Accelerate machine learning model training with Amazon SageMaker and Amazon S3 Express One Zone
The Amazon S3 Express One Zone storage class can now accelerate Amazon SageMaker Model Training with faster load times for training data, checkpoints, and model outputs. S3 Express One Zone is purpose-built to deliver the fastest cloud object storage for performance-critical applications and delivers consistent single-digit millisecond request latency and high throughput to reduce the time and cost to train and tune machine learning models through Amazon SageMaker.
The Amazon S3 Express One Zone storage class can now accelerate Amazon SageMaker Model Training with faster load times for training data, checkpoints, and model outputs. S3 Express One Zone is purpose-built to deliver the fastest cloud object storage for performance-critical applications and delivers consistent single-digit millisecond request latency and high throughput to reduce the time and cost to train and tune machine learning models through Amazon SageMaker.
Get started with S3 Express One Zone by creating a directory bucket in the S3 console or through the AWS CLI. Next, upload objects or import them from an existing bucket using S3 Batch Operations. Then, in the SageMaker Model Training workflow, specify your directory bucket as the S3 location for the input data, checkpoint, or output data configurations.
Amazon S3 Express One Zone is generally available to be used with Amazon SageMaker Model Training in US East (N. Virginia), US West (Oregon), Europe (Stockholm), and Asia Pacific (Tokyo) AWS Regions. For pricing information, visit the S3 pricing page. To learn more, visit the SageMaker Developer Guide. To learn more about the S3 Express One Zone storage class, visit the product page, documentation, or S3 User Guide.