Class CreateMlflowTrackingServerRequest
- All Implemented Interfaces:
SdkPojo
,ToCopyableBuilder<CreateMlflowTrackingServerRequest.Builder,
CreateMlflowTrackingServerRequest>
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Nested Class Summary
Nested Classes -
Method Summary
Modifier and TypeMethodDescriptionfinal String
The S3 URI for a general purpose bucket to use as the MLflow Tracking Server artifact store.final Boolean
Whether to enable or disable automatic registration of new MLflow models to the SageMaker Model Registry.builder()
final boolean
final boolean
equalsBySdkFields
(Object obj) Indicates whether some other object is "equal to" this one by SDK fields.final <T> Optional
<T> getValueForField
(String fieldName, Class<T> clazz) Used to retrieve the value of a field from any class that extendsSdkRequest
.final int
hashCode()
final boolean
hasTags()
For responses, this returns true if the service returned a value for the Tags property.final String
The version of MLflow that the tracking server uses.final String
roleArn()
The Amazon Resource Name (ARN) for an IAM role in your account that the MLflow Tracking Server uses to access the artifact store in Amazon S3.static Class
<? extends CreateMlflowTrackingServerRequest.Builder> tags()
Tags consisting of key-value pairs used to manage metadata for the tracking server.Take this object and create a builder that contains all of the current property values of this object.final String
toString()
Returns a string representation of this object.final String
A unique string identifying the tracking server name.final TrackingServerSize
The size of the tracking server you want to create.final String
The size of the tracking server you want to create.final String
The day and time of the week in Coordinated Universal Time (UTC) 24-hour standard time that weekly maintenance updates are scheduled.Methods inherited from class software.amazon.awssdk.awscore.AwsRequest
overrideConfiguration
Methods inherited from interface software.amazon.awssdk.utils.builder.ToCopyableBuilder
copy
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Method Details
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trackingServerName
A unique string identifying the tracking server name. This string is part of the tracking server ARN.
- Returns:
- A unique string identifying the tracking server name. This string is part of the tracking server ARN.
-
artifactStoreUri
The S3 URI for a general purpose bucket to use as the MLflow Tracking Server artifact store.
- Returns:
- The S3 URI for a general purpose bucket to use as the MLflow Tracking Server artifact store.
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trackingServerSize
The size of the tracking server you want to create. You can choose between
"Small"
,"Medium"
, and"Large"
. The default MLflow Tracking Server configuration size is"Small"
. You can choose a size depending on the projected use of the tracking server such as the volume of data logged, number of users, and frequency of use.We recommend using a small tracking server for teams of up to 25 users, a medium tracking server for teams of up to 50 users, and a large tracking server for teams of up to 100 users.
If the service returns an enum value that is not available in the current SDK version,
trackingServerSize
will returnTrackingServerSize.UNKNOWN_TO_SDK_VERSION
. The raw value returned by the service is available fromtrackingServerSizeAsString()
.- Returns:
- The size of the tracking server you want to create. You can choose between
"Small"
,"Medium"
, and"Large"
. The default MLflow Tracking Server configuration size is"Small"
. You can choose a size depending on the projected use of the tracking server such as the volume of data logged, number of users, and frequency of use.We recommend using a small tracking server for teams of up to 25 users, a medium tracking server for teams of up to 50 users, and a large tracking server for teams of up to 100 users.
- See Also:
-
trackingServerSizeAsString
The size of the tracking server you want to create. You can choose between
"Small"
,"Medium"
, and"Large"
. The default MLflow Tracking Server configuration size is"Small"
. You can choose a size depending on the projected use of the tracking server such as the volume of data logged, number of users, and frequency of use.We recommend using a small tracking server for teams of up to 25 users, a medium tracking server for teams of up to 50 users, and a large tracking server for teams of up to 100 users.
If the service returns an enum value that is not available in the current SDK version,
trackingServerSize
will returnTrackingServerSize.UNKNOWN_TO_SDK_VERSION
. The raw value returned by the service is available fromtrackingServerSizeAsString()
.- Returns:
- The size of the tracking server you want to create. You can choose between
"Small"
,"Medium"
, and"Large"
. The default MLflow Tracking Server configuration size is"Small"
. You can choose a size depending on the projected use of the tracking server such as the volume of data logged, number of users, and frequency of use.We recommend using a small tracking server for teams of up to 25 users, a medium tracking server for teams of up to 50 users, and a large tracking server for teams of up to 100 users.
