| Column Name | Column Data Type |
|---|
endpoint_name Required Input Column
Name of the endpoint. | VARCHAR |
_aws_profile Input Column
The AWS profile defines the AWS identity used. It can be defined via credentials or by assuming a IAM role. | STRUCT(
"type" VARCHAR,
"name" VARCHAR,
"account_id" VARCHAR,
"via_profile_name" VARCHAR,
"assumed_role_arn" VARCHAR,
"organization" STRUCT(
"account_name" VARCHAR,
"id" VARCHAR,
"tags" STRUCT(
"key" VARCHAR,
"value" VARCHAR
)[],
"master_account" STRUCT(
"id" VARCHAR,
"email" VARCHAR
),
"parents" STRUCT(
"type" VARCHAR,
"id" VARCHAR,
"name" VARCHAR,
"tags" STRUCT(
"key" VARCHAR,
"value" VARCHAR
)[]
)[]
)
) |
Show child fields- _aws_profile.account_id
The AWS account id - _aws_profile.assumed_role_arn
The ARN of the assumed role - _aws_profile.name
The unique name of the profile. - _aws_profile.organization
Information about this profile's membership in the AWS organization. Show child fields- _aws_profile.organization.account_name
The name of account speciifed by the organization - _aws_profile.organization.id
The organization id - _aws_profile.organization.master_account
Show child fields- _aws_profile.organization.master_account.email
The organization master account email address - _aws_profile.organization.master_account.id
The organization master account id
- _aws_profile.organization.parents[]
Show child fields- _aws_profile.organization.parents[].id
The id of the parent - _aws_profile.organization.parents[].name
The name of the parent - _aws_profile.organization.parents[].tags[]
Show child fields- _aws_profile.organization.parents[].tags[].key
- _aws_profile.organization.parents[].tags[].value
- _aws_profile.organization.parents[].type
The type of parent can be an organization unit or a root
- _aws_profile.organization.tags[]
Show child fields- _aws_profile.organization.tags[].key
- _aws_profile.organization.tags[].value
- _aws_profile.type
The type of profile, either 'credentials' or 'assumed_role' - _aws_profile.via_profile_name
This IAM role for this profile is assumed by first utilizing another profile with this name to obtain credentials.
|
async_inference_config
Returns the description of an endpoint configuration created using the CreateEndpointConfig API. | STRUCT(
"client_config" STRUCT(
"max_concurrent_invocations_per_instance" BIGINT
),
"output_config" STRUCT(
"kms_key_id" VARCHAR,
"s3_output_path" VARCHAR,
"notification_config" STRUCT(
"success_topic" VARCHAR,
"error_topic" VARCHAR,
"include_inference_response_in" VARCHAR[]
),
"s3_failure_path" VARCHAR
)
) |
Show child fields- async_inference_config.client_config
Configures the behavior of the client used by SageMaker to interact with the model container during asynchronous inference. Show child fields- async_inference_config.client_config.max_concurrent_invocations_per_instance
The maximum number of concurrent requests sent by the SageMaker client to the model container. If no value is provided, SageMaker chooses an optimal value.
- async_inference_config.output_config
Specifies the configuration for asynchronous inference invocation outputs. Show child fields- async_inference_config.output_config.kms_key_id
The Amazon Web Services Key Management Service (Amazon Web Services KMS) key that SageMaker uses to encrypt the asynchronous inference output in Amazon S3. - async_inference_config.output_config.notification_config
Specifies the configuration for notifications of inference results for asynchronous inference. Show child fields- async_inference_config.output_config.notification_config.error_topic
Amazon SNS topic to post a notification to when inference fails. If no topic is provided, no notification is sent on failure. - async_inference_config.output_config.notification_config.include_inference_response_in[]
- async_inference_config.output_config.notification_config.success_topic
Amazon SNS topic to post a notification to when inference completes successfully. If no topic is provided, no notification is sent on success.
- async_inference_config.output_config.s3_failure_path
The Amazon S3 location to upload failure inference responses to. - async_inference_config.output_config.s3_output_path
The Amazon S3 location to upload inference responses to.
|
creation_time
A timestamp that shows when the endpoint was created. | TIMESTAMP_S |
data_capture_config
The currently active data capture configuration used by your Endpoint. | STRUCT(
"enable_capture" BOOLEAN,
"capture_status" VARCHAR,
"current_sampling_percentage" BIGINT,
"destination_s3_uri" VARCHAR,
"kms_key_id" VARCHAR
) |
Show child fields- data_capture_config.capture_status
Whether data capture is currently functional. - data_capture_config.current_sampling_percentage
The percentage of requests being captured by your Endpoint. - data_capture_config.destination_s3_uri
The Amazon S3 location being used to capture the data. - data_capture_config.enable_capture
Whether data capture is enabled or disabled. - data_capture_config.kms_key_id
The KMS key being used to encrypt the data in Amazon S3.
