Today, Amazon GameLift Servers launched new console capabilities that let you view and connect to individual fleet instances. The EC2 and Container Fleet Detail pages have a new Instances tab to see a list of instances associated with a fleet. For each instance, there is an instance details page that displays metadata in a human-readable format (data also available via Amazon GameLift Server APIs). From the list and detail views, you can invoke the connect button, open a modal, and launch AWS CloudShell to start an SSM session directly into that instance.

These console improvements give hands-on tools to debug, inspect, and resolve issues faster. Instead of relying on external tooling or guesswork, directly investigate host performance, pull recent game server logs, or diagnose issues such as network configuration and instance health – all from within the Amazon GameLift Servers Console. This reduces turnaround time when troubleshooting and enhances visibility into what’s happening “under the hood” of a game server fleet.

SSM in Console is available in Amazon GameLift Servers supported regions, except AWS China. For more information, visit the Amazon GameLift Servers documentation.

 

​Today, Amazon GameLift Servers launched new console capabilities that let you view and connect to individual fleet instances. The EC2 and Container Fleet Detail pages have a new Instances tab to see a list of instances associated with a fleet. For each instance, there is an instance details page that displays metadata in a human-readable format (data also available via Amazon GameLift Server APIs). From the list and detail views, you can invoke the connect button, open a modal, and launch AWS CloudShell to start an SSM session directly into that instance. These console improvements give hands-on tools to debug, inspect, and resolve issues faster. Instead of relying on external tooling or guesswork, directly investigate host performance, pull recent game server logs, or diagnose issues such as network configuration and instance health – all from within the Amazon GameLift Servers Console. This reduces turnaround time when troubleshooting and enhances visibility into what’s happening “under the hood” of a game server fleet. SSM in Console is available in Amazon GameLift Servers supported regions, except AWS China. For more information, visit the Amazon GameLift Servers documentation.  

This new standardized interface allows developers to analyze, transform, and deploy production-ready AI agents directly in their preferred development environment.

Get started with AgentCore faster and more easily with one-click installation that integrates Agentic IDEs like Kiro and AI coding assistants (Claude Code, Cursor, and Amazon Q Developer CLI). Use natural language to iteratively develop your agent, including transforming agent logic to work with the AgentCore SDK and deploying your agent into development accounts.

The open-source MCP server is available globally via GitHub.

To get started, visit the AgentCore MCP Server GitHub repository for documentation and installation instructions. You can also learn more about this launch in our blog. For more information about Amazon Bedrock AgentCore and it’s services visit the News Blog and explore in-depth implementation details in the AgentCore documentation. For pricing information, visit the Amazon Bedrock AgentCore Pricing.

 

​This new standardized interface allows developers to analyze, transform, and deploy production-ready AI agents directly in their preferred development environment. Get started with AgentCore faster and more easily with one-click installation that integrates Agentic IDEs like Kiro and AI coding assistants (Claude Code, Cursor, and Amazon Q Developer CLI). Use natural language to iteratively develop your agent, including transforming agent logic to work with the AgentCore SDK and deploying your agent into development accounts. The open-source MCP server is available globally via GitHub. To get started, visit the AgentCore MCP Server GitHub repository for documentation and installation instructions. You can also learn more about this launch in our blog. For more information about Amazon Bedrock AgentCore and it’s services visit the News Blog and explore in-depth implementation details in the AgentCore documentation. For pricing information, visit the Amazon Bedrock AgentCore Pricing.  

AWS Directory Service now enables customers to upgrade Managed Microsoft AD from Standard to Enterprise Edition programmatically through the UpdateDirectorySetup API. The self-service edition upgrade eliminates the need for support tickets when scaling Managed Microsoft AD directories.

The API-driven Standard to Enterprise Edition upgrade removes operational barriers that previously required coordinating maintenance windows with AWS support, enabling on-demand directory scaling with automated pre-upgrade snapshots and sequential domain controller upgrades. This streamlined process ensures data protection through automatic backup creation before upgrades begin, while the sequential upgrade approach maintains directory availability throughout the process.

