10/2/2025, 12:00:00 AM ~ 10/3/2025, 12:00:00 AM (UTC)
Recent Announcements
AWS Directory Service enables API-driven Managed Microsoft AD edition upgrades
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.\n 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.
Amazon Connect now supports agent screen recording for ChromeOS
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).\n 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.
AWS Direct Connect announces 100G expansion in Makati City, Philippines
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.\n 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
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.\n 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 Neptune Database now integrates with GraphStorm for scalable graph machine learning
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.\n 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.
Amazon Cognito adds terms of use and privacy policy documents support to Managed Login
Amazon Cognito now allows you to configure terms of use and privacy policy documents for Managed Login pages. This helps customers seamlessly present legal terms during user registration while simplifying implementation. With Managed Login, Cognito customers could previously use its no-code editor to customize the user journey from signup and login to password recovery and multi-factor authentication. Now, customers can additionally use Managed Login to easily set up terms of use and privacy policy documents, saving development teams from building custom solutions.\n With this capability, you can configure terms of use and privacy policy URLs for each app client in your Cognito user pool. When users register, they see text indicating that by signing up, they agree to your terms of use and privacy policy, and a link to your webpage with the agreement. You can configure different URLs for each supported language to match your Managed Login localization settings. For example, if you have configured the privacy policy and terms of use documents for French (fr) and the same is selected in the lang query-parameter on the sign-up page URL, users will see the French URL you configured. This capability is available to Amazon Cognito customers using the Essentials or Plus tiers in AWS Regions where Cognito is available, including the AWS GovCloud (US) Regions. To learn more, refer to the developer guide and Pricing Detail Page for Cognito Essentials and Plus tier.
Open Source Model Context Protocol (MCP) Server now available for Amazon Bedrock AgentCore
This new standardized interface allows developers to analyze, transform, and deploy production-ready AI agents directly in their preferred development environment.\n 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 Config advanced query and aggregator now available in Asia Pacific (New Zealand) Region
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.\n 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 Secrets Manager expands AWS PrivateLink support to FIPS endpoints
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.\n 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.
Amazon Connect makes it easier to get customer input on outbound calls
Amazon Connect, the cloud-based contact center service from AWS, now supports Get Customer Input and Store Customer Input flow blocks for outbound voice whisper flows. The Get Customer Input flow block allows a prompt to be played to a customer on an outbound call after they answer the call but before they are connected with an agent, and the customer’s response can be collected through either DTMF input or via an Amazon Lex Bot.\n This capability will allow you to capture interactive and dynamic customer input on outbound calls before these are connected to an agent. For example, you can use the Get Customer Input flow block to obtain customer consent for call recording as part of outbound calls placed by agents, and use it to trigger Amazon Connect Contact Lens recording and analytics. The capability is available in all AWS commercial and AWS GovCloud (US-West) regions where Amazon Connect is offered. To learn more about Amazon Connect, please visit the Amazon Connect website or consult the Amazon Connect Administrator Guide.
Amazon GameLift Servers adds ability to view and connect to instances in the console
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.\n 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.
AWS Builder ID now supports Sign in with Google
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.\n 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.
AWS Clean Rooms now supports data access budgets
AWS Clean Rooms now supports data access budgets for tables associated to a collaboration. This new privacy control allows you to limit the number of times your data can be analyzed when training or running inference on a custom ML model or in a SQL query or Pyspark job. With data access budgets, you can establish per-period budgets that refresh daily, weekly, or monthly, lifetime budgets for overall usage, or both types simultaneously. When you spend a budget, the system prevents additional analyses until the budget refreshes, but you can reset or edit a budget at anytime as your needs change.\n AWS Clean Rooms helps companies and their partners easily analyze and collaborate on their collective datasets without revealing or copying one another’s underlying data. For more information about the AWS Regions where AWS Clean Rooms is available, see the AWS Regions table. To learn more about collaborating with AWS Clean Rooms, visit AWS Clean Rooms.
AWS Parallel Computing Service now supports dynamic cluster updates
AWS Parallel Computing Service (AWS PCS) now enables you to modify and update key Slurm workload manager settings without rebuilding your cluster. You can now adjust essential parameters including accounting configurations and workload management settings on existing clusters, where previously these details were fixed at creation time.\n This new flexibility helps you adapt your high performance computing (HPC) environment to changing requirements without disrupting operations. You can make modifications through the AWS Management Console, AWS Command Line Interface (AWS CLI), or AWS SDK. AWS PCS is a managed service that makes it easier for you to run and scale your high performance computing (HPC) workloads and build scientific and engineering models on AWS using Slurm. You can use AWS PCS to build complete, elastic environments that integrate compute, storage, networking, and visualization tools. AWS PCS simplifies cluster operations with managed updates and built-in observability features, helping to remove the burden of maintenance. You can work in a familiar environment, focusing on your research and innovation instead of worrying about infrastructure. Cluster configuration modifications are available in all AWS Regions where AWS PCS is offered. To learn more, see the Modifying a cluster section in the AWS PCS User Guide.
