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Secure access to Amazon SageMaker Studio with AWS SSO and a SAML application

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Cloud security at AWS is the highest priority. Amazon SageMaker Studio offers various mechanisms to protect your data and code using integration with AWS security services like AWS Identity and Access Management (IAM), AWS Key Management Service (AWS KMS), or network isolation with Amazon Virtual Private Cloud (Amazon VPC). Customers in highly regulated industries, like financial services, can set up Studio in VPC only mode to enable network isolation and disable internet access from Studio notebooks. You can use IAM integration with Studio to control which users have access to resources like Studio notebooks, the Studio IDE, or Amazon SageMaker training jobs. A popular use case is to restrict access to the Studio IDE to only users from inside a specified network CIDR range or a designated VPC.


Secure multi-account model deployment with Amazon SageMaker: Part 1

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Amazon SageMaker Studio is a web-based, integrated development environment (IDE) for machine learning (ML) that lets you build, train, debug, deploy, and monitor your ML models. Although Studio provides all the tools you need to take your models from experimentation to production, you need a robust and secure model deployment process. This process must fulfill your organization's operational and security requirements. Amazon SageMaker and Studio provide a wide range of specialized functionality for building highly secure, scalable, and flexible MLOps platforms to cover your model deployment use cases and requirements. Three SageMaker services, SageMaker Pipelines, SageMaker Projects, and SageMaker Model Registry, build a foundation to implement enterprise-grade secure multi-account model deployment workflow.


Securing Amazon Comprehend API calls with AWS PrivateLink

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Amazon Comprehend now supports Amazon Virtual Private Cloud (Amazon VPC) endpoints via AWS PrivateLink so you can securely initiate API calls to Amazon Comprehend from within your VPC and avoid using the public internet. Amazon Comprehend is a fully managed natural language processing (NLP) service that uses machine learning (ML) to find meaning and insights in text. You can use Amazon Comprehend to analyze text documents and identify insights such as sentiment, people, brands, places, and topics in text. Using AWS PrivateLink, you can access Amazon Comprehend easily and securely by keeping your network traffic within the AWS network, while significantly simplifying your internal network architecture. It enables you to privately access Amazon Comprehend APIs from your VPC in a scalable manner by using interface VPC endpoints.