|
endpoint_arn
The Amazon Resource Name (ARN) of the endpoint. | VARCHAR |
endpoint_config_name
The name of the endpoint configuration associated with this endpoint. | VARCHAR |
endpoint_status
The status of the endpoint. -
OutOfService: Endpoint is not available to take incoming requests. -
Creating: CreateEndpoint is executing. -
Updating: UpdateEndpoint or UpdateEndpointWeightsAndCapacities is executing. -
SystemUpdating: Endpoint is undergoing maintenance and cannot be updated or deleted or re-scaled until it has completed. This maintenance operation does not change any customer-specified values such as VPC config, KMS encryption, model, instance type, or instance count. -
RollingBack: Endpoint fails to scale up or down or change its variant weight and is in the process of rolling back to its previous configuration. Once the rollback completes, endpoint returns to an InService status. This transitional status only applies to an endpoint that has autoscaling enabled and is undergoing variant weight or capacity changes as part of an UpdateEndpointWeightsAndCapacities call or when the UpdateEndpointWeightsAndCapacities operation is called explicitly. -
InService: Endpoint is available to process incoming requests. -
Deleting: DeleteEndpoint is executing. -
Failed: Endpoint could not be created, updated, or re-scaled. Use the FailureReason value returned by DescribeEndpoint for information about the failure. DeleteEndpoint is the only operation that can be performed on a failed endpoint. -
UpdateRollbackFailed: Both the rolling deployment and auto-rollback failed. Your endpoint is in service with a mix of the old and new endpoint configurations. For information about how to remedy this issue and restore the endpoint's status to InService, see Rolling Deployments. | VARCHAR |
explainer_config
The configuration parameters for an explainer. | STRUCT(
"clarify_explainer_config" STRUCT(
"enable_explanations" VARCHAR,
"inference_config" STRUCT(
"features_attribute" VARCHAR,
"content_template" VARCHAR,
"max_record_count" BIGINT,
"max_payload_in_mb" BIGINT,
"probability_index" BIGINT,
"label_index" BIGINT,
"probability_attribute" VARCHAR,
"label_attribute" VARCHAR,
"label_headers" VARCHAR[],
"feature_headers" VARCHAR[],
"feature_types" VARCHAR[]
),
"shap_config" STRUCT(
"shap_baseline_config" STRUCT(
"mime_type" VARCHAR,
"shap_baseline" VARCHAR,
"shap_baseline_uri" VARCHAR
),
"number_of_samples" BIGINT,
"use_logit" BOOLEAN,
"seed" BIGINT,
"text_config" STRUCT(
"language" VARCHAR,
"granularity" VARCHAR
)
)
)
) |
Show child fields- explainer_config.clarify_explainer_config
A member of ExplainerConfig that contains configuration parameters for the SageMaker Clarify explainer. Show child fields- explainer_config.clarify_explainer_config.enable_explanations
A JMESPath boolean expression used to filter which records to explain. Explanations are activated by default. See EnableExplanations for additional information. - explainer_config.clarify_explainer_config.inference_config
The inference configuration parameter for the model container. Show child fields- explainer_config.clarify_explainer_config.inference_config.content_template
A template string used to format a JSON record into an acceptable model container input. For example, a ContentTemplate string '{"myfeatures":$features}' will format a list of features [1,2,3] into the record string '{"myfeatures":[1,2,3]}'. Required only when the model container input is in JSON Lines format. - explainer_config.clarify_explainer_config.inference_config.feature_headers[]
- explainer_config.clarify_explainer_config.inference_config.feature_types[]
- explainer_config.clarify_explainer_config.inference_config.features_attribute
Provides the JMESPath expression to extract the features from a model container input in JSON Lines format. For example, if FeaturesAttribute is the JMESPath expression 'myfeatures', it extracts a list of features [1,2,3] from request data '{"myfeatures":[1,2,3]}'. - explainer_config.clarify_explainer_config.inference_config.label_attribute
A JMESPath expression used to locate the list of label headers in the model container output. Example: If the model container output of a batch request is '{"labels":["cat","dog","fish"],"probability":[0.6,0.3,0.1]}', then set LabelAttribute to 'labels' to extract the list of label headers ["cat","dog","fish"] - explainer_config.clarify_explainer_config.inference_config.label_headers[]
- explainer_config.clarify_explainer_config.inference_config.label_index
A zero-based index used to extract a label header or list of label headers from model container output in CSV format. Example for a multiclass model: If the model container output consists of label headers followed by probabilities: '"[\'cat\',\'dog\',\'fish\']","[0.1,0.6,0.3]"', set LabelIndex to 0 to select the label headers ['cat','dog','fish']. - explainer_config.clarify_explainer_config.inference_config.max_payload_in_mb
The maximum payload size (MB) allowed of a request from the explainer to the model container. Defaults to 6 MB. - explainer_config.clarify_explainer_config.inference_config.max_record_count
The maximum number of records in a request that the model container can process when querying the model container for the predictions of a synthetic dataset. A record is a unit of input data that inference can be made on, for example, a single line in CSV data. If MaxRecordCount is 1, the model container expects one record per request. A value of 2 or greater means that the model expects batch requests, which can reduce overhead and speed up the inferencing process. If this parameter is not provided, the explainer will tune the record count per request according to the model container's capacity at runtime. - explainer_config.clarify_explainer_config.inference_config.probability_attribute
A JMESPath expression used to extract the probability (or score) from the model container output if the model container is in JSON Lines format. Example: If the model container output of a single request is '{"predicted_label":1,"probability":0.6}', then set ProbabilityAttribute to 'probability'. - explainer_config.clarify_explainer_config.inference_config.probability_index
A zero-based index used to extract a probability value (score) or list from model container output in CSV format. If this value is not provided, the entire model container output will be treated as a probability value (score) or list. Example for a single class model: If the model container output consists of a string-formatted prediction label followed by its probability: '1,0.6', set ProbabilityIndex to 1 to select the probability value 0.6. Example for a multiclass model: If the model container output consists of a string-formatted prediction label followed by its probability: '"[\'cat\',\'dog\',\'fish\']","[0.1,0.6,0.3]"', set ProbabilityIndex to 1 to select the probability values [0.1,0.6,0.3].