Organizations can now scale their directory infrastructure in response to growing user bases or expanding application requirements without the delays associated with traditional support-driven upgrade processes. The programmatic approach enables integration with existing automation frameworks and infrastructure-as-code deployments.
Directory size upgrades are available in all AWS Directory Service regions through the AWS SDK, providing consistent upgrade capabilities across global deployments.

To learn more, see the AWS Directory Service documentation and UpdateDirectorySetup API reference.

 

​AWS Directory Service now enables customers to upgrade Managed Microsoft AD from Standard to Enterprise Edition programmatically through the UpdateDirectorySetup API. The self-service edition upgrade eliminates the need for support tickets when scaling Managed Microsoft AD directories. The API-driven Standard to Enterprise Edition upgrade removes operational barriers that previously required coordinating maintenance windows with AWS support, enabling on-demand directory scaling with automated pre-upgrade snapshots and sequential domain controller upgrades. This streamlined process ensures data protection through automatic backup creation before upgrades begin, while the sequential upgrade approach maintains directory availability throughout the process. Organizations can now scale their directory infrastructure in response to growing user bases or expanding application requirements without the delays associated with traditional support-driven upgrade processes. The programmatic approach enables integration with existing automation frameworks and infrastructure-as-code deployments. Directory size upgrades are available in all AWS Directory Service regions through the AWS SDK, providing consistent upgrade capabilities across global deployments. To learn more, see the AWS Directory Service documentation and UpdateDirectorySetup API reference.  

AWS Config advanced queries and aggregators are now available in Asia Pacific (New Zealand) region. You can use advanced queries to query the current configuration and compliance state of your AWS resources. Aggregators enable centralized visibility and analysis by aggregating configuration and compliance data from multiple accounts and regions, or across an AWS Organization.

Advanced queries provide a single query endpoint and a query language to get current resource configuration and compliance state without performing service-specific describe API calls. You can use configuration aggregators to run the same queries from a central account across multiple accounts and AWS Regions.

Advanced queries can be used from AWS console and AWS CLI. To learn more about aggregators, please refer to our documentation. With this expansion, AWS Config advanced queries and aggregators are now available in all supported regions.

 

​AWS Config advanced queries and aggregators are now available in Asia Pacific (New Zealand) region. You can use advanced queries to query the current configuration and compliance state of your AWS resources. Aggregators enable centralized visibility and analysis by aggregating configuration and compliance data from multiple accounts and regions, or across an AWS Organization. Advanced queries provide a single query endpoint and a query language to get current resource configuration and compliance state without performing service-specific describe API calls. You can use configuration aggregators to run the same queries from a central account across multiple accounts and AWS Regions. Advanced queries can be used from AWS console and AWS CLI. To learn more about aggregators, please refer to our documentation. With this expansion, AWS Config advanced queries and aggregators are now available in all supported regions.  

You can now create an AWS Builder ID using sign in with Google. AWS Builder ID is a personal profile that provides access to AWS applications including Kiro, AWS Builder Center, AWS Training and Certification, AWS re:Post and AWS Startups.

AWS Builder ID represents you as an individual and is independent from any credentials and data you may have in existing AWS accounts. Like other personal profiles, AWS Builder ID remains with you as you progress through your personal, educational, and career goals. Sign in with Google offers a convenient way for you to access AWS applications and websites with a single click using your Google account. This eliminates the need for separate credentials, further simplifies the registration process, and reduces the likelihood of forgotten passwords. Returning users will benefit from a frictionless sign-in experience to their AWS applications.

Sign in with Google is available to help you get started quickly with any of the applications that support AWS Builder ID.

 

​You can now create an AWS Builder ID using sign in with Google. AWS Builder ID is a personal profile that provides access to AWS applications including Kiro, AWS Builder Center, AWS Training and Certification, AWS re:Post and AWS Startups. AWS Builder ID represents you as an individual and is independent from any credentials and data you may have in existing AWS accounts. Like other personal profiles, AWS Builder ID remains with you as you progress through your personal, educational, and career goals. Sign in with Google offers a convenient way for you to access AWS applications and websites with a single click using your Google account. This eliminates the need for separate credentials, further simplifies the registration process, and reduces the likelihood of forgotten passwords. Returning users will benefit from a frictionless sign-in experience to their AWS applications. Sign in with Google is available to help you get started quickly with any of the applications that support AWS Builder ID.  

