10/1/2025, 12:00:00 AM ~ 10/2/2025, 12:00:00 AM (UTC)

Recent Announcements

Amazon GameLift Streams adds IPv6 support for streaming Windows applications

Amazon GameLift Streams now supports streaming over IPv6 for applications running on Windows-based stream groups, enabling dual-stack (IPv4 and IPv6) streaming capabilities. This enhancement gives our customers flexibility in how they connect to their streamed Windows applications while maintaining compatibility with existing IPv4 implementations.\n When streaming applications running on Windows-based stream groups through Amazon GameLift Streams, customers can now use either IPv4 or IPv6 protocols. This dual-stack support helps customers meet IPv6 compliance requirements and provides additional addressing options for the streaming clients. Please note that Linux runtime applications will continue to require IPv4 connectivity for streaming.

Amazon GameLift Streams IPv6 support for applications running on Windows-based stream groups is available in all AWS Regions where Amazon GameLift Streams is offered. To learn more about networking options for your streaming applications, visit the Amazon GameLift Streams documentation.

Amazon Keyspaces (for Apache Cassandra) now supports IPv6 with dual-stack endpoints

Amazon Keyspaces (for Apache Cassandra) now supports Internet Protocol version 6 (IPv6) through new dual-stack endpoints that enable both IPv6 and IPv4 connectivity. This enhancement provides customers with a vastly expanded address space while maintaining compatibility with existing IPv4-based applications.\n Amazon Keyspaces (for Apache Cassandra) is a scalable, highly available, and managed Apache Cassandra–compatible database service. Amazon Keyspaces is serverless, so you pay for only the resources that you use and you can build applications that serve thousands of requests per second with virtually unlimited throughput and storage. The dual-stack endpoints functionality allows you to gradually transition your applications from IPv4 to IPv6 without disruption, enabling safer migration paths for your critical database services. IPv6 support is also available through PrivateLink interface Virtual Private Cloud (VPC) endpoints, allowing you to access Amazon Keyspaces privately without traversing the public internet. IPv6 support for Amazon Keyspaces is now available in all AWS Commercial and AWS GovCloud (US) Regions where Amazon Keyspaces is offered, at no additional cost. To learn more about IPv6 support on Keyspaces, visit the Amazon Keyspaces documentation page.

Announcing Apache Airflow 3.0 support in Amazon Managed Workflows for Apache Airflow

Amazon Managed Workflows for Apache Airflow (MWAA) now supports Apache Airflow version 3.0, the latest major release of the workflow orchestration platform. This release enhances your ability to author, schedule, and monitor complex workflows with greater efficiency and control.\n Amazon MWAA is a managed service for Apache Airflow that enables seamless workflow orchestration using the familiar Apache Airflow platform. The availability of Apache Airflow v3.0 on MWAA introduces substantial improvements to workflow orchestration, including a completely redesigned interface for enhanced usability and advanced event-driven scheduling capabilities. This new scheduling system triggers workflows based on external events directly, eliminating the need for separate asset update pipelines. The newly introduced Task SDK in Apache Airflow v3.0 on MWAA help you simplify DAGs by reducing boilerplate code, making workflows more concise, readable, and consistent. Security and isolation are strengthened through the Task Execution API, which restricts direct access to the metadatabase and manages all runtime interactions. This release also features scheduler-managed backfill functionality, providing you better control over historical data processing. Additionally, MWAA now supports Python 3.12, while incorporating critical security improvements and bug fixes that enhance the overall reliability and security of your workflows in Amazon MWAA environments. You can launch a new Apache Airflow 3.0 environment on Amazon MWAA with just a few clicks in the AWS Management Console in all currently supported Amazon MWAA regions. To learn more about Apache Airflow 3.0 visit the Amazon MWAA documentation, and the Apache Airflow 3.0 change log in the Apache Airflow documentation. Apache, Apache Airflow, and Airflow are either registered trademarks or trademarks of the Apache Software Foundation in the United States and/or other countries.