- explainer_config.clarify_explainer_config.shap_config
The configuration for SHAP analysis. Show child fields- explainer_config.clarify_explainer_config.shap_config.number_of_samples
The number of samples to be used for analysis by the Kernal SHAP algorithm. The number of samples determines the size of the synthetic dataset, which has an impact on latency of explainability requests. For more information, see the Synthetic data of Configure and create an endpoint. - explainer_config.clarify_explainer_config.shap_config.seed
The starting value used to initialize the random number generator in the explainer. Provide a value for this parameter to obtain a deterministic SHAP result. - explainer_config.clarify_explainer_config.shap_config.shap_baseline_config
The configuration for the SHAP baseline of the Kernal SHAP algorithm. Show child fields- explainer_config.clarify_explainer_config.shap_config.shap_baseline_config.mime_type
The MIME type of the baseline data. Choose from 'text/csv' or 'application/jsonlines'. Defaults to 'text/csv'. - explainer_config.clarify_explainer_config.shap_config.shap_baseline_config.shap_baseline
The inline SHAP baseline data in string format. ShapBaseline can have one or multiple records to be used as the baseline dataset. The format of the SHAP baseline file should be the same format as the training dataset. For example, if the training dataset is in CSV format and each record contains four features, and all features are numerical, then the format of the baseline data should also share these characteristics. For natural language processing (NLP) of text columns, the baseline value should be the value used to replace the unit of text specified by the Granularity of the TextConfig parameter. The size limit for ShapBasline is 4 KB. Use the ShapBaselineUri parameter if you want to provide more than 4 KB of baseline data. - explainer_config.clarify_explainer_config.shap_config.shap_baseline_config.shap_baseline_uri
The uniform resource identifier (URI) of the S3 bucket where the SHAP baseline file is stored. The format of the SHAP baseline file should be the same format as the format of the training dataset. For example, if the training dataset is in CSV format, and each record in the training dataset has four features, and all features are numerical, then the baseline file should also have this same format. Each record should contain only the features. If you are using a virtual private cloud (VPC), the ShapBaselineUri should be accessible to the VPC. For more information about setting up endpoints with Amazon Virtual Private Cloud, see Give SageMaker access to Resources in your Amazon Virtual Private Cloud.
- explainer_config.clarify_explainer_config.shap_config.text_config
A parameter that indicates if text features are treated as text and explanations are provided for individual units of text. Required for natural language processing (NLP) explainability only. Show child fields- explainer_config.clarify_explainer_config.shap_config.text_config.granularity
The unit of granularity for the analysis of text features. For example, if the unit is 'token', then each token (like a word in English) of the text is treated as a feature. SHAP values are computed for each unit/feature. - explainer_config.clarify_explainer_config.shap_config.text_config.language
Specifies the language of the text features in ISO 639-1 or ISO 639-3 code of a supported language. For a mix of multiple languages, use code 'xx'.
- explainer_config.clarify_explainer_config.shap_config.use_logit
A Boolean toggle to indicate if you want to use the logit function (true) or log-odds units (false) for model predictions. Defaults to false.
|
failure_reason
If the status of the endpoint is Failed, the reason why it failed. | VARCHAR |
last_deployment_config
The most recent deployment configuration for the endpoint. | STRUCT(
"blue_green_update_policy" STRUCT(
"traffic_routing_configuration" STRUCT(
"type" VARCHAR,
"wait_interval_in_seconds" BIGINT,
"canary_size" STRUCT(
"type" VARCHAR,
"value" BIGINT
),
"linear_step_size" STRUCT(
"type" VARCHAR,
"value" BIGINT
)
),
"termination_wait_in_seconds" BIGINT,
"maximum_execution_timeout_in_seconds" BIGINT
),
"rolling_update_policy" STRUCT(
"maximum_batch_size" STRUCT(
"type" VARCHAR,
"value" BIGINT
),
"wait_interval_in_seconds" BIGINT,
"maximum_execution_timeout_in_seconds" BIGINT,
"rollback_maximum_batch_size" STRUCT(
"type" VARCHAR,
"value" BIGINT
)
),
"auto_rollback_configuration" STRUCT(
"alarms" STRUCT(
"alarm_name" VARCHAR
)[]
)
) |
Show child fields- last_deployment_config.auto_rollback_configuration
Automatic rollback configuration for handling endpoint deployment failures and recovery. Show child fields- last_deployment_config.auto_rollback_configuration.alarms[]
Show child fields- last_deployment_config.auto_rollback_configuration.alarms[].alarm_name
The name of a CloudWatch alarm in your account.