Amazon Connect now provides screen recording for agents using ChromeOS devices making it easier for you to help improve their performance. With screen recording, you can identify areas for agent coaching (e.g., long contact handle duration or non-compliance with business processes) by not only listening to customer calls or reviewing chat transcripts, but also watching agents’ actions while handling a contact (i.e., a voice call, chat, or task).

Screen recording on ChromeOS is available in all the AWS Regions where Amazon Connect is already available. To learn more about screen recording, please visit the documentation and webpage. For information about screen recording pricing, visit the Amazon Connect pricing page.

 

​Amazon Connect now provides screen recording for agents using ChromeOS devices making it easier for you to help improve their performance. With screen recording, you can identify areas for agent coaching (e.g., long contact handle duration or non-compliance with business processes) by not only listening to customer calls or reviewing chat transcripts, but also watching agents’ actions while handling a contact (i.e., a voice call, chat, or task). Screen recording on ChromeOS is available in all the AWS Regions where Amazon Connect is already available. To learn more about screen recording, please visit the documentation and webpage. For information about screen recording pricing, visit the Amazon Connect pricing page.  

Today, AWS announced the expansion of 10 Gbps and 100 Gbps dedicated connections with MACsec encryption capabilities at the existing AWS Direct Connect location in the ePLDT data center near Makati City, Philippines. You can now establish private, direct network access to all public AWS Regions (except those in China), AWS GovCloud Regions, and AWS Local Zones from this location.

The Direct Connect service enables you to establish a private, physical network connection between AWS and your data center, office, or colocation environment. These private connections can provide a more consistent network experience than those made over the public internet. 

For more information on the over 146 Direct Connect locations worldwide, visit the locations section of the Direct Connect product detail pages. Or, visit our getting started page to learn more about how to purchase and deploy Direct Connect.

 

​Today, AWS announced the expansion of 10 Gbps and 100 Gbps dedicated connections with MACsec encryption capabilities at the existing AWS Direct Connect location in the ePLDT data center near Makati City, Philippines. You can now establish private, direct network access to all public AWS Regions (except those in China), AWS GovCloud Regions, and AWS Local Zones from this location. The Direct Connect service enables you to establish a private, physical network connection between AWS and your data center, office, or colocation environment. These private connections can provide a more consistent network experience than those made over the public internet.  For more information on the over 146 Direct Connect locations worldwide, visit the locations section of the Direct Connect product detail pages. Or, visit our getting started page to learn more about how to purchase and deploy Direct Connect.  

Amazon Connect now provides agent time-off balance data in analytics data lake, making it easier for you to generate reports and insights from this data. With this launch, you can now access latest and historical agent time-off balances across different time-off categories (paid time-off, sick leave, leave of absence, etc.) in the analytics data lake. In addition to balances, you can also view a chronological list of all transactions that impacted the balance. For example, if an agent starts with 80 hours of paid time-off on January 1, submits a 20-hour request on January 3, and later cancels it, you can see each transaction’s impact on the final 80-hour balance. This launch makes time-off management easier by eliminating the need for managers to manually reconcile balances and time-off transactions, thus improving manager productivity and making it easier for them to respond to agent inquiries.

This feature is available in all AWS Regions where Amazon Connect agent scheduling is available. To learn more about Amazon Connect agent scheduling, click here.

 

​Amazon Connect now provides agent time-off balance data in analytics data lake, making it easier for you to generate reports and insights from this data. With this launch, you can now access latest and historical agent time-off balances across different time-off categories (paid time-off, sick leave, leave of absence, etc.) in the analytics data lake. In addition to balances, you can also view a chronological list of all transactions that impacted the balance. For example, if an agent starts with 80 hours of paid time-off on January 1, submits a 20-hour request on January 3, and later cancels it, you can see each transaction’s impact on the final 80-hour balance. This launch makes time-off management easier by eliminating the need for managers to manually reconcile balances and time-off transactions, thus improving manager productivity and making it easier for them to respond to agent inquiries. This feature is available in all AWS Regions where Amazon Connect agent scheduling is available. To learn more about Amazon Connect agent scheduling, click here.  

