Announcing Amazon Web Services Glue for Ray (Preview)

{"value":"Posted On: Nov 28, 2022\n\nAmazon Web Services Glue for Ray is a new engine option on Amazon Web Services Glue. Data engineers can use Amazon Web Services Glue for Ray to process large datasets with Python and popular Python libraries. Amazon Web Services Glue is a serverless, scalable data integration service used to discover, prepare, move, and integrate data from multiple sources. Amazon Web Services Glue for Ray combines that serverless option for data integration with Ray (ray.io), a popular new open-source compute framework that helps you scale Python workloads.\n\nYou pay only for the resources that you use while running code, and you don’t need to configure or tune any resources. Amazon Web Services Glue for Ray facilitates the distributed processing of your Python code over multi-node clusters. You can create and run Ray jobs anywhere that you run Amazon Web Services Glue ETL (extract, transform, and load) jobs. This includes existing Amazon Web Services Glue jobs, command line interfaces (CLIs), and APIs. You can select the Ray engine through notebooks on Amazon Web Services Glue Studio, Amazon SageMaker Studio Notebook, or locally. When the Ray job is ready, you can run it on demand or on a schedule.\n\nAmazon Web Services Glue for Ray is available in preview in the following [Amazon Web Services Regions](https://aws.amazon.com/about-aws/global-infrastructure/regional-product-services/): US East (Ohio), US East (N. Virginia), US West (Oregon), Asia Pacific (Tokyo), and Europe (Ireland). \n\nTo learn more, see our [documentation](https://docs.aws.amazon.com/glue/latest/dg/author-job-ray.html).","render":"<p>Posted On: Nov 28, 2022</p>\n<p>Amazon Web Services Glue for Ray is a new engine option on Amazon Web Services Glue. Data engineers can use Amazon Web Services Glue for Ray to process large datasets with Python and popular Python libraries. Amazon Web Services Glue is a serverless, scalable data integration service used to discover, prepare, move, and integrate data from multiple sources. Amazon Web Services Glue for Ray combines that serverless option for data integration with Ray (ray.io), a popular new open-source compute framework that helps you scale Python workloads.</p>\n<p>You pay only for the resources that you use while running code, and you don’t need to configure or tune any resources. Amazon Web Services Glue for Ray facilitates the distributed processing of your Python code over multi-node clusters. You can create and run Ray jobs anywhere that you run Amazon Web Services Glue ETL (extract, transform, and load) jobs. This includes existing Amazon Web Services Glue jobs, command line interfaces (CLIs), and APIs. You can select the Ray engine through notebooks on Amazon Web Services Glue Studio, Amazon SageMaker Studio Notebook, or locally. When the Ray job is ready, you can run it on demand or on a schedule.</p>\n<p>Amazon Web Services Glue for Ray is available in preview in the following <a href=\"https://aws.amazon.com/about-aws/global-infrastructure/regional-product-services/\" target=\"_blank\">Amazon Web Services Regions</a>: US East (Ohio), US East (N. Virginia), US West (Oregon), Asia Pacific (Tokyo), and Europe (Ireland).</p>\n<p>To learn more, see our <a href=\"https://docs.aws.amazon.com/glue/latest/dg/author-job-ray.html\" target=\"_blank\">documentation</a>.</p>\n"}