Amazon Redshift announces CONJUNCTION TYPE support for row-level security (RLS) policies and RLS support on standard views and late binding views, which enables you to apply granular access controls and ensure that users can only access rows that they are authorized to see, even when the underlying data evolves or user permissions change. 

Amazon Redshift now supports metadata security that enables administrators to restrict the visibility on their catalog data based on user roles and permissions. Users can now see only the metadata for databases, schema, and tables/views that they have access to. It enables customers to deploy multi-tenant applications on a provisioned cluster or Serverless namespace. 

Today, AWS announces the availability of AWS Solution Building Enablement. This release provides AWS Partners prescriptive steps and self-serve assets to build and validate industry solutions across all business models.

Today, Amazon Redshift announces enhanced manageability and monitoring for features for Amazon Redshift Serverless , including cross-account cross-VPC, custom domain name(CNAME), snapshot scheduling, cross-region copy (CRC), improved visibility for serverless billing in the Redshift console, and version tracking. These features provide you with seamless data access, robust data protection, and cost-effective operations.

Today, AWS announces the general availability of myApplications, a new experience in the AWS Management Console that makes it easier to manage and monitor the cost, health, security posture, and performance of your applications. Now, you can create your applications more easily and see your applications in an AWS account from one view in the AWS Management Console. With an at-a-glance view of key application metrics such as cost, performance, and security findings, you can debug operational issues and optimize your applications. You can also act on specific application resources with one click from the application dashboard using the corresponding AWS services, such as AWS Cost Explorer for cost, AWS Security Hub for security findings, and Amazon CloudWatch Application Signals for application performance.

Built on best practices from operating thousands of applications at Amazon, Amazon CloudWatch Application Signals (Preview) is a new capability that makes it easy to automatically instrument and operate applications on AWS. You can track application performance against your most important business objectives without the undifferentiated heavy lifting of manual instrumentation, metrics computations, and correlating observed problem to root cause. CloudWatch Application Signals provides standardized metrics such as volume, latency, and errors for each of your applications with pre built dashboards. In as few as three clicks, you can spot anomalies, drill into the most important metrics, and identify the root cause of issues with correlated metrics logs and traces. 

Today, AWS announces the general availability of a new integrated development environment (IDE) option in Amazon SageMaker Studio: Code Editor, based on Code-OSS (Visual Studio Code – Open Source). You can now boost your analytics and machine learning (ML) teams’ productivity by using the lightweight and powerful IDE with its familiar shortcuts and terminal as well as its advanced debugging capabilities and refactoring tools.

Today, Amazon Web Services, Inc. launches the general availability of Application Composer in VS Code, available as part of the AWS Toolkit. You can use AWS Application Composer’s drag-and-drop interface to create an application design from scratch or import an existing application definition to edit it. 

Starting today, SageMaker Studio offers a suite of IDEs, including Code Editor based on Code-OSS Visual Studio Code Open Source, improved and faster JupyterLab, and RStudio. ML practitioners can choose their preferred IDE to accelerate ML development, for example, a data scientist could use JupyterLab and training jobs in Studio to explore data and tune models, while an MLOPs engineer could choose the Code Editor and the pipelines tool in Studio to deploy and monitor models in production. Your IDE will open in a separate tab allowing users to work with a full screen experience. Additionally, users can now view their training jobs, including jobs they may have scheduled from notebooks and training jobs they may have initiated from JumpStart. We are also excited to announce a new interactive experience in SageMaker Studio to deploy models with optimal configurations in as little as three clicks. Users can also now monitor and manage their endpoints in Studio without having to navigate to AWS Console. SageMaker Studio comes with an improved JumpStart experience. It is now easy to discover, import, fine tune and deploy a foundational model with just a few clicks.

Today, we are excited to announce a new onboarding and administration experience that makes it easy to setup and manage Amazon SageMaker domains. The setup and onboarding flow on console has been redesigned from the ground up to provide a friendlier one click experience for individual users and a step-by-step guide for Enterprise ML Administrators (Admins).