AWS Secrets Manager now supports AWS PrivateLink with all Secrets Manager Federal Information Processing Standard (FIPS) endpoints that are available in commercial AWS Regions and the AWS GovCloud (US) Regions.

With this launch, you can establish a private connection between your virtual private cloud (VPC) and Secrets Manager FIPS endpoints instead of connecting over the public internet, helping you meet your organization’s business, compliance, and regulatory requirements to limit public internet connectivity.

To learn more about AWS Secrets Manager support for AWS PrivateLink, visit the AWS Secrets Manager documentation. For more information about AWS PrivateLink and its benefits, visit the AWS PrivateLink product page. 

 

​AWS Secrets Manager now supports AWS PrivateLink with all Secrets Manager Federal Information Processing Standard (FIPS) endpoints that are available in commercial AWS Regions and the AWS GovCloud (US) Regions. With this launch, you can establish a private connection between your virtual private cloud (VPC) and Secrets Manager FIPS endpoints instead of connecting over the public internet, helping you meet your organization’s business, compliance, and regulatory requirements to limit public internet connectivity. To learn more about AWS Secrets Manager support for AWS PrivateLink, visit the AWS Secrets Manager documentation. For more information about AWS PrivateLink and its benefits, visit the AWS PrivateLink product page.   

Today, we’re announcing the integration of Amazon Neptune Database with GraphStorm, a scalable, open-source graph machine learning (ML) library built for enterprise-scale applications. This brings together Neptune’s OLTP (Online transaction processing) graph capabilities with GraphStorm’s scalable inference engine, making it easier for customers to deploy graph ML in latency-sensitive, transactional environments.

With this integration, developers can train GNN models using GraphStorm and deploy them as real-time inference endpoints that directly query Neptune for subgraph neighborhoods on demand. Predictions—such as node classifications or link predictions—can then be returned in sub-second timeframes, closing the loop between transactional graph updates and ML-driven decisions. This integration unlocks use cases such as fraud detection and prevention, where organizations can make real-time decisions based on complex relationships among accounts, devices, and transactions; dynamic recommendations, where systems can instantly adapt to user behavior using live graph context; and graph-based risk scoring, where risk assessments are continuously updated as the graph evolves. Customers can also combine real-time inference results with graph analytics queries for deeper operational insights, enabling ML feedback loops directly within graph applications.

This feature is available in all regions where Amazon Neptune Database is available. To learn more and try the integration yourself, check out our announcement blog: Modernize fraud prevention: GraphStorm v0.5 for real-time inference for a full walk-through.

 

​Today, we’re announcing the integration of Amazon Neptune Database with GraphStorm, a scalable, open-source graph machine learning (ML) library built for enterprise-scale applications. This brings together Neptune’s OLTP (Online transaction processing) graph capabilities with GraphStorm’s scalable inference engine, making it easier for customers to deploy graph ML in latency-sensitive, transactional environments. With this integration, developers can train GNN models using GraphStorm and deploy them as real-time inference endpoints that directly query Neptune for subgraph neighborhoods on demand. Predictions—such as node classifications or link predictions—can then be returned in sub-second timeframes, closing the loop between transactional graph updates and ML-driven decisions. This integration unlocks use cases such as fraud detection and prevention, where organizations can make real-time decisions based on complex relationships among accounts, devices, and transactions; dynamic recommendations, where systems can instantly adapt to user behavior using live graph context; and graph-based risk scoring, where risk assessments are continuously updated as the graph evolves. Customers can also combine real-time inference results with graph analytics queries for deeper operational insights, enabling ML feedback loops directly within graph applications. This feature is available in all regions where Amazon Neptune Database is available. To learn more and try the integration yourself, check out our announcement blog: Modernize fraud prevention: GraphStorm v0.5 for real-time inference for a full walk-through.