9/9/2025, 12:00:00 AM ~ 9/10/2025, 12:00:00 AM (UTC)

Recent Announcements

TwelveLabs’ Marengo Embed 2.7 can now be used for synchronous inference in Amazon Bedrock

Amazon Bedrock now supports synchronous inference for TwelveLabs’ Marengo 2.7, expanding the capabilities of this multimodal embedding model to deliver low-latency text and image embeddings directly within the API response. This update enables developers to build more responsive, interactive search and retrieval experiences while maintaining the same powerful video understanding capabilities that have made Marengo 2.7 a breakthrough in multimodal AI.\n Since its introduction to Amazon Bedrock earlier this year, Marengo 2.7 has transformed how organizations work with video content through asynchronous inference—ideal for processing large video, audio, and image files. The model generates sophisticated multi-vector embeddings, enabling precise temporal and semantic retrieval across long-form content. Now with synchronous inference support, users can leverage these advanced embedding capabilities for text and image inputs with significantly reduced latency. This makes it perfect for applications such as instant video search where users find specific scenes using natural language queries, or interactive product discovery through image similarity search. For generating embeddings from video, audio, and large-scale image files, continue using asynchronous inference for optimal performance. Marengo 2.7 with synchronous inference is now available in Amazon Bedrock in US East (N. Virginia), Europe (Ireland), and Asia Pacific (Seoul). To get started, visit the Amazon Bedrock console and request model access. To learn more, read the blog, product page, Amazon Bedrock pricing, and documentation.

Amazon MSK Connect is now available in Asia Pacific (Malaysia)

Amazon MSK Connect is now available in the Asia Pacific (Malaysia) Region. MSK Connect enables you to run fully managed Kafka Connect clusters with Amazon Managed Streaming for Apache Kafka (Amazon MSK). With a few clicks, MSK Connect allows you to easily deploy, monitor, and scale connectors that move data in and out of Apache Kafka and Amazon MSK clusters from external systems such as databases, file systems, and search indices. MSK Connect eliminates the need to provision and maintain cluster infrastructure. Connectors scale automatically in response to increases in usage and you pay only for the resources you use. With full compatibility with Kafka Connect, it is easy to migrate workloads without code changes. MSK Connect will support both Amazon MSK-managed and self-managed Apache Kafka clusters.\n You can get started with MSK Connect from the Amazon MSK console or the Amazon CLI. Visit the AWS Regions page for all the regions where Amazon MSK is available. To get started visit, the MSK Connect product page, pricing page, and the Amazon MSK Developer Guide.

Amazon CloudFront adds ECDSA support for signed URLs

Amazon CloudFront now supports Elliptic Curve Digital Signature Algorithm (ECDSA) for signed URLs and signed cookies, providing customers with enhanced performance and security for content access control. This addition gives customers the flexibility to choose between RSA and ECDSA cryptographic algorithms based on their specific security and performance requirements.\n Previously, CloudFront only supported RSA based encryption algorithms to create signed tokens. ECDSA offers several advantages over traditional RSA signatures, including faster signature generation and verification, smaller signature sizes that result in shorter URLs, and equivalent security with smaller key sizes. This makes ECDSA signed URLs and signed cookies particularly beneficial for high-volume applications, mobile environments, and IoT devices where processing efficiency and bandwidth optimization are critical. ECDSA support with signed URLs and signed cookies is available in all edge locations. This excludes Amazon Web Services China (Beijing) region, operated by Sinnet, and the Amazon Web Services China (Ningxia) region, operated by NWCD. There is no additional charge to utilize this feature. To learn more about restricting content delivered with Amazon CloudFront, visit the CloudFront documentation.

AWS Managed Microsoft AD adds LDAPS and Smart Card support using AWS Private CA

AWS Directory Service for Microsoft Active Directory (AWS Managed Microsoft AD) now offers certificate auto-enrollment for LDAPS and Smart Card and certificate based authentication with AWS Private Certificate Authority (AWS Private CA) through AWS Private CA Connector for AD. This integration enables automatic issuance, renewal, and management of certificates to AWS Managed Microsoft AD domain controllers, eliminating the need to maintain certificate authorities on Amazon EC2 instances.\n By leveraging this fully managed solution, you can reduce costs of operating certificate authority infrastructure for Active Directory and simplify certificate management with AWS Private CA’s highly available, HSM-backed infrastructure. The integration supports LDAPS and smart card authentication while providing automatic certificate lifecycle management, flexible certificate control, and built-in security capabilities that streamline migration of Active Directory-aware workloads to AWS. This feature is available in all AWS Regions where AWS Private CA Connector for AD is offered. You can easily set up AWS Private CA integration with your directory in just a few clicks or programmatically via API. To get started, follow the step-by-step instructions in the Set up AWS Private CA Connector for AD for AWS Managed Microsoft AD documentation.

