7/23/2026, 12:00:00 AM ~ 7/24/2026, 12:00:00 AM (UTC)

Recent Announcements

AWS now supports automatic credit memo application preferences

AWS now enables customers who pay through electronic funds transfer to configure preferences for how credit memos are automatically applied to outstanding invoices. Customers can choose from different application preferences directly on the Billing and Cost Management console to match their internal payment processes. These options include combinations of applying credit memos to the original invoice, next eligible invoice, and oldest unpaid invoice. By default, credit memos are applied to the original invoice first, then to future invoices, unless a different preference is selected.\n Automatic credit memo application preferences are available in all commercial AWS Regions. To get started, visit the Payment Preferences page in the AWS Billing and Cost Management console. To learn more, see Managing balance application preferences.

Amazon RDS for MySQL supports MySQL 9.7 in Amazon RDS Database Preview Environment

Amazon RDS for MySQL now supports version community MySQL 9.7 in the Amazon RDS Database Preview Environment, allowing you to evaluate the latest Release on Amazon RDS for MySQL. This preview environment provides a sandbox where you can test applications and explore new MySQL 9.7 capabilities before they become generally available.\n MySQL 9.7 is the latest Long-Term Support release for community MySQL. MySQL Long-Term Support releases include bug fixes, security patches, as well as new features. Please refer to the MySQL 9.7 release notes for more details about this release. Amazon RDS Database Preview Environment database instances are retained for a maximum of 60 days and are automatically deleted after the retention period. Amazon RDS database snapshots created in the preview environment can only be used to create or restore database instances within the preview environment. Amazon RDS Database Preview Environment database instances are priced the same as production RDS instances created in the US East (Ohio) Region. For further information, see Working with the Database Preview Environment.

Amazon Bedrock AgentCore now delivers unified observability with traces and logs in a single log group

Amazon Bedrock AgentCore now delivers agent traces and prompts to the same log group as your agent’s logs, giving you unified observability for AI agents in a single Amazon CloudWatch log group.\n Previously, AgentCore split agent telemetry across multiple destinations trace spans went to the shared aws/spans log group while event logs containing prompts, inputs, and outputs went to a separate resource-specific log group. This meant debugging an agent invocation required searching across multiple log groups, and customers could not apply fine-grained access control or customer-managed key (CMK) encryption at the individual agent level. With today’s launch, all of an agent’s telemetry traces, prompts, structured logs, and standard output is delivered to a single per-agent log group (/aws/bedrock-agentcore/runtimes/<agent_id>-<endpoint_name>). You can now correlate traces and logs in one place, scope IAM policies and CMK encryption to individual agents, and export all telemetry by subscribing to a single log group. For multi-agent systems, each agent’s complete execution history stays together, making end-to-end debugging straightforward.

All newly created agents starting July 20, 2026 in supported AWS Regions use unified observability by default starting no configuration needed. For existing agents, set the UNIFIED_TRACES_DESTINATION_ENABLED=true environment variable on your agent runtime and upgrade ADOT to version 0.17.1 or later. This feature is available in all AWS commercial regions where AgentCore runtime is supported. Learn more in the AgentCore Developer Guide.

Amazon EVS is now available in additional Regions

Today, we’re announcing that Amazon Elastic VMware Service (Amazon EVS) is now available in the Asia Pacific (Seoul), Europe (Zurich), and Europe (Stockholm) Regions. This expansion provides more options to leverage the scale and flexibility of AWS for running your VMware workloads in the cloud.\n Amazon EVS lets you run VMware Cloud Foundation (VCF) directly within your Amazon Virtual Private Cloud (VPC) on EC2 bare-metal instances, powered by AWS Nitro. You can set up a complete VCF environment in just a few hours, enabling rapid workload migration to AWS to help you eliminate aging infrastructure, reduce operational risks, and meet critical timelines for exiting your data center. This launch supports all existing Amazon EVS features, including VCF 9.0 and 9.1 support to take advantage of the latest VMware features, such as memory tiering. The added availability in these Regions gives your VMware workloads lower latency through closer proximity to your end users, compliance with data residency or sovereignty requirements, and additional high availability and resiliency options for your enhanced redundancy strategy. To get started, visit the Amazon EVS product detail page and user guide.