Amazon Elastic Container Services (Amazon ECS), a fully managed container orchestration service, now provides one-click event capture and event history querying directly in the AWS Management Console.\n ECS lifecycle events, including service action events and task state changes, provide visibility into your ECS environment for monitoring and troubleshooting. The ECS console now enables you to set up event capture with a single click, and access an intuitive query interface without leaving the ECS console. The ECS console automatically creates and manages the underlying EventBridge rules and CloudWatch log groups, while providing pre-built query templates and filters for common troubleshooting scenarios. Event capture through the ECS console is a great way to retain data for stopped tasks and recent events beyond the default limits. To enable event capture, on the ECS console, navigate to the Cluster details page, locate the Configuration tab, and click the “Turn on event capture” button. Once enabled, navigate to the Event history tab on your cluster or service details page to query and analyze historical events. The console provides commonly used query parameters such as time range, task ID, and deployment ID, along with filters for stop codes and container exit codes. You can view detailed task lifecycle events such as task state changes and service action events without needing to navigate to another console, or use query languages. ECS console event capture is available in all AWS Commercial Regions and AWS GovCloud (US) Regions. To learn more, visit the ECS developer guide.
AWS Parallel Computing Service expands Slurm customization capabilities
AWS Parallel Computing Service (AWS PCS) now offers expanded Slurm configuration capabilities, enabling you to set over 60 additional parameters for granular control over your high performance computing (HPC) cluster operations. This enhancement provides more flexibility in managing job scheduling, resource allocation, access control, and job lifecycle.\n The new Slurm custom settings give you fine-grained control over various resource management scenarios, including fair-share scheduling and quality of service levels. For example, you can now implement queue-specific priority policies, configure preemption settings, and set custom time and resource limits. Additionally, you can control access permissions at the account level and configure per-job execution behaviors. These and other capabilities help you to run a production HPC environment that efficiently serves multiple teams, projects, and workload types. AWS PCS is a managed service that makes it easier for you to run and scale your HPC workloads and build scientific and engineering models on AWS using Slurm. You can use AWS PCS to build complete, elastic environments that integrate compute, storage, networking, and visualization tools. AWS PCS simplifies cluster operations with managed updates and built-in observability features, helping to remove the burden of maintenance. You can work in a familiar environment, focusing on your research and innovation instead of worrying about infrastructure. Expanded Slurm custom settings are available in all AWS Regions where AWS PCS is available. To learn more, see the AWS PCS User Guide.
AWS Parallel Computing Service (PCS) now supports node reboot via Slurm
AWS Parallel Computing Service (PCS) now allows you to reboot compute nodes using Slurm commands without triggering instance replacement. With this feature, you can reboot nodes for operational reasons such as troubleshooting, resource cleanup, and recovery from degraded states before requiring full node replacement, enabling you to efficiently maintain cluster health at lower costs.\n This feature is available in all AWS Regions where PCS is available. You can use the ‘scontrol reboot’ command with options to schedule immediate or deferred reboots, while reboots through other methods will continue to trigger instance replacement. To learn more, refer to Rebooting compute nodes with Slurm in AWS PCS. PCS is a managed service that simplifies running and scaling high performance computing (HPC) workloads on AWS using Slurm. To learn more about PCS, refer to the service documentation.
Amazon EC2 Instance Connect Endpoint now supports IPv6 connectivity
Starting today, Amazon EC2 Instance Connect Endpoint supports Internet Protocol Version 6 (IPv6) connectivity. Customers can now configure EIC Endpoints to be dual-stack or IPv6 only to connect to instances with IPv6 addresses.\n EC2 Instance Connect helps customers have SSH and RDP connectivity to their EC2 instances without using public IP addresses. With IPv6 support, customers can establish connectivity to instances in private subnets using IPv6 addresses, while maintaining backwards compatibility with existing instances and subnets using IPv4 addresses. EC2 Instance Connect Endpoint IPv6 support is available in all AWS Commercial Regions, the AWS GovCloud (US) Regions, and the China Regions. Customers can access their private EC2 instances through AWS EC2 Console, AWS CLI, and SSH clients. To learn more about connecting to EC2 instances using EC2 Instance Connect Endpoint, see documentation. To learn more about IPv6 support on AWS, visit the documentation page.
Cohere’s Embed v4 multimodal embeddings model now available on Amazon Bedrock
Amazon Bedrock now offers Cohere Embed v4, the latest state-of-the-art multimodal embedding model from Cohere that produces high-quality embeddings for text, images, and complex business documents. This powerful addition to Amazon Bedrock enables enterprises to build AI applications with frontier search and retrieval capabilities.\n Traditional embedding models often struggle to understand complex multimodal business materials, such as business presentations and sales and financial reports, requiring extensive data pre-processing pipelines. Embed v4 addresses this challenge by natively processing documents with tables, graphs, diagrams, code snippets, and even handwritten notes. The model handles real-world imperfections such as spelling errors and formatting issues, eliminating the need for time-consuming data cleanup and helping you surface insights from previously difficult-to-search information. With support for over 100 languages, including Arabic, English, French, Japanese, and Korean, Embed v4 enables global organizations to seamlessly search for information, breaking language barriers. The model is also fine-tuned for industries such as finance, healthcare, and manufacturing, delivering superior performance on specialized documents including financial reports, medical records, and product specifications. Cohere Embed v4 is available for on-demand inference in US East (N. Virginia), Europe (Ireland), and Asia Pacific (Seoul), and can be accessed from select public AWS Regions through cross-region inference. Review the Amazon Bedrock Model Support by Regions guide for complete regional availability. To get started, visit the Amazon Bedrock console to request model access. For more information, refer to the Cohere product page and documentation.
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