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Class: Aws::SageMaker::Types::MonitoringJobDefinition
- Inherits:
-
Struct
- Object
- Struct
- Aws::SageMaker::Types::MonitoringJobDefinition
- Defined in:
- (unknown)
Overview
When passing MonitoringJobDefinition as input to an Aws::Client method, you can use a vanilla Hash:
{
baseline_config: {
constraints_resource: {
s3_uri: "S3Uri",
},
statistics_resource: {
s3_uri: "S3Uri",
},
},
monitoring_inputs: [ # required
{
endpoint_input: { # required
endpoint_name: "EndpointName", # required
local_path: "ProcessingLocalPath", # required
s3_input_mode: "Pipe", # accepts Pipe, File
s3_data_distribution_type: "FullyReplicated", # accepts FullyReplicated, ShardedByS3Key
},
},
],
monitoring_output_config: { # required
monitoring_outputs: [ # required
{
s3_output: { # required
s3_uri: "MonitoringS3Uri", # required
local_path: "ProcessingLocalPath", # required
s3_upload_mode: "Continuous", # accepts Continuous, EndOfJob
},
},
],
kms_key_id: "KmsKeyId",
},
monitoring_resources: { # required
cluster_config: { # required
instance_count: 1, # required
instance_type: "ml.t3.medium", # required, accepts ml.t3.medium, ml.t3.large, ml.t3.xlarge, ml.t3.2xlarge, ml.m4.xlarge, ml.m4.2xlarge, ml.m4.4xlarge, ml.m4.10xlarge, ml.m4.16xlarge, ml.c4.xlarge, ml.c4.2xlarge, ml.c4.4xlarge, ml.c4.8xlarge, ml.p2.xlarge, ml.p2.8xlarge, ml.p2.16xlarge, ml.p3.2xlarge, ml.p3.8xlarge, ml.p3.16xlarge, ml.c5.xlarge, ml.c5.2xlarge, ml.c5.4xlarge, ml.c5.9xlarge, ml.c5.18xlarge, ml.m5.large, ml.m5.xlarge, ml.m5.2xlarge, ml.m5.4xlarge, ml.m5.12xlarge, ml.m5.24xlarge, ml.r5.large, ml.r5.xlarge, ml.r5.2xlarge, ml.r5.4xlarge, ml.r5.8xlarge, ml.r5.12xlarge, ml.r5.16xlarge, ml.r5.24xlarge
volume_size_in_gb: 1, # required
volume_kms_key_id: "KmsKeyId",
},
},
monitoring_app_specification: { # required
image_uri: "ImageUri", # required
container_entrypoint: ["ContainerEntrypointString"],
container_arguments: ["ContainerArgument"],
record_preprocessor_source_uri: "S3Uri",
post_analytics_processor_source_uri: "S3Uri",
},
stopping_condition: {
max_runtime_in_seconds: 1, # required
},
environment: {
"ProcessingEnvironmentKey" => "ProcessingEnvironmentValue",
},
network_config: {
enable_inter_container_traffic_encryption: false,
enable_network_isolation: false,
vpc_config: {
security_group_ids: ["SecurityGroupId"], # required
subnets: ["SubnetId"], # required
},
},
role_arn: "RoleArn", # required
}
Defines the monitoring job.
Returned by:
Instance Attribute Summary collapse
-
#baseline_config ⇒ Types::MonitoringBaselineConfig
Baseline configuration used to validate that the data conforms to the specified constraints and statistics.
-
#environment ⇒ Hash<String,String>
Sets the environment variables in the Docker container.
-
#monitoring_app_specification ⇒ Types::MonitoringAppSpecification
Configures the monitoring job to run a specified Docker container image.
-
#monitoring_inputs ⇒ Array<Types::MonitoringInput>
The array of inputs for the monitoring job.
-
#monitoring_output_config ⇒ Types::MonitoringOutputConfig
The array of outputs from the monitoring job to be uploaded to Amazon Simple Storage Service (Amazon S3).
-
#monitoring_resources ⇒ Types::MonitoringResources
Identifies the resources, ML compute instances, and ML storage volumes to deploy for a monitoring job.
-
#network_config ⇒ Types::NetworkConfig
Specifies networking options for an monitoring job.
-
#role_arn ⇒ String
The Amazon Resource Name (ARN) of an IAM role that Amazon SageMaker can assume to perform tasks on your behalf.
-
#stopping_condition ⇒ Types::MonitoringStoppingCondition
Specifies a time limit for how long the monitoring job is allowed to run.
Instance Attribute Details
#baseline_config ⇒ Types::MonitoringBaselineConfig
Baseline configuration used to validate that the data conforms to the specified constraints and statistics
#environment ⇒ Hash<String,String>
Sets the environment variables in the Docker container.
#monitoring_app_specification ⇒ Types::MonitoringAppSpecification
Configures the monitoring job to run a specified Docker container image.
#monitoring_inputs ⇒ Array<Types::MonitoringInput>
The array of inputs for the monitoring job. Currently we support monitoring an Amazon SageMaker Endpoint.
#monitoring_output_config ⇒ Types::MonitoringOutputConfig
The array of outputs from the monitoring job to be uploaded to Amazon Simple Storage Service (Amazon S3).
#monitoring_resources ⇒ Types::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.
#network_config ⇒ Types::NetworkConfig
Specifies networking options for an monitoring job.
#role_arn ⇒ String
The Amazon Resource Name (ARN) of an IAM role that Amazon SageMaker can assume to perform tasks on your behalf.
#stopping_condition ⇒ Types::MonitoringStoppingCondition
Specifies a time limit for how long the monitoring job is allowed to run.