- See Also:
-
mlflowVersion
The version of MLflow that the tracking server uses. To see which MLflow versions are available to use, see How it works.
- Returns:
- The version of MLflow that the tracking server uses. To see which MLflow versions are available to use, see How it works.
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roleArn
The Amazon Resource Name (ARN) for an IAM role in your account that the MLflow Tracking Server uses to access the artifact store in Amazon S3. The role should have
AmazonS3FullAccess
permissions. For more information on IAM permissions for tracking server creation, see Set up IAM permissions for MLflow.- Returns:
- The Amazon Resource Name (ARN) for an IAM role in your account that the MLflow Tracking Server uses to
access the artifact store in Amazon S3. The role should have
AmazonS3FullAccess
permissions. For more information on IAM permissions for tracking server creation, see Set up IAM permissions for MLflow.
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automaticModelRegistration
Whether to enable or disable automatic registration of new MLflow models to the SageMaker Model Registry. To enable automatic model registration, set this value to
True
. To disable automatic model registration, set this value toFalse
. If not specified,AutomaticModelRegistration
defaults toFalse
.- Returns:
- Whether to enable or disable automatic registration of new MLflow models to the SageMaker Model Registry.
To enable automatic model registration, set this value to
True
. To disable automatic model registration, set this value toFalse
. If not specified,AutomaticModelRegistration
defaults toFalse
.
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weeklyMaintenanceWindowStart
The day and time of the week in Coordinated Universal Time (UTC) 24-hour standard time that weekly maintenance updates are scheduled. For example: TUE:03:30.
- Returns:
- The day and time of the week in Coordinated Universal Time (UTC) 24-hour standard time that weekly maintenance updates are scheduled. For example: TUE:03:30.
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hasTags
public final boolean hasTags()For responses, this returns true if the service returned a value for the Tags property. This DOES NOT check that the value is non-empty (for which, you should check theisEmpty()
method on the property). This is useful because the SDK will never return a null collection or map, but you may need to differentiate between the service returning nothing (or null) and the service returning an empty collection or map. For requests, this returns true if a value for the property was specified in the request builder, and false if a value was not specified. -
tags
Tags consisting of key-value pairs used to manage metadata for the tracking server.
Attempts to modify the collection returned by this method will result in an UnsupportedOperationException.
This method will never return null. If you would like to know whether the service returned this field (so that you can differentiate between null and empty), you can use the
hasTags()
method.- Returns:
- Tags consisting of key-value pairs used to manage metadata for the tracking server.
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toBuilder
Description copied from interface:ToCopyableBuilder
Take this object and create a builder that contains all of the current property values of this object.- Specified by:
toBuilder
in interfaceToCopyableBuilder<CreateMlflowTrackingServerRequest.Builder,
CreateMlflowTrackingServerRequest> - Specified by:
toBuilder
in classSageMakerRequest
- Returns:
- a builder for type T
-
builder
-
serializableBuilderClass
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hashCode
public final int hashCode()- Overrides:
hashCode
in classAwsRequest
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equals
- Overrides:
equals
in classAwsRequest
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equalsBySdkFields
Description copied from interface:SdkPojo
Indicates whether some other object is "equal to" this one by SDK fields. An SDK field is a modeled, non-inherited field in anSdkPojo
class, and is generated based on a service model.If an
SdkPojo
class does not have any inherited fields,equalsBySdkFields
andequals
are essentially the same.- Specified by:
equalsBySdkFields
in interfaceSdkPojo
- Parameters:
obj
- the object to be compared with- Returns:
- true if the other object equals to this object by sdk fields, false otherwise.
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toString
Returns a string representation of this object. This is useful for testing and debugging. Sensitive data will be redacted from this string using a placeholder value. -
getValueForField
Description copied from class:SdkRequest
Used to retrieve the value of a field from any class that extendsSdkRequest
. The field name specified should match the member name from the corresponding service-2.json model specified in the codegen-resources folder for a given service. The class specifies what class to cast the returned value to. If the returned value is also a modeled class, theSdkRequest.getValueForField(String, Class)
method will again be available.- Overrides:
getValueForField
in classSdkRequest
- Parameters:
fieldName
- The name of the member to be retrieved.clazz
- The class to cast the returned object to.- Returns:
- Optional containing the casted return value
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sdkFields
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