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aws-native.sagemaker.MonitoringSchedule
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We recommend new projects start with resources from the AWS provider.
Resource Type definition for AWS::SageMaker::MonitoringSchedule
Create MonitoringSchedule Resource
Resources are created with functions called constructors. To learn more about declaring and configuring resources, see Resources.
Constructor syntax
new MonitoringSchedule(name: string, args: MonitoringScheduleArgs, opts?: CustomResourceOptions);
@overload
def MonitoringSchedule(resource_name: str,
args: MonitoringScheduleArgs,
opts: Optional[ResourceOptions] = None)
@overload
def MonitoringSchedule(resource_name: str,
opts: Optional[ResourceOptions] = None,
monitoring_schedule_config: Optional[MonitoringScheduleConfigArgs] = None,
endpoint_name: Optional[str] = None,
failure_reason: Optional[str] = None,
last_monitoring_execution_summary: Optional[MonitoringScheduleMonitoringExecutionSummaryArgs] = None,
monitoring_schedule_name: Optional[str] = None,
monitoring_schedule_status: Optional[MonitoringScheduleStatus] = None,
tags: Optional[Sequence[_root_inputs.TagArgs]] = None)
func NewMonitoringSchedule(ctx *Context, name string, args MonitoringScheduleArgs, opts ...ResourceOption) (*MonitoringSchedule, error)
public MonitoringSchedule(string name, MonitoringScheduleArgs args, CustomResourceOptions? opts = null)
public MonitoringSchedule(String name, MonitoringScheduleArgs args)
public MonitoringSchedule(String name, MonitoringScheduleArgs args, CustomResourceOptions options)
type: aws-native:sagemaker:MonitoringSchedule
properties: # The arguments to resource properties.
options: # Bag of options to control resource's behavior.
Parameters
- name string
- The unique name of the resource.
- args MonitoringScheduleArgs
- The arguments to resource properties.
- opts CustomResourceOptions
- Bag of options to control resource's behavior.
- resource_name str
- The unique name of the resource.
- args MonitoringScheduleArgs
- The arguments to resource properties.
- opts ResourceOptions
- Bag of options to control resource's behavior.
- ctx Context
- Context object for the current deployment.
- name string
- The unique name of the resource.
- args MonitoringScheduleArgs
- The arguments to resource properties.
- opts ResourceOption
- Bag of options to control resource's behavior.
- name string
- The unique name of the resource.
- args MonitoringScheduleArgs
- The arguments to resource properties.
- opts CustomResourceOptions
- Bag of options to control resource's behavior.
- name String
- The unique name of the resource.
- args MonitoringScheduleArgs
- The arguments to resource properties.
- options CustomResourceOptions
- Bag of options to control resource's behavior.
MonitoringSchedule Resource Properties
To learn more about resource properties and how to use them, see Inputs and Outputs in the Architecture and Concepts docs.
Inputs
In Python, inputs that are objects can be passed either as argument classes or as dictionary literals.
The MonitoringSchedule resource accepts the following input properties:
- Monitoring
Schedule Pulumi.Config Aws Native. Sage Maker. Inputs. Monitoring Schedule Config - The configuration object that specifies the monitoring schedule and defines the monitoring job.
- Endpoint
Name string - The name of the endpoint using the monitoring schedule.
- Failure
Reason string - Contains the reason a monitoring job failed, if it failed.
- Last
Monitoring Pulumi.Execution Summary Aws Native. Sage Maker. Inputs. Monitoring Schedule Monitoring Execution Summary - Describes metadata on the last execution to run, if there was one.
- Monitoring
Schedule stringName - The name of the monitoring schedule.
- Monitoring
Schedule Pulumi.Status Aws Native. Sage Maker. Monitoring Schedule Status - The status of a schedule job.
- List<Pulumi.
Aws Native. Inputs. Tag> - An array of key-value pairs to apply to this resource.
- Monitoring
Schedule MonitoringConfig Schedule Config Args - The configuration object that specifies the monitoring schedule and defines the monitoring job.
- Endpoint
Name string - The name of the endpoint using the monitoring schedule.
- Failure
Reason string - Contains the reason a monitoring job failed, if it failed.
- Last
Monitoring MonitoringExecution Summary Schedule Monitoring Execution Summary Args - Describes metadata on the last execution to run, if there was one.
- Monitoring
Schedule stringName - The name of the monitoring schedule.
- Monitoring
Schedule MonitoringStatus Schedule Status - The status of a schedule job.
- Tag
Args - An array of key-value pairs to apply to this resource.
- monitoring
Schedule MonitoringConfig Schedule Config - The configuration object that specifies the monitoring schedule and defines the monitoring job.
- endpoint
Name String - The name of the endpoint using the monitoring schedule.
- failure
Reason String - Contains the reason a monitoring job failed, if it failed.
- last
Monitoring MonitoringExecution Summary Schedule Monitoring Execution Summary - Describes metadata on the last execution to run, if there was one.
- monitoring
Schedule StringName - The name of the monitoring schedule.
- monitoring
Schedule MonitoringStatus Schedule Status - The status of a schedule job.
- List<Tag>
- An array of key-value pairs to apply to this resource.
- monitoring
Schedule MonitoringConfig Schedule Config - The configuration object that specifies the monitoring schedule and defines the monitoring job.
- endpoint
Name string - The name of the endpoint using the monitoring schedule.
- failure
Reason string - Contains the reason a monitoring job failed, if it failed.
- last
Monitoring MonitoringExecution Summary Schedule Monitoring Execution Summary - Describes metadata on the last execution to run, if there was one.
- monitoring
Schedule stringName - The name of the monitoring schedule.
- monitoring
Schedule MonitoringStatus Schedule Status - The status of a schedule job.
- Tag[]
- An array of key-value pairs to apply to this resource.
- monitoring_
schedule_ Monitoringconfig Schedule Config Args - The configuration object that specifies the monitoring schedule and defines the monitoring job.
- endpoint_
name str - The name of the endpoint using the monitoring schedule.
- failure_
reason str - Contains the reason a monitoring job failed, if it failed.
- last_
monitoring_ Monitoringexecution_ summary Schedule Monitoring Execution Summary Args - Describes metadata on the last execution to run, if there was one.
- monitoring_
schedule_ strname - The name of the monitoring schedule.
- monitoring_
schedule_ Monitoringstatus Schedule Status - The status of a schedule job.
- Sequence[Tag
Args] - An array of key-value pairs to apply to this resource.
- monitoring
Schedule Property MapConfig - The configuration object that specifies the monitoring schedule and defines the monitoring job.
- endpoint
Name String - The name of the endpoint using the monitoring schedule.
- failure
Reason String - Contains the reason a monitoring job failed, if it failed.
- last
Monitoring Property MapExecution Summary - Describes metadata on the last execution to run, if there was one.
- monitoring
Schedule StringName - The name of the monitoring schedule.
- monitoring
Schedule "Pending" | "Failed" | "Scheduled" | "Stopped"Status - The status of a schedule job.
- List<Property Map>
- An array of key-value pairs to apply to this resource.
Outputs
All input properties are implicitly available as output properties. Additionally, the MonitoringSchedule resource produces the following output properties:
- Creation
Time string - The time at which the schedule was created.
- Id string
- The provider-assigned unique ID for this managed resource.
- Last
Modified stringTime - A timestamp that indicates the last time the monitoring job was modified.
- Monitoring
Schedule stringArn - The Amazon Resource Name (ARN) of the monitoring schedule.
- Creation
Time string - The time at which the schedule was created.
- Id string
- The provider-assigned unique ID for this managed resource.
- Last
Modified stringTime - A timestamp that indicates the last time the monitoring job was modified.
- Monitoring
Schedule stringArn - The Amazon Resource Name (ARN) of the monitoring schedule.
- creation
Time String - The time at which the schedule was created.
- id String
- The provider-assigned unique ID for this managed resource.
- last
Modified StringTime - A timestamp that indicates the last time the monitoring job was modified.
- monitoring
Schedule StringArn - The Amazon Resource Name (ARN) of the monitoring schedule.
- creation
Time string - The time at which the schedule was created.
