The semiconductor, electronics design and manufacturing industry association, SEMI, has announced that Greg Barrett will succeed Kevin Bauer as CFO (chief financial officer) and business operations officer. Before joining SEMI, …

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Amazon Connect now enables you to customize service level calculations to your specific needs. Supervisors and managers can define time thresholds for when a contact is considered to meet service level standards and select which contact outcomes to include in the calculation. For example, managers can choose to count callback contacts, exclude contacts transferred out while waiting in queue, and exclude short abandons using a configurable time threshold. Customization of service level calculation is available from the metric configuration section on the analytics dashboards.

With this feature supervisors and managers can now create a service level metric calculation that better aligns with their business operations. With a customized view of service level performance, operations managers can assess how effectively they have met their service standards.

This new feature is available in all AWS regions where Amazon Connect is offered. To learn more about customizing your service level calculation, visit the Admin Guide . To learn more about Amazon Connect, the easy-to-use cloud contact center, visit the Amazon Connect website .

AWS Directory Service now supports IPv6 connectivity for Managed Microsoft AD and AD Connector. The IPv6 capabilities allow customers to deploy directories with IPv4-only, IPv6-only, or dual-stack configurations, helping organizations meet government mandates and standardize on next-generation Internet protocol.

The IPv6 support helps organizations meet regulatory requirements, including U.S. federal agencies’ mandate to transition to IPv6 by 2025, while eliminating dual-protocol network complexity. This enables organizations to modernize their network infrastructure and comply with evolving security standards without maintaining separate IPv4 and IPv6 network stacks.

Customers can upgrade existing IPv4-only directories to dual-stack by enabling IPv6 in VPC subnets, then adding IPv6 support through the Directory Service Management Console. IPv6 capabilities are available in all AWS Directory Service regions , with IPv6 accessible through Console, CLI, and API.

To learn more, see the AWS Directory Service documentation .

Starting today, AWS End User Messaging customers can be notified of updates to their SMS onboarding progress in Slack, Email, or any other Amazon EventBridge destination. Before this launch, tracking the status of your onboarding progress was difficult. Customers had to periodically check the status of a phone number registration in the console. Now with this launch, you can be immediately notified when phone number or sender ID registrations in your AWS account are created, submitted, denied or requires an update.

AWS End User Messaging provides developers with a scalable and cost-effective messaging infrastructure without compromising the safety, security, or results of their communications. Developers can integrate messaging to support uses cases such as one-time passcodes (OTP) at sign-ups, account updates, appointment reminders, delivery notifications, promotions and more.

Support for EventBridge for SMS is available in all AWS Regions where End User Messaging is available, see the AWS Region table.

To learn more, see AWS End User Messaging .

Today, AWS announces the general availability of a self-service Invoice correction feature to update AWS invoices. This launch enables all AWS customers to correct key invoice attributes—including purchase order numbers, business legal name, and addresses — on their AWS invoices and get corrected invoices instantaneously.

AWS customers can now access the new self-service Invoice correction feature directly from the AWS Billing and Cost Management console. This feature offers AWS customers a guided self-service workflow to update invoice attributes in their account settings and on select invoices. This feature gives AWS customers direct control over invoice corrections while reducing wait times and improving efficiency in managing their AWS accounts.

AWS self-service Invoice Correction feature is generally available in all AWS Regions, excluding GovCloud (US) Regions and China (Beijing) and China (Ningxia) Regions.

To get started with AWS self-service invoice correction feature, please visit the product details page . 

EC2 Image Builder now automatically disables pipelines after consecutive failures and allows customers to configure custom log groups for image pipelines. These capabilities address common operational needs including improved control over pipeline execution, enhanced customization options for logging requirements, and better visibility.

Image Builder pipelines are used to automate the creation, testing, and distribution of custom images across your AWS infrastructure. With the new automatic disablement feature, you can configure pipelines to stop execution after a specified number of consecutive failures, preventing creation of unnecessary resources and reducing costs from repeatedly failed builds. Additionally, you can also configure custom log groups for pipelines with specific log retention periods and encryption settings that align with your organizational policies, providing you enhanced customization options for logging and better visibility. These enhancements collectively provide greater control and efficiency in managing your image building processes.

