AWS CloudFormation and CDK express mode reduces deployment time by up to 4x for developers and AI agents building infrastructure, based on internal benchmarks. Express mode completes stack operations when CloudFormation confirms resource configuration is applied, rather than waiting for extended stabilization checks such as traffic readiness, region propagation, and resource cleanup. This enables faster iteration cycles for developers and AI agents building infrastructure.

When iterating on infrastructure in development environments, developers and AI agents need faster iteration cycles to build infrastructure incrementally. Previously, every deployment waited for full resource stabilization regardless of whether the workflow required it. For example, creating a CloudFront distribution required waiting 5-10 minutes for propagation to all edge locations before the deployment completed, even when the developer only needed the distribution domain name to continue. With express mode, deployments complete in seconds once configuration is applied, and propagation continues in the background. CloudFormation still processes resources in dependency order and handles dependent resource failures within the same stack. Express mode disables rollback by default, enabling immediate fix-and-retry without waiting for rollback operations.

To get started, set –deployment-config ‘{«mode»: «EXPRESS»}’ when creating, updating, and deleting stacks or creating a change set through the AWS CLI, AWS SDKs, or the AWS Management Console. For AWS CDK users, activate express mode with cdk deploy –express. No template changes are required. Express mode works with all existing CloudFormation templates, and nested stacks. Visit the CloudFormation Express mode documentation to learn more.

This feature is available in all AWS Regions where CloudFormation is supported. Refer to the AWS Region table for service availability details.

 

​AWS CloudFormation and CDK express mode reduces deployment time by up to 4x for developers and AI agents building infrastructure, based on internal benchmarks. Express mode completes stack operations when CloudFormation confirms resource configuration is applied, rather than waiting for extended stabilization checks such as traffic readiness, region propagation, and resource cleanup. This enables faster iteration cycles for developers and AI agents building infrastructure. When iterating on infrastructure in development environments, developers and AI agents need faster iteration cycles to build infrastructure incrementally. Previously, every deployment waited for full resource stabilization regardless of whether the workflow required it. For example, creating a CloudFront distribution required waiting 5-10 minutes for propagation to all edge locations before the deployment completed, even when the developer only needed the distribution domain name to continue. With express mode, deployments complete in seconds once configuration is applied, and propagation continues in the background. CloudFormation still processes resources in dependency order and handles dependent resource failures within the same stack. Express mode disables rollback by default, enabling immediate fix-and-retry without waiting for rollback operations. To get started, set –deployment-config ‘{«mode»: «EXPRESS»}’ when creating, updating, and deleting stacks or creating a change set through the AWS CLI, AWS SDKs, or the AWS Management Console. For AWS CDK users, activate express mode with cdk deploy –express. No template changes are required. Express mode works with all existing CloudFormation templates, and nested stacks. Visit the CloudFormation Express mode documentation to learn more. This feature is available in all AWS Regions where CloudFormation is supported. Refer to the AWS Region table for service availability details.  

AWS CloudFormation customers can now get immediate feedback on deployment errors in seconds, eliminating the need to wait through a full provision-and-rollback cycle to discover preventable failures. CloudFormation now runs pre-deployment validation on Create Stack and Update Stack operations, catching common deployment errors before resource provisioning begins. This accelerates development velocity across all deployment workflows, from manual iteration to CI/CD pipelines to AI agents provisioning infrastructure.

Previously, pre-deployment validation was available during change set creation, covering property syntax errors, resource name conflicts, and S3 bucket emptiness constraints. With this release, the same validations now run automatically on Create Stack and Update Stack operations. Additionally, three new validation checks are now available as warnings during change set creation. Service quota limits validation warns when creating resources would exceed your account’s service quotas. AWS Config Recorder conflict detection warns when your template adds Config rules to an account that does not have Config recording enabled, or defines a Config Recorder in an account where one is already active. ECR repository delete readiness validation warns when an ECR repository targeted for deletion still contains images. When validation detects an issue, you can view errors using the DescribeEvents API with the operation ID, or in the CloudFormation console by navigating to your stack’s Events tab and clicking the operation ID (or the link in the banner or status reason column) to open the Operation view page, which opens directly on the Deployment validations tab. Each error includes the logical resource ID and property path, so you can pinpoint and fix the problem before any resources are provisioned. In CDK, both cdk deploy and cdk validate surface validation results with construct-level tracing in a unified report, so AI agents and automation tools can parse structured responses and self-correct immediately.

