AWS News - 2026-06-01

Amazon Simple Email Service (Amazon SES) now supports tenant-level suppression lists, allowing email senders to isolate bounces and complaints per tenant. Previously, all tenants in an account shared a single suppression list, meaning one tenant's email issues caused emails for other tenants to be suppressed. With this feature, each tenant maintains a separate suppression list, ensuring that bounces and complaints affect only the tenant that generated them.

This capability benefits any sender managing distinct email streams from a single SES account. Key use cases include SaaS providers sending on behalf of multiple customers, enterprises separating transactional and marketing mail across business units, agencies managing campaigns for different brands, or any application where a complaint from one sending program shouldn't suppress delivery for another. 

You can configure suppression behavior using two settings: suppression scope (TENANT or ACCOUNT) and suppressed reasons (BOUNCE, COMPLAINT, or both). Amazon SES automatically records bounces and complaints to the appropriate tenant's list. You can also manually manage suppressed addresses using API operations including PutSuppressedDestination, GetSuppressedDestination, DeleteSuppressedDestination, and ListSuppressedDestinations with the TenantName parameter.

To learn more about tenant-level suppression lists in Amazon SES, visit the Amazon SES console or refer to the documentation.

You can now use GPT-5.5 and GPT-5.4 in production workloads on Amazon Bedrock and build with Codex for AI-powered software development, with the same security, governance, and operational controls you already use across AWS.

GPT-5.5 is the most capable model from OpenAI, excelling at agentic coding, data analysis, and multi-step autonomous tasks. It runs on the Bedrock next-generation inference engine, built for high performance, reliability, and security. Codex is available through the Codex App, the Codex CLI, and IDE integrations with Visual Studio Code, JetBrains, and Xcode. You can now configure Codex to run inference through Bedrock. Pricing matches OpenAI first-party rates, and usage counts toward existing AWS commitments.

For Regional availability of GPT-5.5 and GPT-5.4 see the AWS Regions page. Read the launch blog to learn more, for documentation and a step-by-step walkthrough, see the Amazon Bedrock docs and the getting started blog.

Amazon Bedrock is a fully managed service that provides secure, enterprise-grade access to high-performing foundation models from leading AI companies, enabling you to build and scale generative AI applications. Amazon Bedrock customers can now monitor inference traffic to the bedrock-mantle endpoint with Amazon CloudWatch metrics, the same way they already do for the bedrock-runtime endpoint and other AWS services. The bedrock-mantle endpoint supports the OpenAI Responses API, OpenAI Chat Completions API, and the Anthropic Messages API, letting customers run existing OpenAI- or Anthropic-based applications on Amazon Bedrock with minimal code changes.

CloudWatch metrics for the bedrock-mantle endpoint are published under the AWS/BedrockMantle namespace and include inference counts, input and output token totals, and client error counts. Metrics are published at multiple granularity levels, including account, project, model, and project-and-model, so customers can attribute usage and costs to the right workloads and teams.

With this launch, customers can monitor production inference, set up alarms, and plan capacity on the bedrock-mantle endpoint. To get started, open the Amazon CloudWatch console, choose Metrics, and select the AWS/BedrockMantle namespace to view metrics for your account. CloudWatch metrics for the bedrock-mantle endpoint are available in all AWS Regions where the endpoint is offered: US East (N. Virginia, Ohio), US West (Oregon), Asia Pacific (Jakarta, Mumbai, Sydney, Tokyo), Europe (Frankfurt, Ireland, London, Milan, Stockholm), and South America (São Paulo). To learn more, see CloudWatch metrics for the bedrock-mantle endpoint.

In my last Week in Review post, I shared what I’d been hearing from customers in the AI-Driven Development Lifecycle (AI-DLC) workshops I’ve been delivering. Last week I was back at it, this time in Denver for a two-day AI-DLC workshop, where I helped facilitate 17 teams to deliver nearly 20 separate use cases in […]

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