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Amazon Connect Contact Lens supports new read-only permissions for reports and dashboards

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Amazon Connect Contact Lens now allows users to save and publish reports and dashboards as read-only. By publishing a report as read-only, only the user who created the report or dashboard can edit the report, while still making it visible for others to view or create a copy. For example, a contact center manager can configure a custom read-only dashboard and share it with the supervisors on their team to ensure they monitor the same metrics, while still allowing the supervisors to customize and save their own versions for further analysis.

This feature is available in all AWS regions where Amazon Connect is offered. To learn more about read only reports, see the Amazon Connect Administrator Guide . To learn more about Amazon Connect, the AWS cloud-based contact center, please visit the Amazon Connect website .

AWS CodePipeline introduces new general purpose compute action

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AWS CodePipeline introduces the Commands action that enables you to easily run shell commands as part of your pipeline execution. With the Commands action, you will have access to a secure compute environment backed by CodeBuild to run AWS CLI, third-party tools, or any shell commands. The Commands action runs CodeBuild managed on-demand EC2 compute, and uses an Amazon Linux 2023 standard 5.0 image .

Previously, if you wanted to run AWS CLI commands, third-party CLI commands, or simply invoke an API, you had to create a CodeBuild project, configure the project with the appropriate commands, and add a CodeBuild action to your pipeline to run the project. Now, you can simply add the Commands action to your pipeline, and define one or more commands as part of the action configuration. Since Commands is like any other CodePipeline action, you can use the standard CodePipeline features of input / output artifacts and output variables.

To learn more about using the Commands action in your pipeline, visit our documentation . For more information about AWS CodePipeline, visit our product page . The Commands action is available in all regions where AWS CodePipeline is supported.
 

Amazon Route 53 Resolver endpoints now support DNS-over-HTTPS (DoH) with Server Name Indication (SNI) validation

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Starting today, you can provide Server Name Indication (SNI) with Route 53 Resolver endpoints for DNS-over-HTTPS (DoH), allowing you to specify the target server hostname for DNS query requests from your outbound endpoints to DoH servers that require SNI for TLS validation.

DoH on Amazon Route 53 Resolver endpoints allows you to encrypt DNS queries that pass through the endpoints and improve privacy by minimizing the visibility of the information exchanged through the queries. With this launch, you can now specify the hostname with your outbound endpoint configuration to perform TLS handshakes for your DNS requests from the outbound endpoints to the DoH server. Enabling SNI validation for your DoH Resolver endpoints also helps you meet regulatory and business compliance requirements, such as those described in the memorandum of the US Office of Management and Budget, where outbound DNS traffic must be be addressed to Cybersecurity and Infrastructure Security Agency (CISA) Protective DNS that require SNI hostname validation for a successful TLS handshake.

Resolver endpoints support for DoH with SNI is available in all Regions where Route 53 is available, including the AWS GovCloud (US) Regions. Visit the AWS Region Table to see all AWS Regions where Amazon Route 53 is available.

You can get started by using the AWS Console or Route 53 API. For more information, visit the Route 53 Resolver product detail page and service documentation . For details on pricing, visit the pricing page .
 

Amazon SageMaker JumpStart is now available in the AWS GovCloud (US-West and US-East) Regions

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Amazon SageMaker JumpStart is now available in the AWS GovCloud (US) Regions. Public sector customers can easily deploy and fine-tune open-weight models through the SageMaker Python SDK.

Amazon SageMaker JumpStart is a machine learning (ML) hub that offers hundreds of pre-trained models and built-in algorithms to help you quickly get started with ML. Customers can discover hundreds of open-weight pre-trained models such as Llama and Mistral stored in the AWS infrastructure, fine-tune with their own data, and deploy for cost effective inferencing using SageMaker Python SDK.

Amazon SageMaker JumpStart is now Generally Available in the AWS GovCloud (US-West and US-East) Regions. Please note that some models require instances not yet available in GovCloud regions and will be usable after instances become available.

To learn more about using SageMaker JumpStart through SageMaker Python SDK, see the SageMaker Python SDK documentation . Available models can also be found in the documentation .

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