- id string
- The provider-assigned unique ID for this managed resource.
- last
Modified stringTime - A timestamp that indicates the last time the monitoring job was modified.
- monitoring
Schedule stringArn - The Amazon Resource Name (ARN) of the monitoring schedule.
- creation_
time str - The time at which the schedule was created.
- id str
- The provider-assigned unique ID for this managed resource.
- last_
modified_ strtime - A timestamp that indicates the last time the monitoring job was modified.
- monitoring_
schedule_ strarn - The Amazon Resource Name (ARN) of the monitoring schedule.
- creation
Time String - The time at which the schedule was created.
- id String
- The provider-assigned unique ID for this managed resource.
- last
Modified StringTime - A timestamp that indicates the last time the monitoring job was modified.
- monitoring
Schedule StringArn - The Amazon Resource Name (ARN) of the monitoring schedule.
Supporting Types
MonitoringScheduleBaselineConfig, MonitoringScheduleBaselineConfigArgs
- Constraints
Resource Pulumi.Aws Native. Sage Maker. Inputs. Monitoring Schedule Constraints Resource - The Amazon S3 URI for the constraints resource.
- Statistics
Resource Pulumi.Aws Native. Sage Maker. Inputs. Monitoring Schedule Statistics Resource - The baseline statistics file in Amazon S3 that the current monitoring job should be validated against.
- Constraints
Resource MonitoringSchedule Constraints Resource - The Amazon S3 URI for the constraints resource.
- Statistics
Resource MonitoringSchedule Statistics Resource - The baseline statistics file in Amazon S3 that the current monitoring job should be validated against.
- constraints
Resource MonitoringSchedule Constraints Resource - The Amazon S3 URI for the constraints resource.
- statistics
Resource MonitoringSchedule Statistics Resource - The baseline statistics file in Amazon S3 that the current monitoring job should be validated against.
- constraints
Resource MonitoringSchedule Constraints Resource - The Amazon S3 URI for the constraints resource.
- statistics
Resource MonitoringSchedule Statistics Resource - The baseline statistics file in Amazon S3 that the current monitoring job should be validated against.
- constraints_
resource MonitoringSchedule Constraints Resource - The Amazon S3 URI for the constraints resource.
- statistics_
resource MonitoringSchedule Statistics Resource - The baseline statistics file in Amazon S3 that the current monitoring job should be validated against.
- constraints
Resource Property Map - The Amazon S3 URI for the constraints resource.
- statistics
Resource Property Map - The baseline statistics file in Amazon S3 that the current monitoring job should be validated against.
MonitoringScheduleBatchTransformInput, MonitoringScheduleBatchTransformInputArgs
- Data
Captured stringDestination S3Uri - A URI that identifies the Amazon S3 storage location where Batch Transform Job captures data.
- Dataset
Format Pulumi.Aws Native. Sage Maker. Inputs. Monitoring Schedule Dataset Format - Local
Path string - Path to the filesystem where the endpoint data is available to the container.
- Exclude
Features stringAttribute - Indexes or names of the features to be excluded from analysis
- S3Data
Distribution Pulumi.Type Aws Native. Sage Maker. Monitoring Schedule Batch Transform Input S3Data Distribution Type - Whether input data distributed in Amazon S3 is fully replicated or sharded by an S3 key. Defauts to FullyReplicated
- S3Input
Mode Pulumi.Aws Native. Sage Maker. Monitoring Schedule Batch Transform Input S3Input Mode - Whether the Pipe or File is used as the input mode for transfering data for the monitoring job. Pipe mode is recommended for large datasets. File mode is useful for small files that fit in memory. Defaults to File.
- Data
Captured stringDestination S3Uri - A URI that identifies the Amazon S3 storage location where Batch Transform Job captures data.
- Dataset
Format MonitoringSchedule Dataset Format - Local
Path string - Path to the filesystem where the endpoint data is available to the container.
- Exclude
Features stringAttribute - Indexes or names of the features to be excluded from analysis
- S3Data
Distribution MonitoringType Schedule Batch Transform Input S3Data Distribution Type - Whether input data distributed in Amazon S3 is fully replicated or sharded by an S3 key. Defauts to FullyReplicated
- S3Input
Mode MonitoringSchedule Batch Transform Input S3Input Mode - Whether the Pipe or File is used as the input mode for transfering data for the monitoring job. Pipe mode is recommended for large datasets. File mode is useful for small files that fit in memory. Defaults to File.
- data
Captured StringDestination S3Uri - A URI that identifies the Amazon S3 storage location where Batch Transform Job captures data.
- dataset
Format MonitoringSchedule Dataset Format - local
Path String - Path to the filesystem where the endpoint data is available to the container.
- exclude
Features StringAttribute - Indexes or names of the features to be excluded from analysis
- s3Data
Distribution MonitoringType Schedule Batch Transform Input S3Data Distribution Type - Whether input data distributed in Amazon S3 is fully replicated or sharded by an S3 key. Defauts to FullyReplicated
- s3Input
Mode MonitoringSchedule Batch Transform Input S3Input Mode - Whether the Pipe or File is used as the input mode for transfering data for the monitoring job. Pipe mode is recommended for large datasets. File mode is useful for small files that fit in memory. Defaults to File.
- data
Captured stringDestination S3Uri - A URI that identifies the Amazon S3 storage location where Batch Transform Job captures data.
- dataset
Format MonitoringSchedule Dataset Format - local
Path string - Path to the filesystem where the endpoint data is available to the container.
- exclude
Features stringAttribute - Indexes or names of the features to be excluded from analysis
- s3Data
Distribution MonitoringType Schedule Batch Transform Input S3Data Distribution Type - Whether input data distributed in Amazon S3 is fully replicated or sharded by an S3 key. Defauts to FullyReplicated
- s3Input
Mode MonitoringSchedule Batch Transform Input S3Input Mode - Whether the Pipe or File is used as the input mode for transfering data for the monitoring job. Pipe mode is recommended for large datasets. File mode is useful for small files that fit in memory. Defaults to File.
- data_
captured_ strdestination_ s3_ uri - A URI that identifies the Amazon S3 storage location where Batch Transform Job captures data.
- dataset_
format MonitoringSchedule Dataset Format - local_
path str - Path to the filesystem where the endpoint data is available to the container.
- exclude_
features_ strattribute - Indexes or names of the features to be excluded from analysis
- s3_
data_ Monitoringdistribution_ type Schedule Batch Transform Input S3Data Distribution Type - Whether input data distributed in Amazon S3 is fully replicated or sharded by an S3 key. Defauts to FullyReplicated
- s3_
input_ Monitoringmode Schedule Batch Transform Input S3Input Mode - Whether the Pipe or File is used as the input mode for transfering data for the monitoring job. Pipe mode is recommended for large datasets. File mode is useful for small files that fit in memory. Defaults to File.
- data
Captured StringDestination S3Uri - A URI that identifies the Amazon S3 storage location where Batch Transform Job captures data.
- dataset
Format Property Map - local
Path String - Path to the filesystem where the endpoint data is available to the container.
- exclude
Features StringAttribute - Indexes or names of the features to be excluded from analysis
- s3Data
Distribution "FullyType Replicated" | "Sharded By S3Key" - Whether input data distributed in Amazon S3 is fully replicated or sharded by an S3 key. Defauts to FullyReplicated
- s3Input
Mode "Pipe" | "File" - Whether the Pipe or File is used as the input mode for transfering data for the monitoring job. Pipe mode is recommended for large datasets. File mode is useful for small files that fit in memory. Defaults to File.