Amazon Bedrock Data Automation now provides support for enhancing transcriptions

Amazon Bedrock Data Automation (BDA) now supports enhanced transcription output for audio files by providing the option to distinguish between various speakers and separately process audio from each channel. Additionally, BDA expands support for blueprint creation using a guided and natural language-based interface for extracting custom insights to audio modality. BDA is a feature of Amazon Bedrock that automates generation of insights from unstructured multimodal content such as documents, images, audio, and videos for your GenAI-powered applications. With this launch, developers can now enable speaker diarization and channel identification in standard output. Speaker diarization detects each unique speaker and tracks speaker changes in a multi-party audio conversation. Channel identification enables separate processing of audio from each channel. For example, speakers such as a customer and sales agent can be separated into unique channels, making it easier to analyze the transcript.\n Speaker diarization and channel identification make transcripts easier to read and extract custom insights from a variety of multi-party voice conversations such as customer calls, education sessions, public safety calls, clinical discussions, and meetings. This enables customers to identify ways to improve employee productivity, add subtitles to webinars, enhance customer experience, or increase regulatory compliance. For example, Telehealth customers can summarize the recommendations of a doctor by assigning the doctors and patients to pre-identified channels. Amazon Bedrock Data Automation is available in a total of 7 AWS Regions in US West (Oregon), US East (N. Virginia), GovCloud (US-West), Europe (Frankfurt), Europe (London), Europe (Ireland), Asia Pacific (Mumbai) and Asia Pacific (Sydney). To learn more, visit the Bedrock Data Automation page, Amazon Bedrock Pricing page, or view documentation.

Application map is now generally available for Amazon CloudWatch

Amazon CloudWatch now helps you monitor large-scale distributed applications by automatically discovering and organizing services into groups based on configurations and their relationships. SREs and DevOps teams can identify critical dependencies and blast radius impacts to remediate issues faster. You get an always-on, out-of-the-box catalog and map that visualizes services and dependencies across AWS accounts and regions, organizing them into logical groups that align with how customers think about their systems—without manual configurations. You can also apply dynamic grouping based on how you organize applications—by teams, business units, criticality tiers, or other attributes.\n With this new application performance monitoring (APM) capability, customers can quickly visualize which applications and dependencies to focus on while troubleshooting their distributed applications. For example, SRE and DevOps teams can now accelerate root cause analysis and reduce mean-time-to-resolution (MTTR) through high-level operational signals such as SLOs, health indicators, changes, and top observations. The application map integrates with a contextual troubleshooting drawer that surfaces relevant metrics and actionable insights to accelerate triage. When deeper investigation is needed, teams can pivot to an application-specific dashboard tailored for troubleshooting. The map, drawer, and dashboard dynamically update as new services are discovered or as customers adjust how their environments are grouped—ensuring the view is always accurate and aligned with how teams operate. This new capability is now available in all AWS commercial regions where Application Signals have launched , at no additional cost. To learn more, please visit CloudWatch Application Signals documentation.

Amazon Detective now supports AWS PrivateLink for private API access

Amazon Detective now supports Amazon Virtual Private Cloud (VPC) endpoints via AWS PrivateLink, enabling you to securely initiate API calls to Detective from within your VPC without requiring Internet traversal. AWS PrivateLink support for Detective is available in all AWS Regions where Detective is available (see the AWS Region table). To try the new feature, you can create a VPC endpoint for Detective through the VPC console, API, or SDK. This creates an elastic network interface in your specified subnets. The interface has a private IP address that serves as an entry point for traffic destined for Detective. You can read more about Detective’s integration with PrivateLink here.\n Amazon Detective automatically collects log data from your AWS resources and uses machine learning, statistical analysis, and graph theory to build interactive visualizations that enable you to conduct faster and more efficient security investigations. Detective analyzes trillions of events from multiple data sources like Amazon Virtual Private Cloud (Amazon VPC) Flow Logs, AWS CloudTrail logs, Amazon Elastic Kubernetes Service (Amazon EKS) audit logs, and findings from multiple AWS security services to create a unified, interactive view of security events. Detective also automatically groups related findings from Amazon GuardDuty, AWS Security Hub and Amazon Inspector to show you combined threats and vulnerabilities to help security analysts identify and prioritize potential high-severity security risks. To get started, see the Amazon Detective User Guide

