用AWS CDK

在这篇文章中,我们提供了一个完整的解决方案,用于使用AWS Cloud Development Kit(AWS CDK)在Amazon Sagemaker AI上编程创建私人劳动力,包括设置专用,完整配置的Amazon Cognito用户池。

来源:亚马逊云科技 _机器学习
亚马逊萨吉人地面真理的私人劳动力和亚马逊增强了AI(Amazon A2I)帮助组织建立专有的高质量数据集,同时保持高度的安全性和隐私标准。AWS管理控制台提供了一种快速和直觉的方式,提供了一种私人劳动力,但是许多组织可以通过这些组织来实现Infosiation,因为它需要自动化InfrrrrrraStiration,因为它是自动化的,因为它需要自动化(IT),因为它需要自动化(IT),因为它需要自动化(In Infrastion)。 automated and consistent deployments, increased operational efficiency, and reduced chances of human errors or misconfigurations.However, creating a private workforce with IaC is not a straightforward task because of some complex technical dependencies between services during the initial creation.In this post, we present a complete solution for programmatically creating private workforces on Amazon SageMaker AI using the AWS Cloud Development Kit (AWS CDK), including the setup of a专用的,完全配置的Amazon Cognito用户池。 The accompanying GitHub repository provides a customizable AWS CDK example that shows how to create and manage a private workforce, paired with a dedicated Amazon Cognito user pool, and how to integrate the necessary Amazon Cognito configurations.Solution overviewThis solution demonstrates how to create a private workforce and a coupled Amazon Cognito user pool and its dependent resources.目的是为基础基础架构提供全面的设置,以启用机器学习(ML)标记任务。该解决方案的关键技术挑战是亚马逊Cognito资源与私人劳动力之间的相互依赖。具体而言,创建用户池应用客户端的创建需要某些参数,例如,仅创建了一个私人工作,才能创建出来。但是,私人劳动力创建本身需要已经存在应用程序客户端。这种相互的依赖性使以直接的方式建立基础架构具有挑战性。