MonitoringScheduleBatchTransformInputS3DataDistributionType, MonitoringScheduleBatchTransformInputS3DataDistributionTypeArgs
- Fully
Replicated - FullyReplicated
- Sharded
By S3Key - ShardedByS3Key
- Monitoring
Schedule Batch Transform Input S3Data Distribution Type Fully Replicated - FullyReplicated
- Monitoring
Schedule Batch Transform Input S3Data Distribution Type Sharded By S3Key - ShardedByS3Key
- Fully
Replicated - FullyReplicated
- Sharded
By S3Key - ShardedByS3Key
- Fully
Replicated - FullyReplicated
- Sharded
By S3Key - ShardedByS3Key
- FULLY_REPLICATED
- FullyReplicated
- SHARDED_BY_S3_KEY
- ShardedByS3Key
- "Fully
Replicated" - FullyReplicated
- "Sharded
By S3Key" - ShardedByS3Key
MonitoringScheduleBatchTransformInputS3InputMode, MonitoringScheduleBatchTransformInputS3InputModeArgs
- Pipe
- Pipe
- File
- File
- Monitoring
Schedule Batch Transform Input S3Input Mode Pipe - Pipe
- Monitoring
Schedule Batch Transform Input S3Input Mode File - File
- Pipe
- Pipe
- File
- File
- Pipe
- Pipe
- File
- File
- PIPE
- Pipe
- FILE
- File
- "Pipe"
- Pipe
- "File"
- File
MonitoringScheduleClusterConfig, MonitoringScheduleClusterConfigArgs
- Instance
Count int - The number of ML compute instances to use in the model monitoring job. For distributed processing jobs, specify a value greater than 1. The default value is 1.
- Instance
Type string - The ML compute instance type for the processing job.
- Volume
Size intIn Gb - The size of the ML storage volume, in gigabytes, that you want to provision. You must specify sufficient ML storage for your scenario.
- Volume
Kms stringKey Id - The AWS Key Management Service (AWS KMS) key that Amazon SageMaker uses to encrypt data on the storage volume attached to the ML compute instance(s) that run the model monitoring job.
- Instance
Count int - The number of ML compute instances to use in the model monitoring job. For distributed processing jobs, specify a value greater than 1. The default value is 1.
- Instance
Type string - The ML compute instance type for the processing job.
- Volume
Size intIn Gb - The size of the ML storage volume, in gigabytes, that you want to provision. You must specify sufficient ML storage for your scenario.
- Volume
Kms stringKey Id - The AWS Key Management Service (AWS KMS) key that Amazon SageMaker uses to encrypt data on the storage volume attached to the ML compute instance(s) that run the model monitoring job.
- instance
Count Integer - The number of ML compute instances to use in the model monitoring job. For distributed processing jobs, specify a value greater than 1. The default value is 1.
- instance
Type String - The ML compute instance type for the processing job.
- volume
Size IntegerIn Gb - The size of the ML storage volume, in gigabytes, that you want to provision. You must specify sufficient ML storage for your scenario.
- volume
Kms StringKey Id - The AWS Key Management Service (AWS KMS) key that Amazon SageMaker uses to encrypt data on the storage volume attached to the ML compute instance(s) that run the model monitoring job.
- instance
Count number - The number of ML compute instances to use in the model monitoring job. For distributed processing jobs, specify a value greater than 1. The default value is 1.
- instance
Type string - The ML compute instance type for the processing job.
- volume
Size numberIn Gb - The size of the ML storage volume, in gigabytes, that you want to provision. You must specify sufficient ML storage for your scenario.
- volume
Kms stringKey Id - The AWS Key Management Service (AWS KMS) key that Amazon SageMaker uses to encrypt data on the storage volume attached to the ML compute instance(s) that run the model monitoring job.
- instance_
count int - The number of ML compute instances to use in the model monitoring job. For distributed processing jobs, specify a value greater than 1. The default value is 1.
- instance_
type str - The ML compute instance type for the processing job.
- volume_
size_ intin_ gb - The size of the ML storage volume, in gigabytes, that you want to provision. You must specify sufficient ML storage for your scenario.
- volume_
kms_ strkey_ id - The AWS Key Management Service (AWS KMS) key that Amazon SageMaker uses to encrypt data on the storage volume attached to the ML compute instance(s) that run the model monitoring job.
- instance
Count Number - The number of ML compute instances to use in the model monitoring job. For distributed processing jobs, specify a value greater than 1. The default value is 1.
- instance
Type String - The ML compute instance type for the processing job.
- volume
Size NumberIn Gb - The size of the ML storage volume, in gigabytes, that you want to provision. You must specify sufficient ML storage for your scenario.
- volume
Kms StringKey Id - The AWS Key Management Service (AWS KMS) key that Amazon SageMaker uses to encrypt data on the storage volume attached to the ML compute instance(s) that run the model monitoring job.
MonitoringScheduleConfig, MonitoringScheduleConfigArgs
- Monitoring
Job Pulumi.Definition Aws Native. Sage Maker. Inputs. Monitoring Schedule Monitoring Job Definition - Defines the monitoring job.
- Monitoring
Job stringDefinition Name - Name of the job definition
- Monitoring
Type Pulumi.Aws Native. Sage Maker. Monitoring Schedule Monitoring Type - The type of the monitoring job definition to schedule.
- Schedule
Config Pulumi.Aws Native. Sage Maker. Inputs. Monitoring Schedule Schedule Config - Configures the monitoring schedule.
- Monitoring
Job MonitoringDefinition Schedule Monitoring Job Definition - Defines the monitoring job.
- Monitoring
Job stringDefinition Name - Name of the job definition
- Monitoring
Type MonitoringSchedule Monitoring Type - The type of the monitoring job definition to schedule.
- Schedule
Config MonitoringSchedule Schedule Config - Configures the monitoring schedule.
- monitoring
Job MonitoringDefinition Schedule Monitoring Job Definition - Defines the monitoring job.
- monitoring
Job StringDefinition Name - Name of the job definition
- monitoring
Type MonitoringSchedule Monitoring Type - The type of the monitoring job definition to schedule.
- schedule
Config MonitoringSchedule Schedule Config - Configures the monitoring schedule.
- monitoring
Job MonitoringDefinition Schedule Monitoring Job Definition - Defines the monitoring job.
- monitoring
Job stringDefinition Name - Name of the job definition
- monitoring
Type MonitoringSchedule Monitoring Type - The type of the monitoring job definition to schedule.
- schedule
Config MonitoringSchedule Schedule Config - Configures the monitoring schedule.
- monitoring_
job_ Monitoringdefinition Schedule Monitoring Job Definition - Defines the monitoring job.
- monitoring_
job_ strdefinition_ name - Name of the job definition
- monitoring_
type MonitoringSchedule Monitoring Type - The type of the monitoring job definition to schedule.
- schedule_
config MonitoringSchedule Schedule Config - Configures the monitoring schedule.
- monitoring
Job Property MapDefinition - Defines the monitoring job.
- monitoring
Job StringDefinition Name - Name of the job definition
- monitoring
Type "DataQuality" | "Model Quality" | "Model Bias" | "Model Explainability" - The type of the monitoring job definition to schedule.
- schedule
Config Property Map - Configures the monitoring schedule.
MonitoringScheduleConstraintsResource, MonitoringScheduleConstraintsResourceArgs
- S3Uri string
- The Amazon S3 URI for baseline constraint file in Amazon S3 that the current monitoring job should validated against.
- S3Uri string
- The Amazon S3 URI for baseline constraint file in Amazon S3 that the current monitoring job should validated against.
- s3Uri String
- The Amazon S3 URI for baseline constraint file in Amazon S3 that the current monitoring job should validated against.
- s3Uri string
- The Amazon S3 URI for baseline constraint file in Amazon S3 that the current monitoring job should validated against.
- s3_
uri str - The Amazon S3 URI for baseline constraint file in Amazon S3 that the current monitoring job should validated against.
- s3Uri String
- The Amazon S3 URI for baseline constraint file in Amazon S3 that the current monitoring job should validated against.
MonitoringScheduleCsv, MonitoringScheduleCsvArgs
- Header bool
- A boolean flag indicating if given CSV has header
- Header bool
- A boolean flag indicating if given CSV has header
- header Boolean
- A boolean flag indicating if given CSV has header
- header boolean
- A boolean flag indicating if given CSV has header
- header bool
- A boolean flag indicating if given CSV has header
- header Boolean
- A boolean flag indicating if given CSV has header
MonitoringScheduleDatasetFormat, MonitoringScheduleDatasetFormatArgs
- csv Property Map
- json Property Map
- parquet Boolean
MonitoringScheduleEndpointInput, MonitoringScheduleEndpointInputArgs
- Endpoint
Name string - Local
Path string - Path to the filesystem where the endpoint data is available to the container.
