Amazon Simple Email Service (SES) now offers a simplified console experience for sending emails over SMTP using Mail Manager. Mail Manager is a capability within SES for managing email flow, but configuring its resources individually to set up SMTP sending requires multiple steps. The new guided setup creates and configures these resources automatically, so developers can get started in just a few clicks.

The guided setup gives developers a working SMTP endpoint and downloadable credentials they can plug into any application or framework that supports SMTP. This is ideal for teams building applications that send email notifications, password resets, or transactional messages and need a fast path to a production-ready SMTP configuration.

This experience is available in all AWS Regions where Amazon SES is available.

To learn more, visit the Amazon SES console or refer to the documentation.

 

​Amazon Simple Email Service (SES) now offers a simplified console experience for sending emails over SMTP using Mail Manager. Mail Manager is a capability within SES for managing email flow, but configuring its resources individually to set up SMTP sending requires multiple steps. The new guided setup creates and configures these resources automatically, so developers can get started in just a few clicks.
The guided setup gives developers a working SMTP endpoint and downloadable credentials they can plug into any application or framework that supports SMTP. This is ideal for teams building applications that send email notifications, password resets, or transactional messages and need a fast path to a production-ready SMTP configuration.
This experience is available in all AWS Regions where Amazon SES is available.
To learn more, visit the Amazon SES console or refer to the documentation.  

Two new models are now available in the Kiro IDE and CLI for the AWS GovCloud (US) Regions.

Claude Opus 4.8 is the most intelligent Opus model, delivering stronger self-verification, more efficient tool calling, and better follow-through on long-horizon projects. It plans before it edits, catches its own mistakes, and finds creative paths around obstacles instead of stalling, making it well suited for complex multi-step tasks that previously required close supervision. Available with a 1M context window and 2.2x credit multiplier.

Claude Sonnet 5 is the most agentic Sonnet model, bringing stronger reasoning, tool use, and coding at Sonnet-class pricing. It approaches Opus 4.8 on reasoning and agentic coding benchmarks while running at meaningfully lower cost, giving developers a cost-performance dial between maximum accuracy and higher throughput. Available with experimental support, a 1M context window, and 1.3x credit multiplier.

Kiro enterprise administrators now have full visibility into organizational usage through built-in monitoring and tracking. A usage dashboard provides aggregate metrics at a glance, per-user activity reports deliver daily CSV telemetry (credits, model usage, and more) to your S3 bucket for license optimization and audit, and optional prompt logging captures user prompts and Kiro responses for compliance and debugging. All data is stored in your own account with no additional charge beyond S3 storage.

Ensure your IDE or CLI is updated to the latest version, then restart it to access the new models from the model selector. For more details, visit the GovCloud documentation, the monitoring and tracking guide, or contact your AWS account team. To learn more about Kiro, visit the Kiro product page.

 

​Two new models are now available in the Kiro IDE and CLI for the AWS GovCloud (US) Regions. Claude Opus 4.8 is the most intelligent Opus model, delivering stronger self-verification, more efficient tool calling, and better follow-through on long-horizon projects. It plans before it edits, catches its own mistakes, and finds creative paths around obstacles instead of stalling, making it well suited for complex multi-step tasks that previously required close supervision. Available with a 1M context window and 2.2x credit multiplier. Claude Sonnet 5 is the most agentic Sonnet model, bringing stronger reasoning, tool use, and coding at Sonnet-class pricing. It approaches Opus 4.8 on reasoning and agentic coding benchmarks while running at meaningfully lower cost, giving developers a cost-performance dial between maximum accuracy and higher throughput. Available with experimental support, a 1M context window, and 1.3x credit multiplier. Kiro enterprise administrators now have full visibility into organizational usage through built-in monitoring and tracking. A usage dashboard provides aggregate metrics at a glance, per-user activity reports deliver daily CSV telemetry (credits, model usage, and more) to your S3 bucket for license optimization and audit, and optional prompt logging captures user prompts and Kiro responses for compliance and debugging. All data is stored in your own account with no additional charge beyond S3 storage. Ensure your IDE or CLI is updated to the latest version, then restart it to access the new models from the model selector. For more details, visit the GovCloud documentation, the monitoring and tracking guide, or contact your AWS account team. To learn more about Kiro, visit the Kiro product page.  

AWS now offers Claude Opus 5 — the most advanced Opus model yet, and compatible with zero data retention (ZDR) — bringing a step-change in coding, long-running agents, and complex professional work to teams building at the highest level. 

