SageMaker Pipeline Execution

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SageMaker Pipeline Execution in AWS represents the details of a specific run of a SageMaker pipeline. It provides information about the execution status, start and end times, steps involved, and metadata such as failure reasons or execution display names. This resource helps track, monitor, and manage machine learning workflow executions, making it easier to debug issues, audit processes, and ensure reproducibility of ML pipelines.

aws.sagemaker_pipeline_execution

Fields

ID	Type	Data Type	Description
_key	core	string
account_id	core	string
created_by	core	json	Information about the user who created or modified an experiment, trial, trial component, lineage group, project, or model card.
creation_time	core	timestamp	The time when the pipeline execution was created.
failure_reason	core	string	If the execution failed, a message describing why.
last_modified_by	core	json	Information about the user who created or modified an experiment, trial, trial component, lineage group, project, or model card.
last_modified_time	core	timestamp	The time when the pipeline execution was modified last.
parallelism_configuration	core	json	The parallelism configuration applied to the pipeline.
pipeline_arn	core	string	The Amazon Resource Name (ARN) of the pipeline.
pipeline_execution_arn	core	string	The Amazon Resource Name (ARN) of the pipeline execution.
pipeline_execution_description	core	string	The description of the pipeline execution.
pipeline_execution_display_name	core	string	The display name of the pipeline execution.
pipeline_execution_status	core	string	The status of the pipeline execution.
pipeline_experiment_config	core	json	Specifies the names of the experiment and trial created by a pipeline.
selective_execution_config	core	json	The selective execution configuration applied to the pipeline run.
tags	core	hstore