- Exclude
Features stringAttribute - Indexes or names of the features to be excluded from analysis
- S3Data
Distribution Pulumi.Type Aws Native. Sage Maker. Monitoring Schedule Endpoint Input S3Data Distribution Type - Whether input data distributed in Amazon S3 is fully replicated or sharded by an S3 key. Defauts to FullyReplicated
- S3Input
Mode Pulumi.Aws Native. Sage Maker. Monitoring Schedule Endpoint Input S3Input Mode - Whether the Pipe or File is used as the input mode for transfering data for the monitoring job. Pipe mode is recommended for large datasets. File mode is useful for small files that fit in memory. Defaults to File.
- Endpoint
Name string - Local
Path string - Path to the filesystem where the endpoint data is available to the container.
- Exclude
Features stringAttribute - Indexes or names of the features to be excluded from analysis
- S3Data
Distribution MonitoringType Schedule Endpoint Input S3Data Distribution Type - Whether input data distributed in Amazon S3 is fully replicated or sharded by an S3 key. Defauts to FullyReplicated
- S3Input
Mode MonitoringSchedule Endpoint Input S3Input Mode - Whether the Pipe or File is used as the input mode for transfering data for the monitoring job. Pipe mode is recommended for large datasets. File mode is useful for small files that fit in memory. Defaults to File.
- endpoint
Name String - local
Path String - Path to the filesystem where the endpoint data is available to the container.
- exclude
Features StringAttribute - Indexes or names of the features to be excluded from analysis
- s3Data
Distribution MonitoringType Schedule Endpoint Input S3Data Distribution Type - Whether input data distributed in Amazon S3 is fully replicated or sharded by an S3 key. Defauts to FullyReplicated
- s3Input
Mode MonitoringSchedule Endpoint Input S3Input Mode - Whether the Pipe or File is used as the input mode for transfering data for the monitoring job. Pipe mode is recommended for large datasets. File mode is useful for small files that fit in memory. Defaults to File.
- endpoint
Name string - local
Path string - Path to the filesystem where the endpoint data is available to the container.
- exclude
Features stringAttribute - Indexes or names of the features to be excluded from analysis
- s3Data
Distribution MonitoringType Schedule Endpoint Input S3Data Distribution Type - Whether input data distributed in Amazon S3 is fully replicated or sharded by an S3 key. Defauts to FullyReplicated
- s3Input
Mode MonitoringSchedule Endpoint Input S3Input Mode - Whether the Pipe or File is used as the input mode for transfering data for the monitoring job. Pipe mode is recommended for large datasets. File mode is useful for small files that fit in memory. Defaults to File.
- endpoint_
name str - local_
path str - Path to the filesystem where the endpoint data is available to the container.
- exclude_
features_ strattribute - Indexes or names of the features to be excluded from analysis
- s3_
data_ Monitoringdistribution_ type Schedule Endpoint Input S3Data Distribution Type - Whether input data distributed in Amazon S3 is fully replicated or sharded by an S3 key. Defauts to FullyReplicated
- s3_
input_ Monitoringmode Schedule Endpoint Input S3Input Mode - Whether the Pipe or File is used as the input mode for transfering data for the monitoring job. Pipe mode is recommended for large datasets. File mode is useful for small files that fit in memory. Defaults to File.
- endpoint
Name String - local
Path String - Path to the filesystem where the endpoint data is available to the container.
- exclude
Features StringAttribute - Indexes or names of the features to be excluded from analysis
- s3Data
Distribution "FullyType Replicated" | "Sharded By S3Key" - Whether input data distributed in Amazon S3 is fully replicated or sharded by an S3 key. Defauts to FullyReplicated
- s3Input
Mode "Pipe" | "File" - Whether the Pipe or File is used as the input mode for transfering data for the monitoring job. Pipe mode is recommended for large datasets. File mode is useful for small files that fit in memory. Defaults to File.
MonitoringScheduleEndpointInputS3DataDistributionType, MonitoringScheduleEndpointInputS3DataDistributionTypeArgs
- Fully
Replicated - FullyReplicated
- Sharded
By S3Key - ShardedByS3Key
- Monitoring
Schedule Endpoint Input S3Data Distribution Type Fully Replicated - FullyReplicated
- Monitoring
Schedule Endpoint Input S3Data Distribution Type Sharded By S3Key - ShardedByS3Key
- Fully
Replicated - FullyReplicated
- Sharded
By S3Key - ShardedByS3Key
- Fully
Replicated - FullyReplicated
- Sharded
By S3Key - ShardedByS3Key
- FULLY_REPLICATED
- FullyReplicated
- SHARDED_BY_S3_KEY
- ShardedByS3Key
- "Fully
Replicated" - FullyReplicated
- "Sharded
By S3Key" - ShardedByS3Key
MonitoringScheduleEndpointInputS3InputMode, MonitoringScheduleEndpointInputS3InputModeArgs
- Pipe
- Pipe
- File
- File
- Monitoring
Schedule Endpoint Input S3Input Mode Pipe - Pipe
- Monitoring
Schedule Endpoint Input S3Input Mode File - File
- Pipe
- Pipe
- File
- File
- Pipe
- Pipe
- File
- File
- PIPE
- Pipe
- FILE
- File
- "Pipe"
- Pipe
- "File"
- File
MonitoringScheduleJson, MonitoringScheduleJsonArgs
- Line bool
- A boolean flag indicating if it is JSON line format
- Line bool
- A boolean flag indicating if it is JSON line format
- line Boolean
- A boolean flag indicating if it is JSON line format
- line boolean
- A boolean flag indicating if it is JSON line format
- line bool
- A boolean flag indicating if it is JSON line format
- line Boolean
- A boolean flag indicating if it is JSON line format
MonitoringScheduleMonitoringAppSpecification, MonitoringScheduleMonitoringAppSpecificationArgs
- Image
Uri string - The container image to be run by the monitoring job.
- Container
Arguments List<string> - An array of arguments for the container used to run the monitoring job.
- Container
Entrypoint List<string> - Specifies the entrypoint for a container used to run the monitoring job.
- Post
Analytics stringProcessor Source Uri - An Amazon S3 URI to a script that is called after analysis has been performed. Applicable only for the built-in (first party) containers.
- Record
Preprocessor stringSource Uri - An Amazon S3 URI to a script that is called per row prior to running analysis. It can base64 decode the payload and convert it into a flatted json so that the built-in container can use the converted data. Applicable only for the built-in (first party) containers
- Image
Uri string - The container image to be run by the monitoring job.
- Container
Arguments []string - An array of arguments for the container used to run the monitoring job.
- Container
Entrypoint []string - Specifies the entrypoint for a container used to run the monitoring job.
- Post
Analytics stringProcessor Source Uri - An Amazon S3 URI to a script that is called after analysis has been performed. Applicable only for the built-in (first party) containers.
- Record
Preprocessor stringSource Uri - An Amazon S3 URI to a script that is called per row prior to running analysis. It can base64 decode the payload and convert it into a flatted json so that the built-in container can use the converted data. Applicable only for the built-in (first party) containers
- image
Uri String - The container image to be run by the monitoring job.
- container
Arguments List<String> - An array of arguments for the container used to run the monitoring job.
- container
Entrypoint List<String> - Specifies the entrypoint for a container used to run the monitoring job.
- post
Analytics StringProcessor Source Uri - An Amazon S3 URI to a script that is called after analysis has been performed. Applicable only for the built-in (first party) containers.
- record
Preprocessor StringSource Uri - An Amazon S3 URI to a script that is called per row prior to running analysis. It can base64 decode the payload and convert it into a flatted json so that the built-in container can use the converted data. Applicable only for the built-in (first party) containers
- image
Uri string - The container image to be run by the monitoring job.
- container
Arguments string[] - An array of arguments for the container used to run the monitoring job.
- container
Entrypoint string[] - Specifies the entrypoint for a container used to run the monitoring job.
- post
Analytics stringProcessor Source Uri - An Amazon S3 URI to a script that is called after analysis has been performed. Applicable only for the built-in (first party) containers.