- last_deployment_config.blue_green_update_policy
Update policy for a blue/green deployment. If this update policy is specified, SageMaker creates a new fleet during the deployment while maintaining the old fleet. SageMaker flips traffic to the new fleet according to the specified traffic routing configuration. Only one update policy should be used in the deployment configuration. If no update policy is specified, SageMaker uses a blue/green deployment strategy with all at once traffic shifting by default. Show child fields- last_deployment_config.blue_green_update_policy.maximum_execution_timeout_in_seconds
Maximum execution timeout for the deployment. Note that the timeout value should be larger than the total waiting time specified in TerminationWaitInSeconds and WaitIntervalInSeconds. - last_deployment_config.blue_green_update_policy.termination_wait_in_seconds
Additional waiting time in seconds after the completion of an endpoint deployment before terminating the old endpoint fleet. Default is 0. - last_deployment_config.blue_green_update_policy.traffic_routing_configuration
Defines the traffic routing strategy to shift traffic from the old fleet to the new fleet during an endpoint deployment. Show child fields- last_deployment_config.blue_green_update_policy.traffic_routing_configuration.canary_size
Batch size for the first step to turn on traffic on the new endpoint fleet. Value must be less than or equal to 50% of the variant's total instance count. Show child fields- last_deployment_config.blue_green_update_policy.traffic_routing_configuration.canary_size.type
Specifies the endpoint capacity type. - last_deployment_config.blue_green_update_policy.traffic_routing_configuration.canary_size.value
Defines the capacity size, either as a number of instances or a capacity percentage.
- last_deployment_config.blue_green_update_policy.traffic_routing_configuration.linear_step_size
Batch size for each step to turn on traffic on the new endpoint fleet. Value must be 10-50% of the variant's total instance count. Show child fields- last_deployment_config.blue_green_update_policy.traffic_routing_configuration.linear_step_size.type
Specifies the endpoint capacity type. - last_deployment_config.blue_green_update_policy.traffic_routing_configuration.linear_step_size.value
Defines the capacity size, either as a number of instances or a capacity percentage.
- last_deployment_config.blue_green_update_policy.traffic_routing_configuration.type
Traffic routing strategy type. -
ALL_AT_ONCE: Endpoint traffic shifts to the new fleet in a single step. -
CANARY: Endpoint traffic shifts to the new fleet in two steps. The first step is the canary, which is a small portion of the traffic. The second step is the remainder of the traffic. -
LINEAR: Endpoint traffic shifts to the new fleet in n steps of a configurable size. - last_deployment_config.blue_green_update_policy.traffic_routing_configuration.wait_interval_in_seconds
The waiting time (in seconds) between incremental steps to turn on traffic on the new endpoint fleet.
- last_deployment_config.rolling_update_policy
Specifies a rolling deployment strategy for updating a SageMaker endpoint. Show child fields- last_deployment_config.rolling_update_policy.maximum_batch_size
Batch size for each rolling step to provision capacity and turn on traffic on the new endpoint fleet, and terminate capacity on the old endpoint fleet. Value must be between 5% to 50% of the variant's total instance count. Show child fields- last_deployment_config.rolling_update_policy.maximum_batch_size.type
Specifies the endpoint capacity type. - last_deployment_config.rolling_update_policy.maximum_batch_size.value
Defines the capacity size, either as a number of instances or a capacity percentage.
- last_deployment_config.rolling_update_policy.maximum_execution_timeout_in_seconds
The time limit for the total deployment. Exceeding this limit causes a timeout. - last_deployment_config.rolling_update_policy.rollback_maximum_batch_size
Batch size for rollback to the old endpoint fleet. Each rolling step to provision capacity and turn on traffic on the old endpoint fleet, and terminate capacity on the new endpoint fleet. If this field is absent, the default value will be set to 100% of total capacity which means to bring up the whole capacity of the old fleet at once during rollback. Show child fields- last_deployment_config.rolling_update_policy.rollback_maximum_batch_size.type
Specifies the endpoint capacity type. - last_deployment_config.rolling_update_policy.rollback_maximum_batch_size.value
Defines the capacity size, either as a number of instances or a capacity percentage.
- last_deployment_config.rolling_update_policy.wait_interval_in_seconds
The length of the baking period, during which SageMaker monitors alarms for each batch on the new fleet.
