Posted On: Jul 9, 2020

Amazon Forecast is a fully managed service that uses machine learning (ML) to generate accurate forecasts without requiring any prior ML experience. Amazon Forecast can be used in a wide variety of use cases, including product demand forecasting, inventory planning, workforce planning and cloud infrastructure usage forecasting.  

Starting today, you can assign tags to dataset groups, datasets, dataset import jobs, predictors, forecasts and forecast export jobs within Forecast. Each tag is a simple label consisting of a customer-defined key and an optional value that can make it easier to manage and filter resources. Tagging allows you to better manage and classify your Forecast resources and enables several use cases including providing access control and security risk management to name a few.

Without tags, enterprises or independent software vendors (ISVs) with multiple resources and users would need to define an Amazon Resource Name (ARN) for each resource as part of the policy attached to the role or user of the resource. This can be a cumbersome process depending on the number of resources and users. With this new capability, access to Forecast resources can be easily and efficiently controlled based on the environment (for example development versus production), specific applications or projects through an identifying tag. The conditions for accessing resources can be specified through IAM policies where the access to a particular resource can be defined as part of the policy statement.  

The tagging functionality is now available in US East (N. Virginia, Ohio), US West (Oregon), Europe (Ireland, Frankfurt),and Asia Pacific (Tokyo, Singapore, Seoul, Sydney, Mumbai). You can add or remove tags from Amazon Forecast resources using the AWS console, CLI, or SDK. Click here to learn more about how to create and use tags in Amazon Forecast. See AWS Tagging Strategies for general best practices for using tags with AWS resources.