- record
Preprocessor stringSource Uri - An Amazon S3 URI to a script that is called per row prior to running analysis. It can base64 decode the payload and convert it into a flatted json so that the built-in container can use the converted data. Applicable only for the built-in (first party) containers
- image_
uri str - The container image to be run by the monitoring job.
- container_
arguments Sequence[str] - An array of arguments for the container used to run the monitoring job.
- container_
entrypoint Sequence[str] - Specifies the entrypoint for a container used to run the monitoring job.
- post_
analytics_ strprocessor_ source_ uri - An Amazon S3 URI to a script that is called after analysis has been performed. Applicable only for the built-in (first party) containers.
- record_
preprocessor_ strsource_ uri - An Amazon S3 URI to a script that is called per row prior to running analysis. It can base64 decode the payload and convert it into a flatted json so that the built-in container can use the converted data. Applicable only for the built-in (first party) containers
- image
Uri String - The container image to be run by the monitoring job.
- container
Arguments List<String> - An array of arguments for the container used to run the monitoring job.
- container
Entrypoint List<String> - Specifies the entrypoint for a container used to run the monitoring job.
- post
Analytics StringProcessor Source Uri - An Amazon S3 URI to a script that is called after analysis has been performed. Applicable only for the built-in (first party) containers.
- record
Preprocessor StringSource Uri - An Amazon S3 URI to a script that is called per row prior to running analysis. It can base64 decode the payload and convert it into a flatted json so that the built-in container can use the converted data. Applicable only for the built-in (first party) containers
MonitoringScheduleMonitoringExecutionSummary, MonitoringScheduleMonitoringExecutionSummaryArgs
- Creation
Time string - The time at which the monitoring job was created.
- Last
Modified stringTime - A timestamp that indicates the last time the monitoring job was modified.
- Monitoring
Execution Pulumi.Status Aws Native. Sage Maker. Monitoring Schedule Monitoring Execution Summary Monitoring Execution Status - The status of the monitoring job.
- Monitoring
Schedule stringName - The name of the monitoring schedule.
- Scheduled
Time string - The time the monitoring job was scheduled.
- Endpoint
Name string - The name of the endpoint used to run the monitoring job.
- Failure
Reason string - Contains the reason a monitoring job failed, if it failed.
- Processing
Job stringArn - The Amazon Resource Name (ARN) of the monitoring job.
- Creation
Time string - The time at which the monitoring job was created.
- Last
Modified stringTime - A timestamp that indicates the last time the monitoring job was modified.
- Monitoring
Execution MonitoringStatus Schedule Monitoring Execution Summary Monitoring Execution Status - The status of the monitoring job.
- Monitoring
Schedule stringName - The name of the monitoring schedule.
- Scheduled
Time string - The time the monitoring job was scheduled.
- Endpoint
Name string - The name of the endpoint used to run the monitoring job.
- Failure
Reason string - Contains the reason a monitoring job failed, if it failed.
- Processing
Job stringArn - The Amazon Resource Name (ARN) of the monitoring job.
- creation
Time String - The time at which the monitoring job was created.
- last
Modified StringTime - A timestamp that indicates the last time the monitoring job was modified.
- monitoring
Execution MonitoringStatus Schedule Monitoring Execution Summary Monitoring Execution Status - The status of the monitoring job.
- monitoring
Schedule StringName - The name of the monitoring schedule.
- scheduled
Time String - The time the monitoring job was scheduled.
- endpoint
Name String - The name of the endpoint used to run the monitoring job.
- failure
Reason String - Contains the reason a monitoring job failed, if it failed.
- processing
Job StringArn - The Amazon Resource Name (ARN) of the monitoring job.
- creation
Time string - The time at which the monitoring job was created.
- last
Modified stringTime - A timestamp that indicates the last time the monitoring job was modified.
- monitoring
Execution MonitoringStatus Schedule Monitoring Execution Summary Monitoring Execution Status - The status of the monitoring job.
- monitoring
Schedule stringName - The name of the monitoring schedule.
- scheduled
Time string - The time the monitoring job was scheduled.
- endpoint
Name string - The name of the endpoint used to run the monitoring job.
- failure
Reason string - Contains the reason a monitoring job failed, if it failed.
- processing
Job stringArn - The Amazon Resource Name (ARN) of the monitoring job.
- creation_
time str - The time at which the monitoring job was created.
- last_
modified_ strtime - A timestamp that indicates the last time the monitoring job was modified.
- monitoring_
execution_ Monitoringstatus Schedule Monitoring Execution Summary Monitoring Execution Status - The status of the monitoring job.
- monitoring_
schedule_ strname - The name of the monitoring schedule.
- scheduled_
time str - The time the monitoring job was scheduled.
- endpoint_
name str - The name of the endpoint used to run the monitoring job.
- failure_
reason str - Contains the reason a monitoring job failed, if it failed.
- processing_
job_ strarn - The Amazon Resource Name (ARN) of the monitoring job.
- creation
Time String - The time at which the monitoring job was created.
- last
Modified StringTime - A timestamp that indicates the last time the monitoring job was modified.
- monitoring
Execution "Pending" | "Completed" | "CompletedStatus With Violations" | "In Progress" | "Failed" | "Stopping" | "Stopped" - The status of the monitoring job.
- monitoring
Schedule StringName - The name of the monitoring schedule.
- scheduled
Time String - The time the monitoring job was scheduled.
- endpoint
Name String - The name of the endpoint used to run the monitoring job.
- failure
Reason String - Contains the reason a monitoring job failed, if it failed.
- processing
Job StringArn - The Amazon Resource Name (ARN) of the monitoring job.
MonitoringScheduleMonitoringExecutionSummaryMonitoringExecutionStatus, MonitoringScheduleMonitoringExecutionSummaryMonitoringExecutionStatusArgs
- Pending
- Pending
- Completed
- Completed
- Completed
With Violations - CompletedWithViolations
- In
Progress - InProgress
- Failed
- Failed
- Stopping
- Stopping
- Stopped
- Stopped
- Monitoring
Schedule Monitoring Execution Summary Monitoring Execution Status Pending - Pending
- Monitoring
Schedule Monitoring Execution Summary Monitoring Execution Status Completed - Completed
- Monitoring
Schedule Monitoring Execution Summary Monitoring Execution Status Completed With Violations - CompletedWithViolations
- Monitoring
Schedule Monitoring Execution Summary Monitoring Execution Status In Progress - InProgress
- Monitoring
Schedule Monitoring Execution Summary Monitoring Execution Status Failed - Failed
- Monitoring
Schedule Monitoring Execution Summary Monitoring Execution Status Stopping - Stopping
- Monitoring
Schedule Monitoring Execution Summary Monitoring Execution Status Stopped - Stopped
- Pending
- Pending
- Completed
- Completed
- Completed
With Violations - CompletedWithViolations
- In
Progress - InProgress
- Failed
- Failed
- Stopping
- Stopping
- Stopped
- Stopped
- Pending
- Pending
- Completed
- Completed
- Completed
With Violations - CompletedWithViolations
- In
Progress - InProgress
- Failed
- Failed
- Stopping
- Stopping
- Stopped
- Stopped
- PENDING
- Pending
- COMPLETED
- Completed
- COMPLETED_WITH_VIOLATIONS
- CompletedWithViolations
- IN_PROGRESS
- InProgress
- FAILED
- Failed
- STOPPING
- Stopping
- STOPPED
- Stopped
- "Pending"
- Pending
- "Completed"
- Completed
- "Completed
With Violations" - CompletedWithViolations
- "In
Progress" - InProgress
- "Failed"
- Failed
- "Stopping"
- Stopping
- "Stopped"
- Stopped
MonitoringScheduleMonitoringInput, MonitoringScheduleMonitoringInputArgs
MonitoringScheduleMonitoringJobDefinition, MonitoringScheduleMonitoringJobDefinitionArgs
- Monitoring
App Pulumi.Specification Aws Native. Sage Maker. Inputs. Monitoring Schedule Monitoring App Specification - Configures the monitoring job to run a specified Docker container image.
- Monitoring
Inputs List<Pulumi.Aws Native. Sage Maker. Inputs. Monitoring Schedule Monitoring Input> - The array of inputs for the monitoring job. Currently we support monitoring an Amazon SageMaker Endpoint.