|
last_modified_time
A timestamp that shows when the endpoint was last modified. | TIMESTAMP_S |
pending_deployment_summary
Returns the summary of an in-progress deployment. This field is only returned when the endpoint is creating or updating with a new endpoint configuration. | STRUCT(
"endpoint_config_name" VARCHAR,
"production_variants" STRUCT(
"variant_name" VARCHAR,
"deployed_images" STRUCT(
"specified_image" VARCHAR,
"resolved_image" VARCHAR,
"resolution_time" TIMESTAMP_S
)[],
"current_weight" DOUBLE,
"desired_weight" DOUBLE,
"current_instance_count" BIGINT,
"desired_instance_count" BIGINT,
"instance_type" VARCHAR,
"accelerator_type" VARCHAR,
"variant_status" STRUCT(
"status" VARCHAR,
"status_message" VARCHAR,
"start_time" TIMESTAMP_S
)[],
"current_serverless_config" STRUCT(
"memory_size_in_mb" BIGINT,
"max_concurrency" BIGINT,
"provisioned_concurrency" BIGINT
),
"desired_serverless_config" STRUCT(
"memory_size_in_mb" BIGINT,
"max_concurrency" BIGINT,
"provisioned_concurrency" BIGINT
),
"managed_instance_scaling" STRUCT(
"status" VARCHAR,
"min_instance_count" BIGINT,
"max_instance_count" BIGINT
),
"routing_config" STRUCT(
"routing_strategy" VARCHAR
)
)[],
"start_time" TIMESTAMP_S,
"shadow_production_variants" STRUCT(
"variant_name" VARCHAR,
"deployed_images" STRUCT(
"specified_image" VARCHAR,
"resolved_image" VARCHAR,
"resolution_time" TIMESTAMP_S
)[],
"current_weight" DOUBLE,
"desired_weight" DOUBLE,
"current_instance_count" BIGINT,
"desired_instance_count" BIGINT,
"instance_type" VARCHAR,
"accelerator_type" VARCHAR,
"variant_status" STRUCT(
"status" VARCHAR,
"status_message" VARCHAR,
"start_time" TIMESTAMP_S
)[],
"current_serverless_config" STRUCT(
"memory_size_in_mb" BIGINT,
"max_concurrency" BIGINT,
"provisioned_concurrency" BIGINT
),
"desired_serverless_config" STRUCT(
"memory_size_in_mb" BIGINT,
"max_concurrency" BIGINT,
"provisioned_concurrency" BIGINT
),
"managed_instance_scaling" STRUCT(
"status" VARCHAR,
"min_instance_count" BIGINT,
"max_instance_count" BIGINT
),
"routing_config" STRUCT(
"routing_strategy" VARCHAR
)
)[]
) |
Show child fields- pending_deployment_summary.endpoint_config_name
The name of the endpoint configuration used in the deployment. - pending_deployment_summary.production_variants[]
Show child fields- pending_deployment_summary.production_variants[].accelerator_type
The size of the Elastic Inference (EI) instance to use for the production variant. EI instances provide on-demand GPU computing for inference. For more information, see Using Elastic Inference in Amazon SageMaker. - pending_deployment_summary.production_variants[].current_instance_count
The number of instances associated with the variant. - pending_deployment_summary.production_variants[].current_serverless_config
The serverless configuration for the endpoint. Show child fields- pending_deployment_summary.production_variants[].current_serverless_config.max_concurrency
The maximum number of concurrent invocations your serverless endpoint can process. - pending_deployment_summary.production_variants[].current_serverless_config.memory_size_in_mb
The memory size of your serverless endpoint. Valid values are in 1 GB increments: 1024 MB, 2048 MB, 3072 MB, 4096 MB, 5120 MB, or 6144 MB. - pending_deployment_summary.production_variants[].current_serverless_config.provisioned_concurrency
The amount of provisioned concurrency to allocate for the serverless endpoint. Should be less than or equal to MaxConcurrency. This field is not supported for serverless endpoint recommendations for Inference Recommender jobs. For more information about creating an Inference Recommender job, see CreateInferenceRecommendationsJobs.
- pending_deployment_summary.production_variants[].current_weight
The weight associated with the variant. - pending_deployment_summary.production_variants[].deployed_images[]
Show child fields- pending_deployment_summary.production_variants[].deployed_images[].resolution_time
The date and time when the image path for the model resolved to the ResolvedImage - pending_deployment_summary.production_variants[].deployed_images[].resolved_image
The specific digest path of the image hosted in this ProductionVariant. - pending_deployment_summary.production_variants[].deployed_images[].specified_image
The image path you specified when you created the model.
- pending_deployment_summary.production_variants[].desired_instance_count
The number of instances requested in this deployment, as specified in the endpoint configuration for the endpoint. The value is taken from the request to the CreateEndpointConfig operation. - pending_deployment_summary.production_variants[].desired_serverless_config
The serverless configuration requested for this deployment, as specified in the endpoint configuration for the endpoint. Show child fields- pending_deployment_summary.production_variants[].desired_serverless_config.max_concurrency
The maximum number of concurrent invocations your serverless endpoint can process. - pending_deployment_summary.production_variants[].desired_serverless_config.memory_size_in_mb
The memory size of your serverless endpoint. Valid values are in 1 GB increments: 1024 MB, 2048 MB, 3072 MB, 4096 MB, 5120 MB, or 6144 MB. - pending_deployment_summary.production_variants[].desired_serverless_config.provisioned_concurrency
The amount of provisioned concurrency to allocate for the serverless endpoint. Should be less than or equal to MaxConcurrency. This field is not supported for serverless endpoint recommendations for Inference Recommender jobs. For more information about creating an Inference Recommender job, see CreateInferenceRecommendationsJobs.
- pending_deployment_summary.production_variants[].desired_weight
The requested weight for the variant in this deployment, as specified in the endpoint configuration for the endpoint. The value is taken from the request to the CreateEndpointConfig operation. - pending_deployment_summary.production_variants[].instance_type
The type of instances associated with the variant. - pending_deployment_summary.production_variants[].managed_instance_scaling
Settings that control the range in the number of instances that the endpoint provisions as it scales up or down to accommodate traffic. Show child fields- pending_deployment_summary.production_variants[].managed_instance_scaling.max_instance_count
The maximum number of instances that the endpoint can provision when it scales up to accommodate an increase in traffic. - pending_deployment_summary.production_variants[].managed_instance_scaling.min_instance_count
The minimum number of instances that the endpoint must retain when it scales down to accommodate a decrease in traffic. - pending_deployment_summary.production_variants[].managed_instance_scaling.status
Indicates whether managed instance scaling is enabled.