These capabilities are available to all customers at no additional costs, in all AWS commercial regions including AWS China (Beijing) Region, operated by Sinnet, AWS China (Ningxia) Region, operated by NWCD, and AWS GovCloud (US) Regions.

You can get started from the EC2 Image Builder Console, CLI, API, CloudFormation, or CDK, and learn more in the EC2 Image Builder documentation .

Today, AWS Clean Rooms announces support for cross-region data collaboration. This launch enables companies and their partners to easily collaborate with data sources stored in different regions, without having to move, copy, or share their underlying data.

With AWS Clean Rooms support for cross-region data collaboration, organizations can collaborate with their partners by leveraging datasets stored in regions outside of their own. Companies can collaborate with data sources stored in different AWS and Snowflake Regions from where their collaboration is hosted, eliminating the need to move or replicate data across regions to collaborate with their partners. Collaboration creators can control where their analysis results are delivered by configuring a set of allowed regions, helping each collaborator comply with applicable data residency requirements and sovereignty laws. For example, a media publisher with data stored in US East (N. Virginia) can collaborate with an advertising partner whose data resides in EU Central (Frankfurt) without building additional data pipelines or sharing underlying data with one another.

With AWS Clean Rooms, customers can create a secure data clean room in minutes and collaborate with any company on AWS or Snowflake to generate unique insights about advertising campaigns, investment decisions, and research and development. For more information about the AWS Regions where AWS Clean Rooms is available, see the AWS Regions table. To learn more about collaborating with AWS Clean Rooms, visit AWS Clean Rooms .

Amazon Connect now provides agents with generative AI-powered email conversation overviews, suggested actions, and responses. This enables agents to handle emails more efficiently, and customers to receive faster, more consistent support. For example, when a customer emails about a refund request, Amazon Connect automatically provides key details about the customer’s purchase history, recommends a refund resolution step-by-step guide, and generates an email response to help resolve the contact quickly.

To enable this feature, add the Amazon Q in Connect block to your flows before an email contact is assigned to your agent. You can customize the outputs of your email generative AI-powered assistant by adding knowledge bases and defining your prompts to guide the AI agent with generating responses that match your company’s language, tone, and policies for consistent customer service.

This new feature is available in all AWS regions where Amazon Q in Connect is available . To learn more and get started, refer to the help documentation , pricing page , or visit the Amazon Connect website.

AWS Glue adds write operations support for SAP OData, Adobe Marketo Engage, Salesforce Marketing Cloud, and HubSpot connectors. This allows you to not only extract data from those applications, but also write data to them directly from your AWS Glue ETL jobs.

With the new write functionality you can create and update records in SAP systems; sync leads into Adobe Marketo Engage; updating subscriber and campaign data in Salesforce Marketing Cloud; manage contacts, companies, and deals in HubSpot; and more.

This feature simplifies building end-to-end ETL pipelines that both extract data from and write processed results back to target applications, eliminating the need for custom scripts or intermediate systems.

Write operations support for SAP OData, Adobe Marketo Engage, Salesforce Marketing Cloud, and HubSpot connectors is available in all Regions where AWS Glue is available. To learn more and see the list of supported entities, visit AWS Glue documentation .

You can now perform batch AI inference within Amazon OpenSearch Ingestion pipelines to efficiently enrich and ingest large datasets for Amazon OpenSearch Service domains.

Previously, customers used OpenSearch’s AI connectors to Amazon Bedrock, Amazon SageMaker, and 3rd-party services for real-time inference. Inferences generate enrichments such as vector embeddings, predictions, translations, and recommendations to power AI use cases. Real-time inference is ideal for low-latency requirements such as streaming enrichments. Batch inference is ideal for enriching large datasets offline, delivering higher performance and cost efficiency. You can now use the same AI connectors with Amazon OpenSearch Ingestion pipelines as an asynchronous batch inference job to enrich large datasets such as generating and ingesting up to billions of vector embeddings.

This feature is available in all regions that support Amazon OpenSearch Ingestion and 2.17+ domains. Learn more from the documentation .