Claude Opus 5 delivers advances in coding, understanding and navigating codebases like an experienced engineer and writing production-quality code while adapting its strategy as it works. It powers dependable agents that run for hours and even overnight, finding paths around obstacles, recovering from errors, and reaching their objectives. And it brings deeper reasoning to long documents and higher accuracy to complex analysis, with the largest gains on document-heavy enterprise work. 

Customers have two ways to access Claude Opus 5: Amazon Bedrock and Claude Platform on AWS. 

Amazon Bedrock offers Claude Opus 5 with zero data retention (ZDR) enabled by default, giving you Opus’ top-tier intelligence while meeting your data governance requirements. It keeps your data within AWS infrastructure with regional data residency, and provides access through a unified service with AWS-managed features like Guardrails and Knowledge Bases. To learn more, see the Amazon Bedrock documentation and regional availability.

Claude Platform on AWS gives you direct access to Anthropic’s native platform experience and capabilities via the AWS Console, with support for zero data retention (ZDR) available on request. Build, test, and deploy with the same APIs, features, and console experience you’d get working with Anthropic directly, unified with AWS billing and authentication. To get started, see the Claude Platform on AWS documentation. 

 

​AWS now offers Claude Opus 5 — the most advanced Opus model yet, and compatible with zero data retention (ZDR) — bringing a step-change in coding, long-running agents, and complex professional work to teams building at the highest level. 
Claude Opus 5 delivers advances in coding, understanding and navigating codebases like an experienced engineer and writing production-quality code while adapting its strategy as it works. It powers dependable agents that run for hours and even overnight, finding paths around obstacles, recovering from errors, and reaching their objectives. And it brings deeper reasoning to long documents and higher accuracy to complex analysis, with the largest gains on document-heavy enterprise work. 
Customers have two ways to access Claude Opus 5: Amazon Bedrock and Claude Platform on AWS. 
Amazon Bedrock offers Claude Opus 5 with zero data retention (ZDR) enabled by default, giving you Opus’ top-tier intelligence while meeting your data governance requirements. It keeps your data within AWS infrastructure with regional data residency, and provides access through a unified service with AWS-managed features like Guardrails and Knowledge Bases. To learn more, see the Amazon Bedrock documentation and regional availability.
Claude Platform on AWS gives you direct access to Anthropic’s native platform experience and capabilities via the AWS Console, with support for zero data retention (ZDR) available on request. Build, test, and deploy with the same APIs, features, and console experience you’d get working with Anthropic directly, unified with AWS billing and authentication. To get started, see the Claude Platform on AWS documentation.   

Today, AWS announces a research preview of aws-bench, an open-source benchmark that measures how accurately and efficiently AI agents complete real-world AWS tasks. Model providers and AI researchers building agents that operate on AWS infrastructure need an objective, reproducible way to measure performance and diagnose failures. aws-bench provides a public suite of test cases derived from analysis of real AWS usage, including investigation, troubleshooting, and infrastructure creation tasks.

Each test case pairs a natural-language query with a defined cloud resource state and a ground-truth answer, so you can score any agent or model on a consistent, verifiable basis. Researchers and model providers can use aws-bench to improve foundation model performance on AWS tasks, improve agent harnesses, and track improvement progress. The release includes an easy-to-use CLI tool to instantiate testing environments, execute and score evaluation runs, and reset resource state.

aws-bench is available now on GitHub. To get started, follow the setup instructions on the README. 

 

​Today, AWS announces a research preview of aws-bench, an open-source benchmark that measures how accurately and efficiently AI agents complete real-world AWS tasks. Model providers and AI researchers building agents that operate on AWS infrastructure need an objective, reproducible way to measure performance and diagnose failures. aws-bench provides a public suite of test cases derived from analysis of real AWS usage, including investigation, troubleshooting, and infrastructure creation tasks. Each test case pairs a natural-language query with a defined cloud resource state and a ground-truth answer, so you can score any agent or model on a consistent, verifiable basis. Researchers and model providers can use aws-bench to improve foundation model performance on AWS tasks, improve agent harnesses, and track improvement progress. The release includes an easy-to-use CLI tool to instantiate testing environments, execute and score evaluation runs, and reset resource state. aws-bench is available now on GitHub. To get started, follow the setup instructions on the README.   

Today, AWS announces the general availability of the AWS Lambda Durable Execution SDK for .NET, empowering C# developers to build resilient, long-running workflows using Lambda durable functions. With this SDK, developers can create multi-step applications like payment processing pipelines, AI agent orchestration, and human-in-the-loop approvals directly in their applications without implementing custom progress tracking or integrating external orchestration services. 