- pending_deployment_summary.production_variants[].routing_config
Settings that control how the endpoint routes incoming traffic to the instances that the endpoint hosts. Show child fields- pending_deployment_summary.production_variants[].routing_config.routing_strategy
Sets how the endpoint routes incoming traffic:
- pending_deployment_summary.production_variants[].variant_name
The name of the variant. - pending_deployment_summary.production_variants[].variant_status[]
Show child fields- pending_deployment_summary.production_variants[].variant_status[].start_time
The start time of the current status change. - pending_deployment_summary.production_variants[].variant_status[].status
The endpoint variant status which describes the current deployment stage status or operational status. -
Creating: Creating inference resources for the production variant. -
Deleting: Terminating inference resources for the production variant. -
Updating: Updating capacity for the production variant. -
ActivatingTraffic: Turning on traffic for the production variant. -
Baking: Waiting period to monitor the CloudWatch alarms in the automatic rollback configuration. - pending_deployment_summary.production_variants[].variant_status[].status_message
A message that describes the status of the production variant.
- pending_deployment_summary.shadow_production_variants[]
Show child fields- pending_deployment_summary.shadow_production_variants[].accelerator_type
The size of the Elastic Inference (EI) instance to use for the production variant. EI instances provide on-demand GPU computing for inference. For more information, see Using Elastic Inference in Amazon SageMaker. - pending_deployment_summary.shadow_production_variants[].current_instance_count
The number of instances associated with the variant. - pending_deployment_summary.shadow_production_variants[].current_serverless_config
The serverless configuration for the endpoint. Show child fields- pending_deployment_summary.shadow_production_variants[].current_serverless_config.max_concurrency
The maximum number of concurrent invocations your serverless endpoint can process. - pending_deployment_summary.shadow_production_variants[].current_serverless_config.memory_size_in_mb
The memory size of your serverless endpoint. Valid values are in 1 GB increments: 1024 MB, 2048 MB, 3072 MB, 4096 MB, 5120 MB, or 6144 MB. - pending_deployment_summary.shadow_production_variants[].current_serverless_config.provisioned_concurrency
The amount of provisioned concurrency to allocate for the serverless endpoint. Should be less than or equal to MaxConcurrency. This field is not supported for serverless endpoint recommendations for Inference Recommender jobs. For more information about creating an Inference Recommender job, see CreateInferenceRecommendationsJobs.
- pending_deployment_summary.shadow_production_variants[].current_weight
The weight associated with the variant. - pending_deployment_summary.shadow_production_variants[].deployed_images[]
Show child fields- pending_deployment_summary.shadow_production_variants[].deployed_images[].resolution_time
The date and time when the image path for the model resolved to the ResolvedImage - pending_deployment_summary.shadow_production_variants[].deployed_images[].resolved_image
The specific digest path of the image hosted in this ProductionVariant. - pending_deployment_summary.shadow_production_variants[].deployed_images[].specified_image
The image path you specified when you created the model.
- pending_deployment_summary.shadow_production_variants[].desired_instance_count
The number of instances requested in this deployment, as specified in the endpoint configuration for the endpoint. The value is taken from the request to the CreateEndpointConfig operation. - pending_deployment_summary.shadow_production_variants[].desired_serverless_config
The serverless configuration requested for this deployment, as specified in the endpoint configuration for the endpoint. Show child fields- pending_deployment_summary.shadow_production_variants[].desired_serverless_config.max_concurrency
The maximum number of concurrent invocations your serverless endpoint can process. - pending_deployment_summary.shadow_production_variants[].desired_serverless_config.memory_size_in_mb
The memory size of your serverless endpoint. Valid values are in 1 GB increments: 1024 MB, 2048 MB, 3072 MB, 4096 MB, 5120 MB, or 6144 MB. - pending_deployment_summary.shadow_production_variants[].desired_serverless_config.provisioned_concurrency
The amount of provisioned concurrency to allocate for the serverless endpoint. Should be less than or equal to MaxConcurrency. This field is not supported for serverless endpoint recommendations for Inference Recommender jobs. For more information about creating an Inference Recommender job, see CreateInferenceRecommendationsJobs.
- pending_deployment_summary.shadow_production_variants[].desired_weight
The requested weight for the variant in this deployment, as specified in the endpoint configuration for the endpoint. The value is taken from the request to the CreateEndpointConfig operation. - pending_deployment_summary.shadow_production_variants[].instance_type
The type of instances associated with the variant. - pending_deployment_summary.shadow_production_variants[].managed_instance_scaling
Settings that control the range in the number of instances that the endpoint provisions as it scales up or down to accommodate traffic. Show child fields- pending_deployment_summary.shadow_production_variants[].managed_instance_scaling.max_instance_count
The maximum number of instances that the endpoint can provision when it scales up to accommodate an increase in traffic. - pending_deployment_summary.shadow_production_variants[].managed_instance_scaling.min_instance_count
The minimum number of instances that the endpoint must retain when it scales down to accommodate a decrease in traffic. - pending_deployment_summary.shadow_production_variants[].managed_instance_scaling.status
Indicates whether managed instance scaling is enabled.