Amazon EC2 R8g instances now available in additional regions

Starting today, Amazon Elastic Compute Cloud (Amazon EC2) R8g instances are available in AWS Asia Pacific (Osaka) and AWS Canada (Central) regions. These instances are powered by AWS Graviton4 processors and deliver up to 30% better performance compared to AWS Graviton3-based instances. Amazon EC2 R8g instances are ideal for memory-intensive workloads such as databases, in-memory caches, and real-time big data analytics. These instances are built on the AWS Nitro System, which offloads CPU virtualization, storage, and networking functions to dedicated hardware and software to enhance the performance and security of your workloads.\n AWS Graviton4-based Amazon EC2 instances deliver the best performance and energy efficiency for a broad range of workloads running on Amazon EC2. AWS Graviton4-based R8g instances offer larger instance sizes with up to 3x more vCPU (up to 48xlarge) and memory (up to 1.5TB) than Graviton3-based R7g instances. These instances are up to 30% faster for web applications, 40% faster for databases, and 45% faster for large Java applications compared to AWS Graviton3-based R7g instances. R8g instances are available in 12 different instance sizes, including two bare metal sizes. They offer up to 50 Gbps enhanced networking bandwidth and up to 40 Gbps of bandwidth to the Amazon Elastic Block Store (Amazon EBS). To learn more, see Amazon EC2 R8g Instances. To explore how to migrate your workloads to Graviton-based instances, see AWS Graviton Fast Start program and Porting Advisor for Graviton. To get started, see the AWS Management Console.

Amazon ElastiCache supports M7g and R7g Graviton3-based nodes in additional AWS Regions

Amazon ElastiCache now supports Graviton3-based M7g and R7g node families in the following AWS Regions: Canada (Calgary), Middle East & Africa (Bahrain, Cape Town, Dubai, Tel Aviv), Europe (Milan, Paris (introducing R7g), and Zurich), Asia Pacific (Hong Kong, Jakarta, Kuala Lumpur, Melbourne, and Osaka).\n ElastiCache Graviton3 nodes deliver improved price-performance compared to Graviton2. As an example, when running ElastiCache for Redis OSS on an R7g.4xlarge node, you can achieve up to 28% increased throughput (read and write operations per second) and up to 21% improved P99 latency, compared to running on R6g.4xlarge. In addition, these nodes deliver up to 25% higher networking bandwidth. For complete information on pricing and regional availability, please refer to the Amazon ElastiCache pricing page. To get started, create a new cluster or upgrade to Graviton3 using the AWS Management Console. For more information on supported node types, please refer to the documentation.

Amazon Q in Connect now supports selecting LLMs directly in Connect Web UI

Amazon Q in Connect, a generative AI-powered assistant for customer service, now enables contact center administrators to select different Large Language Models (LLMs) directly through the Amazon Connect web UI, providing a seamless AI Agent configuration experience. This no-code approach allows administrators to choose between LLM model families when building AI Agents to optimize for different business requirements. For example, you can select Amazon Nova Pro for faster response times, Anthropic Claude Sonnet for complex reasoning tasks, or switch between model families to optimize for different customer interaction types.\n For more information about the AWS Regions where Amazon Q in Connect is available, see the Amazon Connect features by Region documentation. To learn more about Amazon Q in Connect, please visit the website or see the help documentation. To learn more about Amazon Connect, the AWS contact center as a service solution on the cloud, please visit the Amazon Connect website.

AWS Blogs

AWS Japan Blog (Japanese)

AWS Big Data Blog

AWS Compute Blog

Containers

AWS Database Blog

AWS for Industries

Artificial Intelligence

Open Source Project

AWS CLI

Amplify for Android

Amazon EKS Anywhere