Struct aws_sdk_sagemaker::model::MonitoringJobDefinition [−][src]
#[non_exhaustive]pub struct MonitoringJobDefinition {
pub baseline_config: Option<MonitoringBaselineConfig>,
pub monitoring_inputs: Option<Vec<MonitoringInput>>,
pub monitoring_output_config: Option<MonitoringOutputConfig>,
pub monitoring_resources: Option<MonitoringResources>,
pub monitoring_app_specification: Option<MonitoringAppSpecification>,
pub stopping_condition: Option<MonitoringStoppingCondition>,
pub environment: Option<HashMap<String, String>>,
pub network_config: Option<NetworkConfig>,
pub role_arn: Option<String>,
}
Expand description
Defines the monitoring job.
Fields (Non-exhaustive)
This struct is marked as non-exhaustive
Struct { .. }
syntax; cannot be matched against without a wildcard ..
; and struct update syntax will not work.baseline_config: Option<MonitoringBaselineConfig>
Baseline configuration used to validate that the data conforms to the specified constraints and statistics
monitoring_inputs: Option<Vec<MonitoringInput>>
The array of inputs for the monitoring job. Currently we support monitoring an Amazon SageMaker Endpoint.
monitoring_output_config: Option<MonitoringOutputConfig>
The array of outputs from the monitoring job to be uploaded to Amazon Simple Storage Service (Amazon S3).
monitoring_resources: Option<MonitoringResources>
Identifies the resources, ML compute instances, and ML storage volumes to deploy for a monitoring job. In distributed processing, you specify more than one instance.
monitoring_app_specification: Option<MonitoringAppSpecification>
Configures the monitoring job to run a specified Docker container image.
stopping_condition: Option<MonitoringStoppingCondition>
Specifies a time limit for how long the monitoring job is allowed to run.
environment: Option<HashMap<String, String>>
Sets the environment variables in the Docker container.
network_config: Option<NetworkConfig>
Specifies networking options for an monitoring job.
role_arn: Option<String>
The Amazon Resource Name (ARN) of an IAM role that Amazon SageMaker can assume to perform tasks on your behalf.
Implementations
Baseline configuration used to validate that the data conforms to the specified constraints and statistics
The array of inputs for the monitoring job. Currently we support monitoring an Amazon SageMaker Endpoint.
The array of outputs from the monitoring job to be uploaded to Amazon Simple Storage Service (Amazon S3).
Identifies the resources, ML compute instances, and ML storage volumes to deploy for a monitoring job. In distributed processing, you specify more than one instance.
Configures the monitoring job to run a specified Docker container image.
Specifies a time limit for how long the monitoring job is allowed to run.
Sets the environment variables in the Docker container.
Specifies networking options for an monitoring job.
Creates a new builder-style object to manufacture MonitoringJobDefinition
Trait Implementations
This method tests for self
and other
values to be equal, and is used
by ==
. Read more
This method tests for !=
.
Auto Trait Implementations
impl RefUnwindSafe for MonitoringJobDefinition
impl Send for MonitoringJobDefinition
impl Sync for MonitoringJobDefinition
impl Unpin for MonitoringJobDefinition
impl UnwindSafe for MonitoringJobDefinition
Blanket Implementations
Mutably borrows from an owned value. Read more
Attaches the provided Subscriber
to this type, returning a
WithDispatch
wrapper. Read more
Attaches the current default Subscriber
to this type, returning a
WithDispatch
wrapper. Read more