- pending_deployment_summary.shadow_production_variants[].routing_config
Settings that control how the endpoint routes incoming traffic to the instances that the endpoint hosts. Show child fields- pending_deployment_summary.shadow_production_variants[].routing_config.routing_strategy
Sets how the endpoint routes incoming traffic:
- pending_deployment_summary.shadow_production_variants[].variant_name
The name of the variant. - pending_deployment_summary.shadow_production_variants[].variant_status[]
Show child fields- pending_deployment_summary.shadow_production_variants[].variant_status[].start_time
The start time of the current status change. - pending_deployment_summary.shadow_production_variants[].variant_status[].status
The endpoint variant status which describes the current deployment stage status or operational status. -
Creating: Creating inference resources for the production variant. -
Deleting: Terminating inference resources for the production variant. -
Updating: Updating capacity for the production variant. -
ActivatingTraffic: Turning on traffic for the production variant. -
Baking: Waiting period to monitor the CloudWatch alarms in the automatic rollback configuration. - pending_deployment_summary.shadow_production_variants[].variant_status[].status_message
A message that describes the status of the production variant.
- pending_deployment_summary.start_time
The start time of the deployment.
|
production_variants
An array of ProductionVariantSummary objects, one for each model hosted behind this endpoint. | STRUCT(
"variant_name" VARCHAR,
"deployed_images" STRUCT(
"specified_image" VARCHAR,
"resolved_image" VARCHAR,
"resolution_time" TIMESTAMP_S
)[],
"current_weight" DOUBLE,
"desired_weight" DOUBLE,
"current_instance_count" BIGINT,
"desired_instance_count" BIGINT,
"variant_status" STRUCT(
"status" VARCHAR,
"status_message" VARCHAR,
"start_time" TIMESTAMP_S
)[],
"current_serverless_config" STRUCT(
"memory_size_in_mb" BIGINT,
"max_concurrency" BIGINT,
"provisioned_concurrency" BIGINT
),
"desired_serverless_config" STRUCT(
"memory_size_in_mb" BIGINT,
"max_concurrency" BIGINT,
"provisioned_concurrency" BIGINT
),
"managed_instance_scaling" STRUCT(
"status" VARCHAR,
"min_instance_count" BIGINT,
"max_instance_count" BIGINT
),
"routing_config" STRUCT(
"routing_strategy" VARCHAR
)
)[] |
Show child fields- production_variants[]
Show child fields- production_variants[].current_instance_count
The number of instances associated with the variant. - production_variants[].current_serverless_config
The serverless configuration for the endpoint. Show child fields- production_variants[].current_serverless_config.max_concurrency
The maximum number of concurrent invocations your serverless endpoint can process. - production_variants[].current_serverless_config.memory_size_in_mb
The memory size of your serverless endpoint. Valid values are in 1 GB increments: 1024 MB, 2048 MB, 3072 MB, 4096 MB, 5120 MB, or 6144 MB. - production_variants[].current_serverless_config.provisioned_concurrency
The amount of provisioned concurrency to allocate for the serverless endpoint. Should be less than or equal to MaxConcurrency. This field is not supported for serverless endpoint recommendations for Inference Recommender jobs. For more information about creating an Inference Recommender job, see CreateInferenceRecommendationsJobs.
- production_variants[].current_weight
The weight associated with the variant. - production_variants[].deployed_images[]
Show child fields- production_variants[].deployed_images[].resolution_time
The date and time when the image path for the model resolved to the ResolvedImage - production_variants[].deployed_images[].resolved_image
The specific digest path of the image hosted in this ProductionVariant. - production_variants[].deployed_images[].specified_image
The image path you specified when you created the model.
- production_variants[].desired_instance_count
The number of instances requested in the UpdateEndpointWeightsAndCapacities request. - production_variants[].desired_serverless_config
The serverless configuration requested for the endpoint update. Show child fields- production_variants[].desired_serverless_config.max_concurrency
The maximum number of concurrent invocations your serverless endpoint can process. - production_variants[].desired_serverless_config.memory_size_in_mb
The memory size of your serverless endpoint. Valid values are in 1 GB increments: 1024 MB, 2048 MB, 3072 MB, 4096 MB, 5120 MB, or 6144 MB. - production_variants[].desired_serverless_config.provisioned_concurrency
The amount of provisioned concurrency to allocate for the serverless endpoint. Should be less than or equal to MaxConcurrency. This field is not supported for serverless endpoint recommendations for Inference Recommender jobs. For more information about creating an Inference Recommender job, see CreateInferenceRecommendationsJobs.
- production_variants[].desired_weight
The requested weight, as specified in the UpdateEndpointWeightsAndCapacities request. - production_variants[].managed_instance_scaling
Settings that control the range in the number of instances that the endpoint provisions as it scales up or down to accommodate traffic. Show child fields- production_variants[].managed_instance_scaling.max_instance_count
The maximum number of instances that the endpoint can provision when it scales up to accommodate an increase in traffic. - production_variants[].managed_instance_scaling.min_instance_count
The minimum number of instances that the endpoint must retain when it scales down to accommodate a decrease in traffic. - production_variants[].managed_instance_scaling.status
Indicates whether managed instance scaling is enabled.