- Monitoring
Output Pulumi.Config Aws Native. Sage Maker. Inputs. Monitoring Schedule Monitoring Output Config - The array of outputs from the monitoring job to be uploaded to Amazon S3.
- Monitoring
Resources Pulumi.Aws Native. Sage Maker. Inputs. Monitoring Schedule Monitoring Resources - 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.
- Role
Arn string - The Amazon Resource Name (ARN) of an IAM role that Amazon SageMaker can assume to perform tasks on your behalf.
- Baseline
Config Pulumi.Aws Native. Sage Maker. Inputs. Monitoring Schedule Baseline Config - Baseline configuration used to validate that the data conforms to the specified constraints and statistics
- Environment object
- Sets the environment variables in the Docker container
- Network
Config Pulumi.Aws Native. Sage Maker. Inputs. Monitoring Schedule Network Config - Specifies networking options for an monitoring job.
- Stopping
Condition Pulumi.Aws Native. Sage Maker. Inputs. Monitoring Schedule Stopping Condition - Specifies a time limit for how long the monitoring job is allowed to run.
- Monitoring
App MonitoringSpecification Schedule Monitoring App Specification - Configures the monitoring job to run a specified Docker container image.
- Monitoring
Inputs []MonitoringSchedule Monitoring Input - The array of inputs for the monitoring job. Currently we support monitoring an Amazon SageMaker Endpoint.
- Monitoring
Output MonitoringConfig Schedule Monitoring Output Config - The array of outputs from the monitoring job to be uploaded to Amazon S3.
- Monitoring
Resources MonitoringSchedule Monitoring Resources - 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.
- Role
Arn string - The Amazon Resource Name (ARN) of an IAM role that Amazon SageMaker can assume to perform tasks on your behalf.
- Baseline
Config MonitoringSchedule Baseline Config - Baseline configuration used to validate that the data conforms to the specified constraints and statistics
- Environment interface{}
- Sets the environment variables in the Docker container
- Network
Config MonitoringSchedule Network Config - Specifies networking options for an monitoring job.
- Stopping
Condition MonitoringSchedule Stopping Condition - Specifies a time limit for how long the monitoring job is allowed to run.
- monitoring
App MonitoringSpecification Schedule Monitoring App Specification - Configures the monitoring job to run a specified Docker container image.
- monitoring
Inputs List<MonitoringSchedule Monitoring Input> - The array of inputs for the monitoring job. Currently we support monitoring an Amazon SageMaker Endpoint.
- monitoring
Output MonitoringConfig Schedule Monitoring Output Config - The array of outputs from the monitoring job to be uploaded to Amazon S3.
- monitoring
Resources MonitoringSchedule Monitoring Resources - 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.
- role
Arn String - The Amazon Resource Name (ARN) of an IAM role that Amazon SageMaker can assume to perform tasks on your behalf.
- baseline
Config MonitoringSchedule Baseline Config - Baseline configuration used to validate that the data conforms to the specified constraints and statistics
- environment Object
- Sets the environment variables in the Docker container
- network
Config MonitoringSchedule Network Config - Specifies networking options for an monitoring job.
- stopping
Condition MonitoringSchedule Stopping Condition - Specifies a time limit for how long the monitoring job is allowed to run.
- monitoring
App MonitoringSpecification Schedule Monitoring App Specification - Configures the monitoring job to run a specified Docker container image.
- monitoring
Inputs MonitoringSchedule Monitoring Input[] - The array of inputs for the monitoring job. Currently we support monitoring an Amazon SageMaker Endpoint.
- monitoring
Output MonitoringConfig Schedule Monitoring Output Config - The array of outputs from the monitoring job to be uploaded to Amazon S3.
- monitoring
Resources MonitoringSchedule Monitoring Resources - 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.
- role
Arn string - The Amazon Resource Name (ARN) of an IAM role that Amazon SageMaker can assume to perform tasks on your behalf.
- baseline
Config MonitoringSchedule Baseline Config - Baseline configuration used to validate that the data conforms to the specified constraints and statistics
- environment any
- Sets the environment variables in the Docker container
- network
Config MonitoringSchedule Network Config - Specifies networking options for an monitoring job.
- stopping
Condition MonitoringSchedule Stopping Condition - Specifies a time limit for how long the monitoring job is allowed to run.
- monitoring_
app_ Monitoringspecification Schedule Monitoring App Specification - Configures the monitoring job to run a specified Docker container image.
- monitoring_
inputs Sequence[MonitoringSchedule Monitoring Input] - The array of inputs for the monitoring job. Currently we support monitoring an Amazon SageMaker Endpoint.
- monitoring_
output_ Monitoringconfig Schedule Monitoring Output Config - The array of outputs from the monitoring job to be uploaded to Amazon S3.
- monitoring_
resources MonitoringSchedule Monitoring Resources - 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.
- role_
arn str - The Amazon Resource Name (ARN) of an IAM role that Amazon SageMaker can assume to perform tasks on your behalf.
- baseline_
config MonitoringSchedule Baseline Config - Baseline configuration used to validate that the data conforms to the specified constraints and statistics
- environment Any
- Sets the environment variables in the Docker container
- network_
config MonitoringSchedule Network Config - Specifies networking options for an monitoring job.
- stopping_
condition MonitoringSchedule Stopping Condition - Specifies a time limit for how long the monitoring job is allowed to run.
- monitoring
App Property MapSpecification - Configures the monitoring job to run a specified Docker container image.
- monitoring
Inputs List<Property Map> - The array of inputs for the monitoring job. Currently we support monitoring an Amazon SageMaker Endpoint.
- monitoring
Output Property MapConfig - The array of outputs from the monitoring job to be uploaded to Amazon S3.
- monitoring
Resources Property Map - 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.
- role
Arn String - The Amazon Resource Name (ARN) of an IAM role that Amazon SageMaker can assume to perform tasks on your behalf.
- baseline
Config Property Map - Baseline configuration used to validate that the data conforms to the specified constraints and statistics
- environment Any
- Sets the environment variables in the Docker container
- network
Config Property Map - Specifies networking options for an monitoring job.
- stopping
Condition Property Map - Specifies a time limit for how long the monitoring job is allowed to run.
MonitoringScheduleMonitoringOutput, MonitoringScheduleMonitoringOutputArgs
- S3Output
Pulumi.
Aws Native. Sage Maker. Inputs. Monitoring Schedule S3Output - The Amazon S3 storage location where the results of a monitoring job are saved.
- S3Output
Monitoring
Schedule S3Output - The Amazon S3 storage location where the results of a monitoring job are saved.
- s3Output
Monitoring
Schedule S3Output - The Amazon S3 storage location where the results of a monitoring job are saved.
- s3Output
Monitoring
Schedule S3Output - The Amazon S3 storage location where the results of a monitoring job are saved.
- s3_
output MonitoringSchedule S3Output - The Amazon S3 storage location where the results of a monitoring job are saved.
- s3Output Property Map
- The Amazon S3 storage location where the results of a monitoring job are saved.
MonitoringScheduleMonitoringOutputConfig, MonitoringScheduleMonitoringOutputConfigArgs
- Monitoring
Outputs List<Pulumi.Aws Native. Sage Maker. Inputs. Monitoring Schedule Monitoring Output> - Monitoring outputs for monitoring jobs. This is where the output of the periodic monitoring jobs is uploaded.
- Kms
Key stringId - The AWS Key Management Service (AWS KMS) key that Amazon SageMaker uses to encrypt the model artifacts at rest using Amazon S3 server-side encryption.
- Monitoring
Outputs []MonitoringSchedule Monitoring Output - Monitoring outputs for monitoring jobs. This is where the output of the periodic monitoring jobs is uploaded.
- Kms
Key stringId - The AWS Key Management Service (AWS KMS) key that Amazon SageMaker uses to encrypt the model artifacts at rest using Amazon S3 server-side encryption.
- monitoring
Outputs List<MonitoringSchedule Monitoring Output> - Monitoring outputs for monitoring jobs. This is where the output of the periodic monitoring jobs is uploaded.