AWS API MCP Server v1.0.0 release

Today, AWS announces the v1.0.0 release of the AWS API model context protocol (MCP) server enabling foundation models (FMs) to interact with any AWS API through natural language by creating and executing syntactically correct CLI commands.\n The v1.0.0 release of the AWS API MCP Server contains many enhancements that make the server easier to configure, use, and integrate with MCP clients and agentic frameworks. This release reduces startup time and removes several dependencies by converting the suggest_aws_command tool to a remote service rather than relying on local installation. Security enhancements offer improved secure file system controls, and better input validation. Customers using AWS CloudWatch agent can now collect logs from the API MCP Server for improved observability. In order to support more hosting and configuration options, the AWS API MCP Server now offers streamable HTTP transport in addition to the existing stdio. To make human-in-the-loop workflows requiring iterative inputs more reliable, the AWS API MCP Server now includes elicitation in supported MCP clients. To provide additional safeguards the API MCP Server can be configured to deny certain types of actions or require human oversight and consent for mutating actions. This release also includes a new experimental tool called get_execution_plan to provide prescriptive workflows for common AWS tasks. The tool can be enabled by setting the EXPERIMENTAL_AGENT_SCRIPTS flag to true. Customers can configure the AWS API MCP Server for use with their MCP-compatible clients from several popular MCP registries. The AWS API MCP Server is also available packaged as a container in the Amazon ECR Public Gallery. The AWS API MCP Server is open-source and available now. Visit the AWS Labs GitHub repository to view the source, download, and start experimenting with natural language interaction with AWS APIs today.

AWS Knowledge MCP Server now generally available

Today, AWS announces the general availability (GA) of the AWS Knowledge Model Context Protocol (MCP) Server. The AWS Knowledge server gives AI agents and MCP clients access to authoritative knowledge, including documentation, blog posts, What’s New announcements, and Well-Architected best practices, in an LLM-compatible format. With this release, the server also includes knowledge about the regional availability of AWS APIs and CloudFormation resources.\n AWS Knowledge MCP Server enables MCP clients and agentic frameworks supporting MCP to anchor their responses in trusted AWS context, guidance, and best practices. Customers can now benefit from more accurate reasoning, increased consistency of execution, reduced manual context management so they can focus on business problems rather than MCP configurations. The server is publicly accessible at no cost and does not require an AWS account. Usage is subject to rate limits. Give your developers and agents access to the most up-to-date AWS information today by configuring your MCP clients to use the AWS Knowledge MCP Server endpoint, and follow the Getting Started guide for setup instructions. The AWS Knowledge MCP Server is available globally.

AWS Cloud WAN is now available in AWS GovCloud (US) Regions

Starting today, AWS Cloud WAN is available in the AWS GovCloud (US-West) and AWS GovCloud (US-East) regions.\n With AWS Cloud WAN, you can use a central dashboard and network policies to create a global network that spans multiple locations and networks, removing the need to configure and manage different networks using different technologies. You can use network policies to specify the Amazon Virtual Private Clouds, AWS Transit Gateways, and on-premises locations you want to connect to using an AWS Site-to-Site VPN, AWS Direct Connect, or third-party software-defined WAN (SD-WAN) products. The AWS Cloud WAN central dashboard generates a comprehensive view of the network to help you monitor network health, security, and performance. In addition, AWS Cloud WAN automatically creates a global network across AWS Regions by using Border Gateway Protocol (BGP) so that you can easily exchange routes worldwide. To learn more, please visit the AWS Cloud WAN product detail page.

AWS DataSync now supports VPC endpoint policies

AWS DataSync now supports virtual private cloud (VPC) endpoint policies, allowing you to control access to DataSync API operations through DataSync VPC service endpoints and Federal Information Processing Standard (FIPS) 140-3 enabled VPC service endpoints. This new feature helps organizations strengthen their security posture and meet compliance requirements when accessing DataSync API operations through VPC endpoints.\n VPC endpoint policies allow you to restrict specific DataSync API actions accessed through your VPC endpoints. For example, you can control which AWS principals can access DataSync operations such as CreateTask, StartTaskExecution, or ListAgents. These policies work in conjunction with identity-based policies and resource-based policies to secure access in your AWS environment. This feature is available in all AWS Regions where AWS DataSync is available. For more information about FIPS 140-3 at AWS, visit FIPS 140-3 Compliance. To learn more about VPC endpoint policies for AWS DataSync, see the AWS DataSync User Guide.

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