- production_variants[].routing_config
Settings that control how the endpoint routes incoming traffic to the instances that the endpoint hosts. Show child fields- production_variants[].routing_config.routing_strategy
Sets how the endpoint routes incoming traffic:
- production_variants[].variant_name
The name of the variant. - production_variants[].variant_status[]
Show child fields- production_variants[].variant_status[].start_time
The start time of the current status change. - production_variants[].variant_status[].status
The endpoint variant status which describes the current deployment stage status or operational status. -
Creating: Creating inference resources for the production variant. -
Deleting: Terminating inference resources for the production variant. -
Updating: Updating capacity for the production variant. -
ActivatingTraffic: Turning on traffic for the production variant. -
Baking: Waiting period to monitor the CloudWatch alarms in the automatic rollback configuration. - production_variants[].variant_status[].status_message
A message that describes the status of the production variant.
|
shadow_production_variants
An array of ProductionVariantSummary objects, one for each model that you want to host at this endpoint in shadow mode with production traffic replicated from the model specified on ProductionVariants. | STRUCT(
"variant_name" VARCHAR,
"deployed_images" STRUCT(
"specified_image" VARCHAR,
"resolved_image" VARCHAR,
"resolution_time" TIMESTAMP_S
)[],
"current_weight" DOUBLE,
"desired_weight" DOUBLE,
"current_instance_count" BIGINT,
"desired_instance_count" BIGINT,
"variant_status" STRUCT(
"status" VARCHAR,
"status_message" VARCHAR,
"start_time" TIMESTAMP_S
)[],
"current_serverless_config" STRUCT(
"memory_size_in_mb" BIGINT,
"max_concurrency" BIGINT,
"provisioned_concurrency" BIGINT
),
"desired_serverless_config" STRUCT(
"memory_size_in_mb" BIGINT,
"max_concurrency" BIGINT,
"provisioned_concurrency" BIGINT
),
"managed_instance_scaling" STRUCT(
"status" VARCHAR,
"min_instance_count" BIGINT,
"max_instance_count" BIGINT
),
"routing_config" STRUCT(
"routing_strategy" VARCHAR
)
)[] |
Show child fields- shadow_production_variants[]
Show child fields- shadow_production_variants[].current_instance_count
The number of instances associated with the variant. - shadow_production_variants[].current_serverless_config
The serverless configuration for the endpoint. Show child fields- shadow_production_variants[].current_serverless_config.max_concurrency
The maximum number of concurrent invocations your serverless endpoint can process. - shadow_production_variants[].current_serverless_config.memory_size_in_mb
The memory size of your serverless endpoint. Valid values are in 1 GB increments: 1024 MB, 2048 MB, 3072 MB, 4096 MB, 5120 MB, or 6144 MB. - shadow_production_variants[].current_serverless_config.provisioned_concurrency
The amount of provisioned concurrency to allocate for the serverless endpoint. Should be less than or equal to MaxConcurrency. This field is not supported for serverless endpoint recommendations for Inference Recommender jobs. For more information about creating an Inference Recommender job, see CreateInferenceRecommendationsJobs.
- shadow_production_variants[].current_weight
The weight associated with the variant. - shadow_production_variants[].deployed_images[]
Show child fields- shadow_production_variants[].deployed_images[].resolution_time
The date and time when the image path for the model resolved to the ResolvedImage - shadow_production_variants[].deployed_images[].resolved_image
The specific digest path of the image hosted in this ProductionVariant. - shadow_production_variants[].deployed_images[].specified_image
The image path you specified when you created the model.
- shadow_production_variants[].desired_instance_count
The number of instances requested in the UpdateEndpointWeightsAndCapacities request. - shadow_production_variants[].desired_serverless_config
The serverless configuration requested for the endpoint update. Show child fields- shadow_production_variants[].desired_serverless_config.max_concurrency
The maximum number of concurrent invocations your serverless endpoint can process. - shadow_production_variants[].desired_serverless_config.memory_size_in_mb
The memory size of your serverless endpoint. Valid values are in 1 GB increments: 1024 MB, 2048 MB, 3072 MB, 4096 MB, 5120 MB, or 6144 MB. - shadow_production_variants[].desired_serverless_config.provisioned_concurrency
The amount of provisioned concurrency to allocate for the serverless endpoint. Should be less than or equal to MaxConcurrency. This field is not supported for serverless endpoint recommendations for Inference Recommender jobs. For more information about creating an Inference Recommender job, see CreateInferenceRecommendationsJobs.
- shadow_production_variants[].desired_weight
The requested weight, as specified in the UpdateEndpointWeightsAndCapacities request. - shadow_production_variants[].managed_instance_scaling
Settings that control the range in the number of instances that the endpoint provisions as it scales up or down to accommodate traffic. Show child fields- shadow_production_variants[].managed_instance_scaling.max_instance_count
The maximum number of instances that the endpoint can provision when it scales up to accommodate an increase in traffic. - shadow_production_variants[].managed_instance_scaling.min_instance_count
The minimum number of instances that the endpoint must retain when it scales down to accommodate a decrease in traffic. - shadow_production_variants[].managed_instance_scaling.status
Indicates whether managed instance scaling is enabled.
- shadow_production_variants[].routing_config
Settings that control how the endpoint routes incoming traffic to the instances that the endpoint hosts. Show child fields- shadow_production_variants[].routing_config.routing_strategy
Sets how the endpoint routes incoming traffic:
- shadow_production_variants[].variant_name
The name of the variant. - shadow_production_variants[].variant_status[]
Show child fields- shadow_production_variants[].variant_status[].start_time
The start time of the current status change. - shadow_production_variants[].variant_status[].status
The endpoint variant status which describes the current deployment stage status or operational status. -
Creating: Creating inference resources for the production variant. -
Deleting: Terminating inference resources for the production variant. -
Updating: Updating capacity for the production variant. -
ActivatingTraffic: Turning on traffic for the production variant. -
Baking: Waiting period to monitor the CloudWatch alarms in the automatic rollback configuration. - shadow_production_variants[].variant_status[].status_message
A message that describes the status of the production variant.
|