- kms
Key StringId - The AWS Key Management Service (AWS KMS) key that Amazon SageMaker uses to encrypt the model artifacts at rest using Amazon S3 server-side encryption.
- monitoring
Outputs MonitoringSchedule Monitoring Output[] - Monitoring outputs for monitoring jobs. This is where the output of the periodic monitoring jobs is uploaded.
- kms
Key stringId - The AWS Key Management Service (AWS KMS) key that Amazon SageMaker uses to encrypt the model artifacts at rest using Amazon S3 server-side encryption.
- monitoring_
outputs Sequence[MonitoringSchedule Monitoring Output] - Monitoring outputs for monitoring jobs. This is where the output of the periodic monitoring jobs is uploaded.
- kms_
key_ strid - The AWS Key Management Service (AWS KMS) key that Amazon SageMaker uses to encrypt the model artifacts at rest using Amazon S3 server-side encryption.
- monitoring
Outputs List<Property Map> - Monitoring outputs for monitoring jobs. This is where the output of the periodic monitoring jobs is uploaded.
- kms
Key StringId - The AWS Key Management Service (AWS KMS) key that Amazon SageMaker uses to encrypt the model artifacts at rest using Amazon S3 server-side encryption.
MonitoringScheduleMonitoringResources, MonitoringScheduleMonitoringResourcesArgs
- Cluster
Config Pulumi.Aws Native. Sage Maker. Inputs. Monitoring Schedule Cluster Config - The configuration for the cluster resources used to run the processing job.
- Cluster
Config MonitoringSchedule Cluster Config - The configuration for the cluster resources used to run the processing job.
- cluster
Config MonitoringSchedule Cluster Config - The configuration for the cluster resources used to run the processing job.
- cluster
Config MonitoringSchedule Cluster Config - The configuration for the cluster resources used to run the processing job.
- cluster_
config MonitoringSchedule Cluster Config - The configuration for the cluster resources used to run the processing job.
- cluster
Config Property Map - The configuration for the cluster resources used to run the processing job.
MonitoringScheduleMonitoringType, MonitoringScheduleMonitoringTypeArgs
- Data
Quality - DataQuality
- Model
Quality - ModelQuality
- Model
Bias - ModelBias
- Model
Explainability - ModelExplainability
- Monitoring
Schedule Monitoring Type Data Quality - DataQuality
- Monitoring
Schedule Monitoring Type Model Quality - ModelQuality
- Monitoring
Schedule Monitoring Type Model Bias - ModelBias
- Monitoring
Schedule Monitoring Type Model Explainability - ModelExplainability
- Data
Quality - DataQuality
- Model
Quality - ModelQuality
- Model
Bias - ModelBias
- Model
Explainability - ModelExplainability
- Data
Quality - DataQuality
- Model
Quality - ModelQuality
- Model
Bias - ModelBias
- Model
Explainability - ModelExplainability
- DATA_QUALITY
- DataQuality
- MODEL_QUALITY
- ModelQuality
- MODEL_BIAS
- ModelBias
- MODEL_EXPLAINABILITY
- ModelExplainability
- "Data
Quality" - DataQuality
- "Model
Quality" - ModelQuality
- "Model
Bias" - ModelBias
- "Model
Explainability" - ModelExplainability
MonitoringScheduleNetworkConfig, MonitoringScheduleNetworkConfigArgs
- Enable
Inter boolContainer Traffic Encryption - Whether to encrypt all communications between distributed processing jobs. Choose True to encrypt communications. Encryption provides greater security for distributed processing jobs, but the processing might take longer.
- Enable
Network boolIsolation - Whether to allow inbound and outbound network calls to and from the containers used for the processing job.
- Vpc
Config Pulumi.Aws Native. Sage Maker. Inputs. Monitoring Schedule Vpc Config - Specifies a VPC that your training jobs and hosted models have access to. Control access to and from your training and model containers by configuring the VPC. For more information, see Protect Endpoints by Using an Amazon Virtual Private Cloud and Protect Training Jobs by Using an Amazon Virtual Private Cloud .
- Enable
Inter boolContainer Traffic Encryption - Whether to encrypt all communications between distributed processing jobs. Choose True to encrypt communications. Encryption provides greater security for distributed processing jobs, but the processing might take longer.
- Enable
Network boolIsolation - Whether to allow inbound and outbound network calls to and from the containers used for the processing job.
- Vpc
Config MonitoringSchedule Vpc Config - Specifies a VPC that your training jobs and hosted models have access to. Control access to and from your training and model containers by configuring the VPC. For more information, see Protect Endpoints by Using an Amazon Virtual Private Cloud and Protect Training Jobs by Using an Amazon Virtual Private Cloud .
- enable
Inter BooleanContainer Traffic Encryption - Whether to encrypt all communications between distributed processing jobs. Choose True to encrypt communications. Encryption provides greater security for distributed processing jobs, but the processing might take longer.
- enable
Network BooleanIsolation - Whether to allow inbound and outbound network calls to and from the containers used for the processing job.
- vpc
Config MonitoringSchedule Vpc Config - Specifies a VPC that your training jobs and hosted models have access to. Control access to and from your training and model containers by configuring the VPC. For more information, see Protect Endpoints by Using an Amazon Virtual Private Cloud and Protect Training Jobs by Using an Amazon Virtual Private Cloud .
- enable
Inter booleanContainer Traffic Encryption - Whether to encrypt all communications between distributed processing jobs. Choose True to encrypt communications. Encryption provides greater security for distributed processing jobs, but the processing might take longer.
- enable
Network booleanIsolation - Whether to allow inbound and outbound network calls to and from the containers used for the processing job.
- vpc
Config MonitoringSchedule Vpc Config - Specifies a VPC that your training jobs and hosted models have access to. Control access to and from your training and model containers by configuring the VPC. For more information, see Protect Endpoints by Using an Amazon Virtual Private Cloud and Protect Training Jobs by Using an Amazon Virtual Private Cloud .
- enable_
inter_ boolcontainer_ traffic_ encryption - Whether to encrypt all communications between distributed processing jobs. Choose True to encrypt communications. Encryption provides greater security for distributed processing jobs, but the processing might take longer.
- enable_
network_ boolisolation - Whether to allow inbound and outbound network calls to and from the containers used for the processing job.
- vpc_
config MonitoringSchedule Vpc Config - Specifies a VPC that your training jobs and hosted models have access to. Control access to and from your training and model containers by configuring the VPC. For more information, see Protect Endpoints by Using an Amazon Virtual Private Cloud and Protect Training Jobs by Using an Amazon Virtual Private Cloud .
- enable
Inter BooleanContainer Traffic Encryption - Whether to encrypt all communications between distributed processing jobs. Choose True to encrypt communications. Encryption provides greater security for distributed processing jobs, but the processing might take longer.
- enable
Network BooleanIsolation - Whether to allow inbound and outbound network calls to and from the containers used for the processing job.
- vpc
Config Property Map - Specifies a VPC that your training jobs and hosted models have access to. Control access to and from your training and model containers by configuring the VPC. For more information, see Protect Endpoints by Using an Amazon Virtual Private Cloud and Protect Training Jobs by Using an Amazon Virtual Private Cloud .
MonitoringScheduleS3Output, MonitoringScheduleS3OutputArgs
- Local
Path string - The local path to the Amazon S3 storage location where Amazon SageMaker saves the results of a monitoring job. LocalPath is an absolute path for the output data.
- S3Uri string
- A URI that identifies the Amazon S3 storage location where Amazon SageMaker saves the results of a monitoring job.
- S3Upload
Mode Pulumi.Aws Native. Sage Maker. Monitoring Schedule S3Output S3Upload Mode - Whether to upload the results of the monitoring job continuously or after the job completes.
- Local
Path string - The local path to the Amazon S3 storage location where Amazon SageMaker saves the results of a monitoring job. LocalPath is an absolute path for the output data.
- S3Uri string
- A URI that identifies the Amazon S3 storage location where Amazon SageMaker saves the results of a monitoring job.
- S3Upload
Mode MonitoringSchedule S3Output S3Upload Mode - Whether to upload the results of the monitoring job continuously or after the job completes.
