AWS Audit Manager is a new service that helps you continuously audit your AWS usage to simplify how you assess risk and compliance with regulations and industry standards. Audit Manager automates evidence collection to make it easier to assess whether your policies, procedures, and activities, also known as controls, are operating effectively. When it is time for an audit, AWS Audit Manager helps you manage stakeholder reviews of your controls and enables you to build audit-ready reports with much less manual effort and in less time.

Amazon SageMaker Model Monitor continuously monitors machine learning models for concept drift (i.e. changes in data distribution and characteristics over time) and alerts you if there are any deviations so you can take remedial action. Starting today, you can also use Amazon SageMaker Model Monitor to detect drift in model quality, bias, and feature importance. With these new fully managed capabilities, SageMaker Model Monitor helps you maintain high quality machine learning models in production.

Amazon Kendra is a highly accurate and easy to use intelligent search service powered by machine learning. Starting today, AWS customers can automatically index and search content that is contained in Google Drive repositories using Amazon Kendra’s new built-in Google Drive connector.

AWS Security Hub is now integrated with AWS Audit Manager, which helps simplify how you assess risk and monitor your compliance with regulations and industry standards. AWS Audit Manager is a new service that helps you continuously audit your AWS usage and automates evidence collection to make it easier for you to assess whether your policies, procedures, and activities are operating effectively. Using a prebuilt or customized framework, you can launch an Audit Manger assessment to begin collecting and organizing evidence, such as Security Hub findings, in accordance with the requirements of an industry standard or regulation, such as the Payment Card Industry Data Security Standard (PCI DSS) or the Center for Internet Security (CIS) AWS Foundations Benchmark standard. With Audit Manager, you can focus on reviewing the relevant evidence to ensure your controls are working as intended and build audit-ready reports with much less manual effort. For more information on AWS Audit Manager, see their documentation here .

We’re excited to announce Amazon SageMaker Feature Store, a new capability of Amazon SageMaker to ingest, store, share, reuse, and serve features for real time and batch machine learning (ML) applications.  

We’re excited to announce Amazon SageMaker Pipelines, a new capability of Amazon SageMaker to build, manage, automate, and scale end to end machine learning workflows. SageMaker Pipelines brings automation and orchestration to ML workflows, enabling you to accelerate machine learning projects and scale up to thousands of models in production.

Today we are introducing Amazon SageMaker Clarify to help machine learning developers achieve greater visibility into their training data and models so they can identify and limit bias and explain predictions.

Amazon HealthLake is a HIPAA-eligible service that enables healthcare providers, health insurance companies, and pharmaceutical companies to store, transform, query, and analyze health data at petabyte scale.

Amazon SageMaker Data Wrangler reduces the time it takes to aggregate and prepare data for machine learning (ML) from weeks to minutes. With Amazon SageMaker Data Wrangler, you can simplify the process of data preparation and feature engineering, and complete each step of the data preparation workflow, including data selection, cleansing, exploration, and visualization from a single visual interface.