Claude Sonnet 5 is now available on Amazon Bedrock in AWS GovCloud (US)

AWS GovCloud (US) now offers Claude Sonnet 5 on Amazon Bedrock. Claude Sonnet 5 delivers strong performance across coding, professional work, and agentic tasks while maintaining the balance of capability, cost, and speed. For coding, it navigates large codebases, lands multi-file changes, and carries debugging and refactoring tasks through to completion with fewer rounds of correction. For agents, it calls tools precisely, holds state across many steps, and recovers from errors so more runs finish correctly the first time. For knowledge work, it builds spreadsheets, drafts documents, and turns unstructured material into structured analysis. \n With this launch, Claude Opus 4.8 and Claude Sonnet 5 are available on bedrock-runtime endpoints in AWS GovCloud (US-West and US-East) and bedrock-mantle endpoints in AWS GovCloud (US-West) for performing inference. Bedrock Mantle, Amazon Bedorck’s next-generation inference engine, supports the Anthropic Messages API. Amazon Bedrock keeps your data within AWS infrastructure and provides access to Claude Sonnet 5 through a unified service with AWS-managed features like Guardrails, Knowledge Bases, and regional data residency. To learn more, see the Amazon Bedrock documentation and regional availability.

Announcing region expansion of G7e instances on SageMaker AI inference

We are pleased to announce the availability of Amazon EC2 G7e instances in Asia Pacific (Seoul), Europe (London), and Asia Pacific (Tokyo) on Amazon SageMaker AI inference. G7e instances feature up to 8 NVIDIA RTX PRO 6000 Blackwell Server Edition GPUs with 96 GB of memory per GPU, 5th Generation Intel Xeon processors, and up to 1,600 Gbps of Elastic Fabric Adapter networking bandwidth, delivering up to 2.3x inference performance compared to previous-generation G6e instances.\n With this region expansion, you can now deploy inference endpoints on G7e instances closer to your end users in Asia and Europe, reducing latency for generative AI workloads. G7e instances provide up to 768 GB of total GPU memory on a single instance, enabling you to serve medium-to-large language models of up to 70B parameters with FP8 precision without multi-node configurations. These instances are well suited for LLM inference, image and video generation, spatial computing, and scientific computing workloads that require high GPU memory capacity and bandwidth. G7e instances for SageMaker AI inference are now available in Asia Pacific (Seoul), Europe (London), and Asia Pacific (Tokyo), in addition to previously supported regions. For pricing information on these instances, please visit our pricing page.

Announcing region expansion of G6 instances on SageMaker AI Inference

We are pleased to announce the availability of Amazon EC2 G6 instances in the AWS GovCloud (US-East) region on Amazon SageMaker AI inference. G6 instances are powered by up to 8 NVIDIA L4 Tensor Core GPUs, each with 24 GB of memory, and third-generation AMD EPYC processors, delivering up to 2x the deep learning inference performance compared to G4dn instances.\n With this region expansion, government agencies and organizations operating in GovCloud can deploy inference endpoints on G6 instances to serve generative AI workloads—including small-to-medium language models, image generation, and computer vision tasks—while meeting strict compliance and data residency requirements. G6 instances offer strong price-performance for production inference workloads that fit within 24 GB of GPU memory. G6 instances for SageMaker AI inference are now available in AWS GovCloud (US-East), in addition to previously supported regions. For pricing information on these instances, please visit our pricing page.

AWS Wickr announces Data Retention Service feature

AWS Wickr now offers a managed Data Retention Service feature for Premium users, enabling organizations to retain conversations across their network for data archiving purposes. AWS Wickr is an enterprise-grade, secure collaboration product that provides end-to-end encrypted messaging, file management, screen sharing, and voice/video conferencing capabilities. The Data Retention Service feature provides a cloud-native alternative to traditional container-based data retention methods.\n The Data Retention Service can retain conversations in your network, including direct messages and conversations in Groups or Rooms between internal members and external federated teams. The serverless architecture offers simplified deployment, managed infrastructure, automatic scaling, and comprehensive monitoring while maintaining Wickr’s end-to-end encryption standards. This feature is particularly valuable for organizations that require comprehensive data archiving capabilities and maintaining audit trails.

AWS Wickr Premium customers can opt in to enable data retention for their networks. To learn more, visit the AWS Wickr documentation.

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