Pre-deployment validation is enabled by default on all stack operations with no configuration required. If you need to skip validation for a specific operation, use the new DisableValidation parameter on CreateStack, UpdateStack and CreateChangeSet API calls, or the –disable-validation flag in the CLI. Visit the Validate stack deployments User Guide to learn more.

This feature is available in all AWS Regions where CloudFormation is supported, excluding China. Refer to the AWS Region table for service availability details.

 

​AWS CloudFormation customers can now get immediate feedback on deployment errors in seconds, eliminating the need to wait through a full provision-and-rollback cycle to discover preventable failures. CloudFormation now runs pre-deployment validation on Create Stack and Update Stack operations, catching common deployment errors before resource provisioning begins. This accelerates development velocity across all deployment workflows, from manual iteration to CI/CD pipelines to AI agents provisioning infrastructure. Previously, pre-deployment validation was available during change set creation, covering property syntax errors, resource name conflicts, and S3 bucket emptiness constraints. With this release, the same validations now run automatically on Create Stack and Update Stack operations. Additionally, three new validation checks are now available as warnings during change set creation. Service quota limits validation warns when creating resources would exceed your account’s service quotas. AWS Config Recorder conflict detection warns when your template adds Config rules to an account that does not have Config recording enabled, or defines a Config Recorder in an account where one is already active. ECR repository delete readiness validation warns when an ECR repository targeted for deletion still contains images. When validation detects an issue, you can view errors using the DescribeEvents API with the operation ID, or in the CloudFormation console by navigating to your stack’s Events tab and clicking the operation ID (or the link in the banner or status reason column) to open the Operation view page, which opens directly on the Deployment validations tab. Each error includes the logical resource ID and property path, so you can pinpoint and fix the problem before any resources are provisioned. In CDK, both cdk deploy and cdk validate surface validation results with construct-level tracing in a unified report, so AI agents and automation tools can parse structured responses and self-correct immediately. Pre-deployment validation is enabled by default on all stack operations with no configuration required. If you need to skip validation for a specific operation, use the new DisableValidation parameter on CreateStack, UpdateStack and CreateChangeSet API calls, or the –disable-validation flag in the CLI. Visit the Validate stack deployments User Guide to learn more. This feature is available in all AWS Regions where CloudFormation is supported, excluding China. Refer to the AWS Region table for service availability details.  

Amazon Relational Database Service (Amazon RDS) now offers dynamic connection scaling for IAM database authentication, allowing connection rates to scale with instance resources.

IAM database authentication performance now scales with available instance resources, enabling enterprise workloads to leverage IAM authentication for high-volume connection patterns. The number of new IAM authentication requests your instance can handle depends on available resources and workload characteristics. For optimal performance, we recommend reusing IAM user or IAM assumed role principals to generate authentication tokens, or reusing the authentication tokens themselves, when possible.

This update is available in all AWS Regions, including the AWS GovCloud (US) Regions, where IAM database authentication is supported for Amazon Aurora and Amazon RDS database engines including PostgreSQL, MySQL, and MariaDB. To learn more, visit the IAM database authentication documentation.

 

​Amazon Relational Database Service (Amazon RDS) now offers dynamic connection scaling for IAM database authentication, allowing connection rates to scale with instance resources. IAM database authentication performance now scales with available instance resources, enabling enterprise workloads to leverage IAM authentication for high-volume connection patterns. The number of new IAM authentication requests your instance can handle depends on available resources and workload characteristics. For optimal performance, we recommend reusing IAM user or IAM assumed role principals to generate authentication tokens, or reusing the authentication tokens themselves, when possible. This update is available in all AWS Regions, including the AWS GovCloud (US) Regions, where IAM database authentication is supported for Amazon Aurora and Amazon RDS database engines including PostgreSQL, MySQL, and MariaDB. To learn more, visit the IAM database authentication documentation.  

AWS Parallel Computing Service (PCS) now supports managed in-place Slurm version upgrades for existing clusters. You can move your clusters up to three Slurm major versions ahead with no disruption to running jobs.

To upgrade, update your Cluster configuration with your target Slurm version using the AWS Management Console, AWS CLI, or UpdateCluster API. PCS handles the upgrade of all managed Slurm components — the controller, accounting database, and REST API. Running jobs continue uninterrupted during the upgrade, queued jobs resume once the operation completes, and any accounting data is preserved in the database. You can then update your compute nodes to the new Slurm version at your convenience. Refer to the PCS User Guide for more information on the steps to follow and considerations to review based on your cluster configuration.

