption_spec = 21;
    • mergeEncryptionSpec

      public ModelDeploymentMonitoringJob.Builder mergeEncryptionSpec(EncryptionSpec value)
       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.
       
      .google.cloud.aiplatform.v1.EncryptionSpec encryption_spec = 21;
    • clearEncryptionSpec

      public ModelDeploymentMonitoringJob.Builder clearEncryptionSpec()
       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.
       
      .google.cloud.aiplatform.v1.EncryptionSpec encryption_spec = 21;
    • getEncryptionSpecBuilder

      public EncryptionSpec.Builder getEncryptionSpecBuilder()
       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.
       
      .google.cloud.aiplatform.v1.EncryptionSpec encryption_spec = 21;
    • getEncryptionSpecOrBuilder

      public EncryptionSpecOrBuilder getEncryptionSpecOrBuilder()
       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.
       
      .google.cloud.aiplatform.v1.EncryptionSpec encryption_spec = 21;
      Specified by:
      getEncryptionSpecOrBuilder in interface ModelDeploymentMonitoringJobOrBuilder
    • getEnableMonitoringPipelineLogs

      public boolean 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](https://cloud.google.com/logging#pricing).
       
      bool enable_monitoring_pipeline_logs = 22;
      Specified by:
      getEnableMonitoringPipelineLogs in interface ModelDeploymentMonitoringJobOrBuilder
      Returns:
      The enableMonitoringPipelineLogs.
    • setEnableMonitoringPipelineLogs

      public ModelDeploymentMonitoringJob.Builder setEnableMonitoringPipelineLogs(boolean value)
       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](https://cloud.google.com/logging#pricing).
       
      bool enable_monitoring_pipeline_logs = 22;
      Parameters:
      value - The enableMonitoringPipelineLogs to set.
      Returns:
      This builder for chaining.
    • clearEnableMonitoringPipelineLogs

      public ModelDeploymentMonitoringJob.Builder clearEnableMonitoringPipelineLogs()
       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](https://cloud.google.com/logging#pricing).
       
      bool enable_monitoring_pipeline_logs = 22;
      Returns:
      This builder for chaining.
    • hasError

      public boolean hasError()
       Output only. Only populated when the job's state is `JOB_STATE_FAILED` or
       `JOB_STATE_CANCELLED`.
       
      .google.rpc.Status error = 23 [(.google.api.field_behavior) = OUTPUT_ONLY];
      Specified by:
      hasError in interface ModelDeploymentMonitoringJobOrBuilder
      Returns:
      Whether the error field is set.
    • getError

      public Status getError()
       Output only. Only populated when the job's state is `JOB_STATE_FAILED` or
       `JOB_STATE_CANCELLED`.
       
      .google.rpc.Status error = 23 [(.google.api.field_behavior) = OUTPUT_ONLY];
      Specified by:
      getError in interface ModelDeploymentMonitoringJobOrBuilder
      Returns:
      The error.
    • setError

       Output only. Only populated when the job's state is `JOB_STATE_FAILED` or
       `JOB_STATE_CANCELLED`.
       
      .google.rpc.Status error = 23 [(.google.api.field_behavior) = OUTPUT_ONLY];
    • setError

      public ModelDeploymentMonitoringJob.Builder setError(Status.Builder builderForValue)
       Output only. Only populated when the job's state is `JOB_STATE_FAILED` or
       `JOB_STATE_CANCELLED`.
       
      .google.rpc.Status error = 23 [(.google.api.field_behavior) = OUTPUT_ONLY];
    • mergeError

      public ModelDeploymentMonitoringJob.Builder mergeError(Status value)
       Output only. Only populated when the job's state is `JOB_STATE_FAILED` or
       `JOB_STATE_CANCELLED`.
       
      .google.rpc.Status error = 23 [(.google.api.field_behavior) = OUTPUT_ONLY];
    • clearError

       Output only. Only populated when the job's state is `JOB_STATE_FAILED` or
       `JOB_STATE_CANCELLED`.
       
      .google.rpc.Status error = 23 [(.google.api.field_behavior) = OUTPUT_ONLY];
    • getErrorBuilder

      public Status.Builder getErrorBuilder()
       Output only. Only populated when the job's state is `JOB_STATE_FAILED` or
       `JOB_STATE_CANCELLED`.
       
      .google.rpc.Status error = 23 [(.google.api.field_behavior) = OUTPUT_ONLY];
    • getErrorOrBuilder

      public StatusOrBuilder getErrorOrBuilder()
       Output only. Only populated when the job's state is `JOB_STATE_FAILED` or
       `JOB_STATE_CANCELLED`.
       
      .google.rpc.Status error = 23 [(.google.api.field_behavior) = OUTPUT_ONLY];
      Specified by:
      getErrorOrBuilder in interface ModelDeploymentMonitoringJobOrBuilder
    • getSatisfiesPzs

      public boolean getSatisfiesPzs()
       Output only. Reserved for future use.
       
      bool satisfies_pzs = 26 [(.google.api.field_behavior) = OUTPUT_ONLY];
      Specified by:
      getSatisfiesPzs in interface ModelDeploymentMonitoringJobOrBuilder
      Returns:
      The satisfiesPzs.
    • setSatisfiesPzs

      public ModelDeploymentMonitoringJob.Builder setSatisfiesPzs(boolean value)
       Output only. Reserved for future use.
       
      bool satisfies_pzs = 26 [(.google.api.field_behavior) = OUTPUT_ONLY];
      Parameters:
      value - The satisfiesPzs to set.
      Returns:
      This builder for chaining.
    • clearSatisfiesPzs

      public ModelDeploymentMonitoringJob.Builder clearSatisfiesPzs()
       Output only. Reserved for future use.
       
      bool satisfies_pzs = 26 [(.google.api.field_behavior) = OUTPUT_ONLY];
      Returns:
      This builder for chaining.
    • getSatisfiesPzi

      public boolean getSatisfiesPzi()
       Output only. Reserved for future use.
       
      bool satisfies_pzi = 27 [(.google.api.field_behavior) = OUTPUT_ONLY];
      Specified by:
      getSatisfiesPzi in interface ModelDeploymentMonitoringJobOrBuilder
      Returns:
      The satisfiesPzi.
    • setSatisfiesPzi

      public ModelDeploymentMonitoringJob.Builder setSatisfiesPzi(boolean value)
       Output only. Reserved for future use.
       
      bool satisfies_pzi = 27 [(.google.api.field_behavior) = OUTPUT_ONLY];
      Parameters:
      value - The satisfiesPzi to set.
      Returns:
      This builder for chaining.
    • clearSatisfiesPzi

      public ModelDeploymentMonitoringJob.Builder clearSatisfiesPzi()
       Output only. Reserved for future use.
       
      bool satisfies_pzi = 27 [(.google.api.field_behavior) = OUTPUT_ONLY];
      Returns:
      This builder for chaining.