- local
Path String - The local path to the Amazon S3 storage location where Amazon SageMaker saves the results of a monitoring job. LocalPath is an absolute path for the output data.
- s3Uri String
- A URI that identifies the Amazon S3 storage location where Amazon SageMaker saves the results of a monitoring job.
- s3Upload
Mode MonitoringSchedule S3Output S3Upload Mode - Whether to upload the results of the monitoring job continuously or after the job completes.
- local
Path string - The local path to the Amazon S3 storage location where Amazon SageMaker saves the results of a monitoring job. LocalPath is an absolute path for the output data.
- s3Uri string
- A URI that identifies the Amazon S3 storage location where Amazon SageMaker saves the results of a monitoring job.
- s3Upload
Mode MonitoringSchedule S3Output S3Upload Mode - Whether to upload the results of the monitoring job continuously or after the job completes.
- local_
path str - The local path to the Amazon S3 storage location where Amazon SageMaker saves the results of a monitoring job. LocalPath is an absolute path for the output data.
- s3_
uri str - A URI that identifies the Amazon S3 storage location where Amazon SageMaker saves the results of a monitoring job.
- s3_
upload_ Monitoringmode Schedule S3Output S3Upload Mode - Whether to upload the results of the monitoring job continuously or after the job completes.
- local
Path String - The local path to the Amazon S3 storage location where Amazon SageMaker saves the results of a monitoring job. LocalPath is an absolute path for the output data.
- s3Uri String
- A URI that identifies the Amazon S3 storage location where Amazon SageMaker saves the results of a monitoring job.
- s3Upload
Mode "Continuous" | "EndOf Job" - Whether to upload the results of the monitoring job continuously or after the job completes.
MonitoringScheduleS3OutputS3UploadMode, MonitoringScheduleS3OutputS3UploadModeArgs
- Continuous
- Continuous
- End
Of Job - EndOfJob
- Monitoring
Schedule S3Output S3Upload Mode Continuous - Continuous
- Monitoring
Schedule S3Output S3Upload Mode End Of Job - EndOfJob
- Continuous
- Continuous
- End
Of Job - EndOfJob
- Continuous
- Continuous
- End
Of Job - EndOfJob
- CONTINUOUS
- Continuous
- END_OF_JOB
- EndOfJob
- "Continuous"
- Continuous
- "End
Of Job" - EndOfJob
MonitoringScheduleScheduleConfig, MonitoringScheduleScheduleConfigArgs
- Schedule
Expression string - A cron expression or 'NOW' that describes details about the monitoring schedule.
- Data
Analysis stringEnd Time - Data Analysis end time, e.g. PT0H
- Data
Analysis stringStart Time - Data Analysis start time, e.g. -PT1H
- Schedule
Expression string - A cron expression or 'NOW' that describes details about the monitoring schedule.
- Data
Analysis stringEnd Time - Data Analysis end time, e.g. PT0H
- Data
Analysis stringStart Time - Data Analysis start time, e.g. -PT1H
- schedule
Expression String - A cron expression or 'NOW' that describes details about the monitoring schedule.
- data
Analysis StringEnd Time - Data Analysis end time, e.g. PT0H
- data
Analysis StringStart Time - Data Analysis start time, e.g. -PT1H
- schedule
Expression string - A cron expression or 'NOW' that describes details about the monitoring schedule.
- data
Analysis stringEnd Time - Data Analysis end time, e.g. PT0H
- data
Analysis stringStart Time - Data Analysis start time, e.g. -PT1H
- schedule_
expression str - A cron expression or 'NOW' that describes details about the monitoring schedule.
- data_
analysis_ strend_ time - Data Analysis end time, e.g. PT0H
- data_
analysis_ strstart_ time - Data Analysis start time, e.g. -PT1H
- schedule
Expression String - A cron expression or 'NOW' that describes details about the monitoring schedule.
- data
Analysis StringEnd Time - Data Analysis end time, e.g. PT0H
- data
Analysis StringStart Time - Data Analysis start time, e.g. -PT1H
MonitoringScheduleStatisticsResource, MonitoringScheduleStatisticsResourceArgs
- S3Uri string
- The Amazon S3 URI for the baseline statistics file in Amazon S3 that the current monitoring job should be validated against.
- S3Uri string
- The Amazon S3 URI for the baseline statistics file in Amazon S3 that the current monitoring job should be validated against.
- s3Uri String
- The Amazon S3 URI for the baseline statistics file in Amazon S3 that the current monitoring job should be validated against.
- s3Uri string
- The Amazon S3 URI for the baseline statistics file in Amazon S3 that the current monitoring job should be validated against.
- s3_
uri str - The Amazon S3 URI for the baseline statistics file in Amazon S3 that the current monitoring job should be validated against.
- s3Uri String
- The Amazon S3 URI for the baseline statistics file in Amazon S3 that the current monitoring job should be validated against.
MonitoringScheduleStatus, MonitoringScheduleStatusArgs
- Pending
- Pending
- Failed
- Failed
- Scheduled
- Scheduled
- Stopped
- Stopped
- Monitoring
Schedule Status Pending - Pending
- Monitoring
Schedule Status Failed - Failed
- Monitoring
Schedule Status Scheduled - Scheduled
- Monitoring
Schedule Status Stopped - Stopped
- Pending
- Pending
- Failed
- Failed
- Scheduled
- Scheduled
- Stopped
- Stopped
- Pending
- Pending
- Failed
- Failed
- Scheduled
- Scheduled
- Stopped
- Stopped
- PENDING
- Pending
- FAILED
- Failed
- SCHEDULED
- Scheduled
- STOPPED
- Stopped
- "Pending"
- Pending
- "Failed"
- Failed
- "Scheduled"
- Scheduled
- "Stopped"
- Stopped
MonitoringScheduleStoppingCondition, MonitoringScheduleStoppingConditionArgs
- Max
Runtime intIn Seconds - The maximum runtime allowed in seconds.
- Max
Runtime intIn Seconds - The maximum runtime allowed in seconds.
- max
Runtime IntegerIn Seconds - The maximum runtime allowed in seconds.
- max
Runtime numberIn Seconds - The maximum runtime allowed in seconds.
- max_
runtime_ intin_ seconds - The maximum runtime allowed in seconds.
- max
Runtime NumberIn Seconds - The maximum runtime allowed in seconds.
MonitoringScheduleVpcConfig, MonitoringScheduleVpcConfigArgs
- Security
Group List<string>Ids - The VPC security group IDs, in the form sg-xxxxxxxx. Specify the security groups for the VPC that is specified in the Subnets field.
- Subnets List<string>
- The ID of the subnets in the VPC to which you want to connect to your monitoring jobs.
- Security
Group []stringIds - The VPC security group IDs, in the form sg-xxxxxxxx. Specify the security groups for the VPC that is specified in the Subnets field.
- Subnets []string
- The ID of the subnets in the VPC to which you want to connect to your monitoring jobs.
- security
Group List<String>Ids - The VPC security group IDs, in the form sg-xxxxxxxx. Specify the security groups for the VPC that is specified in the Subnets field.
- subnets List<String>
- The ID of the subnets in the VPC to which you want to connect to your monitoring jobs.
- security
Group string[]Ids - The VPC security group IDs, in the form sg-xxxxxxxx. Specify the security groups for the VPC that is specified in the Subnets field.
- subnets string[]
- The ID of the subnets in the VPC to which you want to connect to your monitoring jobs.
- security_
group_ Sequence[str]ids - The VPC security group IDs, in the form sg-xxxxxxxx. Specify the security groups for the VPC that is specified in the Subnets field.
- subnets Sequence[str]
- The ID of the subnets in the VPC to which you want to connect to your monitoring jobs.
- security
Group List<String>Ids - The VPC security group IDs, in the form sg-xxxxxxxx. Specify the security groups for the VPC that is specified in the Subnets field.
- subnets List<String>
- The ID of the subnets in the VPC to which you want to connect to your monitoring jobs.
Tag, TagArgs
Package Details
- Repository
- AWS Native pulumi/pulumi-aws-native
- License
- Apache-2.0
We recommend new projects start with resources from the AWS provider.