AWS PCS is a managed service that simplifies running and scaling HPC workloads on AWS using Slurm. You can build complete, elastic environments that integrate compute, storage, networking, and visualization tools, while the service handles cluster operations with managed updates and built-in observability features.

This feature is available in all AWS Regions where PCS is available. To get started, see the PCS User Guide.

 

​AWS Parallel Computing Service (PCS) now supports managed in-place Slurm version upgrades for existing clusters. You can move your clusters up to three Slurm major versions ahead with no disruption to running jobs. To upgrade, update your Cluster configuration with your target Slurm version using the AWS Management Console, AWS CLI, or UpdateCluster API. PCS handles the upgrade of all managed Slurm components — the controller, accounting database, and REST API. Running jobs continue uninterrupted during the upgrade, queued jobs resume once the operation completes, and any accounting data is preserved in the database. You can then update your compute nodes to the new Slurm version at your convenience. Refer to the PCS User Guide for more information on the steps to follow and considerations to review based on your cluster configuration. AWS PCS is a managed service that simplifies running and scaling HPC workloads on AWS using Slurm. You can build complete, elastic environments that integrate compute, storage, networking, and visualization tools, while the service handles cluster operations with managed updates and built-in observability features. This feature is available in all AWS Regions where PCS is available. To get started, see the PCS User Guide.  

Amazon ElastiCache now supports T4g node types in the following AWS Regions: Africa (Cape Town), Asia Pacific (Jakarta), Asia Pacific (Osaka), AWS GovCloud (US-East), and AWS GovCloud (US-West). T4g nodes are powered by AWS Graviton2 processors and provide a baseline level of CPU performance with the ability to burst CPU usage at any time, making them ideal for applications that experience temporary spikes in usage.

For complete information on pricing and regional availability, please refer to the Amazon ElastiCache pricing page. To get started, create a new cluster or modify an existing cluster using the AWS Management Console, AWS CLI, or API. To learn more, see Supported node types in the Amazon ElastiCache User Guide.

 

​Amazon ElastiCache now supports T4g node types in the following AWS Regions: Africa (Cape Town), Asia Pacific (Jakarta), Asia Pacific (Osaka), AWS GovCloud (US-East), and AWS GovCloud (US-West). T4g nodes are powered by AWS Graviton2 processors and provide a baseline level of CPU performance with the ability to burst CPU usage at any time, making them ideal for applications that experience temporary spikes in usage.
For complete information on pricing and regional availability, please refer to the Amazon ElastiCache pricing page. To get started, create a new cluster or modify an existing cluster using the AWS Management Console, AWS CLI, or API. To learn more, see Supported node types in the Amazon ElastiCache User Guide.  

Amazon Neptune now supports dual-stack mode, enabling database clusters to accept connections over IPv4, IPv6, or both protocols simultaneously. This allows organizations to adopt IPv6 while maintaining backward compatibility with existing IPv4 deployments.

Neptune dual-stack mode supports two configurations. Private dual-stack mode provides IPv6 endpoints that remain isolated from the internet, suitable for internal applications and private graph databases. Public dual-stack mode enables IPv6 endpoints accessible from the internet, supporting internet-facing applications and hybrid network environments. Clients connect seamlessly using their preferred protocol with no application changes required.

Dual-stack mode is available in all AWS Regions where Amazon Neptune is supported. To get started, see the Neptune setup documentation.

 

​Amazon Neptune now supports dual-stack mode, enabling database clusters to accept connections over IPv4, IPv6, or both protocols simultaneously. This allows organizations to adopt IPv6 while maintaining backward compatibility with existing IPv4 deployments. Neptune dual-stack mode supports two configurations. Private dual-stack mode provides IPv6 endpoints that remain isolated from the internet, suitable for internal applications and private graph databases. Public dual-stack mode enables IPv6 endpoints accessible from the internet, supporting internet-facing applications and hybrid network environments. Clients connect seamlessly using their preferred protocol with no application changes required. Dual-stack mode is available in all AWS Regions where Amazon Neptune is supported. To get started, see the Neptune setup documentation.  

AWS End User Messaging now supports rich media and interactive messaging for RCS across all 22 supported countries. With the new SendRcsMessage API, you can send rich cards, carousels, images, videos, and interactive suggestion buttons that let recipients take action directly inside their messaging app.