Lambda durable functions extend Lambda’s event-driven programming model with operations that checkpoint progress automatically and pause execution for up to a year when waiting on external events. The AWS Lambda Durable Execution SDK for .NET provides an idiomatic C# experience for building with Lambda durable functions. It includes steps for progress tracking, callback integration for human and agent-in-the-loop workflows, durable invocation for reliable function chaining, and waits for efficient suspension. The SDK installs from NuGet into the .NET toolchain you use today. The local testing emulator in the SDK enables developers to build and debug locally before deploying to production.

To get started, see the Lambda durable functions developer guide and the AWS Lambda Durable Execution SDK for .NET on NuGet. For Regional availability and pricing details, see the AWS Regional Services List and AWS Lambda Pricing.

 

 

​Today, AWS announces the general availability of the AWS Lambda Durable Execution SDK for .NET, empowering C# developers to build resilient, long-running workflows using Lambda durable functions. With this SDK, developers can create multi-step applications like payment processing pipelines, AI agent orchestration, and human-in-the-loop approvals directly in their applications without implementing custom progress tracking or integrating external orchestration services. 
Lambda durable functions extend Lambda’s event-driven programming model with operations that checkpoint progress automatically and pause execution for up to a year when waiting on external events. The AWS Lambda Durable Execution SDK for .NET provides an idiomatic C# experience for building with Lambda durable functions. It includes steps for progress tracking, callback integration for human and agent-in-the-loop workflows, durable invocation for reliable function chaining, and waits for efficient suspension. The SDK installs from NuGet into the .NET toolchain you use today. The local testing emulator in the SDK enables developers to build and debug locally before deploying to production.
To get started, see the Lambda durable functions developer guide and the AWS Lambda Durable Execution SDK for .NET on NuGet. For Regional availability and pricing details, see the AWS Regional Services List and AWS Lambda Pricing.
   

Amazon CloudWatch Logs now supports Application Load Balancer (ALB) logs as vended logs, improving observability and simplifying debugging for network traffic patterns. You can now analyze ALB access, connection and health check logs directly in CloudWatch to gain insights into client connections, traffic distribution, connection status and target health, helping you identify and troubleshoot network issues faster. Additionally, you can set up CloudWatch telemetry enablement rules to automatically configure logging of both existing and newly created ALB resources, for your organization, specific accounts, or specific resources, ensuring consistent monitoring coverage without manual setup.

With this CloudWatch Logs integration, you can track detailed access patterns using CloudWatch Logs Insights queries, create metric filters for monitoring and alarming, and review traffic patterns in real time using Live Tail. ALB logs can be configured through the integrations tab of your application load balancer in AWS Management Console, AWS CLI, or SDKs. You can also configure delivery of ALB logs to Amazon Data Firehose or Amazon S3 with support for Apache Parquet format.

ALB logs delivery to CloudWatch is available in all AWS Commercial and GovCloud regions where Application Load Balancer and CloudWatch are available. ALB logs are charged as vended logs when delivered to CloudWatch Logs and Data Firehose, while delivery to Amazon S3 is free (Parquet conversion is charged at $0.035/GB – N. Virginia).

To learn more about configuring ALB logs in CloudWatch Logs, please visit our documentation. For pricing information, see CloudWatch pricing page.

 

​Amazon CloudWatch Logs now supports Application Load Balancer (ALB) logs as vended logs, improving observability and simplifying debugging for network traffic patterns. You can now analyze ALB access, connection and health check logs directly in CloudWatch to gain insights into client connections, traffic distribution, connection status and target health, helping you identify and troubleshoot network issues faster. Additionally, you can set up CloudWatch telemetry enablement rules to automatically configure logging of both existing and newly created ALB resources, for your organization, specific accounts, or specific resources, ensuring consistent monitoring coverage without manual setup. With this CloudWatch Logs integration, you can track detailed access patterns using CloudWatch Logs Insights queries, create metric filters for monitoring and alarming, and review traffic patterns in real time using Live Tail. ALB logs can be configured through the integrations tab of your application load balancer in AWS Management Console, AWS CLI, or SDKs. You can also configure delivery of ALB logs to Amazon Data Firehose or Amazon S3 with support for Apache Parquet format. ALB logs delivery to CloudWatch is available in all AWS Commercial and GovCloud regions where Application Load Balancer and CloudWatch are available. ALB logs are charged as vended logs when delivered to CloudWatch Logs and Data Firehose, while delivery to Amazon S3 is free (Parquet conversion is charged at $0.035/GB – N. Virginia). To learn more about configuring ALB logs in CloudWatch Logs, please visit our documentation. For pricing information, see CloudWatch pricing page.  

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.

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. 

 

​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. 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 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.

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 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. 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.  

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.

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. 

 

​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. 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.   

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.

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 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.
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.