RCS message recipients can tap to confirm an appointment, browse a product catalog, complete a payment in a webview, share their location, or interact with an AI agent, all without leaving their phone’s messaging app. Behind each of these interactions is the same AWS infrastructure you already use to build applications. RCS becomes the interface layer that connects your backend services, your data, and your AI directly to your end users through your conversation with them.

With this release AWS now supports four RCS message types (text, files, rich cards, and carousels). These message types can be used with any combination of six actions (replies, URLs, webviews, phone calls, maps, and calendar events) to bring web and mobile app experiences directly into conversations.. Each message supports configurable SMS or MMS fallback for recipients without RCS.

AWS End User Messaging also introduces RCS Conversation pricing for 21 countries consisting of one flat rate for unlimited messages within a 24-hour session, so you can build back-and-forth workflows without per-message cost pressure.

RCS messaging is available in all AWS Regions where AWS End User Messaging is available. To learn more, see sending rich RCS messages in the AWS End User Messaging User Guide.

 

 

​AWS End User Messaging now supports rich media and interactive messaging for RCS across all 22 supported countries. With the new SendRcsMessage API, you can send rich cards, carousels, images, videos, and interactive suggestion buttons that let recipients take action directly inside their messaging app.
RCS message recipients can tap to confirm an appointment, browse a product catalog, complete a payment in a webview, share their location, or interact with an AI agent, all without leaving their phone’s messaging app. Behind each of these interactions is the same AWS infrastructure you already use to build applications. RCS becomes the interface layer that connects your backend services, your data, and your AI directly to your end users through your conversation with them.
With this release AWS now supports four RCS message types (text, files, rich cards, and carousels). These message types can be used with any combination of six actions (replies, URLs, webviews, phone calls, maps, and calendar events) to bring web and mobile app experiences directly into conversations.. Each message supports configurable SMS or MMS fallback for recipients without RCS.
AWS End User Messaging also introduces RCS Conversation pricing for 21 countries consisting of one flat rate for unlimited messages within a 24-hour session, so you can build back-and-forth workflows without per-message cost pressure.
RCS messaging is available in all AWS Regions where AWS End User Messaging is available. To learn more, see sending rich RCS messages in the AWS End User Messaging User Guide.
   

Announcing Capability Insights for AWS, an open-source solution for regional capabilities

Today, AWS announces the launch of Capability Insights, an open-source solution that enables you to deploy regional capabilities data inside your own Amazon Virtual Private Cloud (VPC). This self-hosted dashboard addresses the needs of teams building multi-Region architectures requiring regional capabilities data deployed as infrastructure they own, inside their network, and under their governance. The solution is designed for organizations with data residency requirements, compliance teams needing internal reporting, and teams planning regional expansion or multi-Region recovery strategies.

The dashboard auto-refreshes every 24 hours with AWS capabilities data across all Regions, covering services, features, API operations, and CloudFormation resource types. The Workload Analysis component scans your AWS CloudTrail logs and AWS CloudFormation stacks to filter 200+ services down to the number of services your account actually uses, reducing multi-week gap analysis to quick reviews. All data remains within your VPC perimeter, supporting compliance and data residency requirements while providing full ownership and control over the infrastructure hosting the regional capabilities data.

 

 

​Announcing Capability Insights for AWS, an open-source solution for regional capabilities
Today, AWS announces the launch of Capability Insights, an open-source solution that enables you to deploy regional capabilities data inside your own Amazon Virtual Private Cloud (VPC). This self-hosted dashboard addresses the needs of teams building multi-Region architectures requiring regional capabilities data deployed as infrastructure they own, inside their network, and under their governance. The solution is designed for organizations with data residency requirements, compliance teams needing internal reporting, and teams planning regional expansion or multi-Region recovery strategies.
The dashboard auto-refreshes every 24 hours with AWS capabilities data across all Regions, covering services, features, API operations, and CloudFormation resource types. The Workload Analysis component scans your AWS CloudTrail logs and AWS CloudFormation stacks to filter 200+ services down to the number of services your account actually uses, reducing multi-week gap analysis to quick reviews. All data remains within your VPC perimeter, supporting compliance and data residency requirements while providing full ownership and control over the infrastructure hosting the regional capabilities data.
   

Amazon Time Sync Service introduces support for microsecond accurate time on 26 additional EC2 instance types in all commercial regions. Built on Amazon’s proven network infrastructure and the AWS Nitro System, microsecond accurate time and nanosecond precision hardware timestamps leverage the reference clocks running in the Nitro System directly, enabling customers to easily order application events, measure 1-way network latency, and increase distributed application transaction speed. 
 
Starting today, customers can access microsecond accurate time on these additional instance types by creating a Precision Time Placement Group (PTPG), a new placement strategy that allows customers to launch instances with Precision Time Protocol hardware clock (PHC) enabled. Customers that require both low network latency as well as precision time can associate a PTPG with their Cluster Placement Group (CPG), so that their low-latency workloads also benefit from microsecond accurate time. 
 
For more information, refer to the Amazon Time Sync Service documentation.

 

​Amazon Time Sync Service introduces support for microsecond accurate time on 26 additional EC2 instance types in all commercial regions. Built on Amazon’s proven network infrastructure and the AWS Nitro System, microsecond accurate time and nanosecond precision hardware timestamps leverage the reference clocks running in the Nitro System directly, enabling customers to easily order application events, measure 1-way network latency, and increase distributed application transaction speed.    Starting today, customers can access microsecond accurate time on these additional instance types by creating a Precision Time Placement Group (PTPG), a new placement strategy that allows customers to launch instances with Precision Time Protocol hardware clock (PHC) enabled. Customers that require both low network latency as well as precision time can associate a PTPG with their Cluster Placement Group (CPG), so that their low-latency workloads also benefit from microsecond accurate time.    For more information, refer to the Amazon Time Sync Service documentation.  

Amazon WorkSpaces for agents is now generally available, enabling AI agents to securely access and operate desktop applications through managed WorkSpaces environments. Enterprises run critical business processes on desktop applications (ERP systems, CRMs, mainframes, and proprietary tools) where years of customization, undocumented logic, and strict compliance requirements make them too critical to abandon and costly to modernize. WorkSpaces for agentsnow gives AI agents a managed cloud workspace where they can see the screen and operate these applications the way humans do, without requiring application modernization or custom integrations.

WorkSpaces uses the same infrastructure for agents as organizations have trusted for over a decade to deliver secure, managed desktops at scale. Agents inherit the same identity controls, network isolation, and compliance boundaries as human users, so organizations gain automation without giving up governance. Organizations can automate workflows such as claims processing, patient record updates, trade settlement, and back-office operations. The service works with any agent framework using Model Context Protocol (MCP), and pricing scales based on active session time.

Since launching in Preview, customer and partner feedback has shaped new capabilities. MCP tool forwarding allows agents to interact with applications and the desktop operating system through direct MCP calls rather than using computer use tools, improving accuracy, reducing latency, and lowering cost. Real-time session control gives operators live visibility into agent activity with the ability to revoke access mid-session. Domain-joined fleet support lets agents operate under existing Active Directory identities, extending the same access policies and audit attribution that apply to employees.

To learn more, visit Amazon WorkSpaces for AI agents. To get started building, see the documentation and sample code on GitHub.  

 

​Amazon WorkSpaces for agents is now generally available, enabling AI agents to securely access and operate desktop applications through managed WorkSpaces environments. Enterprises run critical business processes on desktop applications (ERP systems, CRMs, mainframes, and proprietary tools) where years of customization, undocumented logic, and strict compliance requirements make them too critical to abandon and costly to modernize. WorkSpaces for agentsnow gives AI agents a managed cloud workspace where they can see the screen and operate these applications the way humans do, without requiring application modernization or custom integrations.
WorkSpaces uses the same infrastructure for agents as organizations have trusted for over a decade to deliver secure, managed desktops at scale. Agents inherit the same identity controls, network isolation, and compliance boundaries as human users, so organizations gain automation without giving up governance. Organizations can automate workflows such as claims processing, patient record updates, trade settlement, and back-office operations. The service works with any agent framework using Model Context Protocol (MCP), and pricing scales based on active session time.
Since launching in Preview, customer and partner feedback has shaped new capabilities. MCP tool forwarding allows agents to interact with applications and the desktop operating system through direct MCP calls rather than using computer use tools, improving accuracy, reducing latency, and lowering cost. Real-time session control gives operators live visibility into agent activity with the ability to revoke access mid-session. Domain-joined fleet support lets agents operate under existing Active Directory identities, extending the same access policies and audit attribution that apply to employees.
To learn more, visit Amazon WorkSpaces for AI agents. To get started building, see the documentation and sample code on GitHub.