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Amazon ECS Service Connect now supports seamless communication between services residing in different AWS accounts through integration with AWS Resource Access Manager (AWS RAM). This enhancement simplifies resource sharing, reduces duplication, and promotes consistent service-to-service communication across environments for organizations with multi-account architectures. Amazon ECS Service Connect leverages AWS Cloud Map namespaces for storing information about ECS services and tasks. To enable seamless cross-account communication between Amazon ECS Service Connect services, you can now share the underlying AWS Cloud Map namespaces using AWS RAM with individual AWS accounts, specific Organizational Units (OUs), or your entire AWS Organization. To get started, create a resource share in AWS RAM, add the namespaces you want to share, and sp

AWS Direct Connect now supports 4-byte Autonomous System (AS) numbers for virtual interfaces. Direct Connect uses the standard Border Gateway Protocol to provide customers with private connectivity to the AWS global network. However, customers with complex, multi-tenant network topologies or who need to maintain consistent AS numbering across their entire network can run into challenges with the maximum limit of 65,536 possible 2-byte AS numbers. With 4-byte AS numbers, customers can now use the entire range supported by RFC 6793, up to 4,294,967,294. Support for 4-byte AS numbers is now available in all AWS regions globally and on all Direct Connect virtual interface types. To get started, visit the AWS Direct Connect Console or use the updated APIs to create virtual interfaces with the new 4-byte AS numbers. For more information, check out the AWS Direct Connect documentation.

Starting today, Amazon Elastic Compute Cloud (Amazon EC2) M4 and M4 Pro Mac instances are now generally available (GA). M4 Mac instances offer up to 20% better application build performance compared to M2 Mac instances, while M4 Pro Mac instances deliver up to 15% better application build performance compared to M2 Pro Mac instances. These instances are ideal for building and testing applications for Apple platforms such as iOS, macOS, iPadOS, tvOS, watchOS, visionOS, and Safari. M4 and M4 Pro Mac instances are powered by the AWS Nitro System, providing up to 10 Gbps network bandwidth and 8 Gbps of Amazon Elastic Block Store (Amazon EBS) storage bandwidth. M4 Mac instances are built on Apple M4 Mac Mini computers featuring 10‑core CPU, 10‑core GPU, 24GB unified memory, and 16‑core Neural Engine. M4 Pro Mac instances feature a 14‑core CPU, 20‑core GPU, 48GB unified memory, and 16‑core Neural Engine. Both instance families come with a new 2TB instance store volume

We are pleased to announce general availability of Amazon EC2 P6-B200 instances on SageMaker notebooks. Amazon EC2 P6-B200 instances are powered by 8 NVIDIA Blackwell GPUs with 1440 GB of high-bandwidth GPU memory and 5th Generation Intel Xeon processors (Emerald Rapids). These instances deliver up to 2x better performance compared to P5en instances for AI training. Customers can use P6-B200 instances to interactively develop and fine-tune large foundation models, including LLMs, mixture of experts models, and multi-modal reasoning models. These instances enable efficient experimentation with larger models directly in JupyterLab or CodeEditor environments for generative AI applications such as enterprise copilots and content generation across text, images, and video. Amazon EC2 P6-B200 instances are available for SageMaker notebooks in the AWS US East (Ohio) and US West (Oregon) regions.

Today, AWS has introduced five new Elastic Fabric Adapter (EFA) metrics to enhance network observability for AI/ML and High Performance Computing (HPC) workloads. These new metrics help diagnose performance issues by tracking retransmitted packets and bytes, retransmit timeout events, impaired remote connection events, and unresponsive remote receiver events. With these new metrics, you can monitor for network congestion or instance configuration issues, allowing for timely action to maintain application performance. The metrics are implemented as counters at the per-EFA device level, accumulating data since instance launch or the most recent driver reset. Stored in the sys filesystem, these metrics counters are accessible via the instance command line. For enhanced monitoring and alerting capabilities, you can integrate these metrics into Prometheus scripts, facilitating export to third-party tools such as Grafana for dashboard creation and alarm setting. The new metrics a

Today, AWS announces remote connection from Visual Studio Code (VS Code) to Amazon SageMaker Unified Studio. This new capability allows developers to leverage their VS Code setup while accessing the scalable compute resources of Amazon SageMaker. By connecting VS Code to SageMaker Unified Studio, you can maintain your existing development workflows and configurations within a unified environment for AWS analytics and AI/ML services. SageMaker Unified Studio, part of the next generation of Amazon SageMaker, offers a broad set of fully managed cloud interactive development environments (IDE), including JupyterLab and Code Editor based on Code-OSS (Open Source Software) like VS Code. Starting today, you can use your customized local VS Code setup while accessing your compute resources and data in Amazon SageMaker. Authentication is simple and secure using the AWS Toolkit extension in VS Code. This integration provides a streamlined path from your local development environment

Today, AWS announces enhanced scanning capabilities for GuardDuty Malware Protection for Amazon S3. This launch increases scanning capabilities by raising the maximum file size limit from 5GB to 100 GB. Additionally, the archive processing capacity has been expanded to handle up to 10,000 files per archive, up from the previous limit of 1,000 files. GuardDuty Malware Protection for S3 is a fully managed threat detection service that automatically scans objects uploaded to S3 buckets and alerts customers of malware, viruses, and other malicious code before they can impact workloads or downstream processes. With this launch, GuardDuty S3 malware scanning now offers customers even better protection for large files and comprehensive archive collections stored in Amazon S3. The enhanced scanning capabilities are automatically enabled in all

We are excited to announce that AWS Deadline Cloud is now available in Asia Pacific (Seoul) and Europe (London). Deadline Cloud is a fully managed service that simplifies render management for teams creating computer-generated graphics and visual effects for films, television, broadcasting, web content, and design. Customers can now use Deadline Cloud to scale their render farms in regions that are close to their creative teams, enabling better integration with existing AWS services and creative pipelines. Deadline Cloud is now available in 10 AWS regions worldwide: US East (N. Virginia and Ohio), US West (Oregon), Asia Pacific (Seoul, Singapore, Sydney and Tokyo), and Europe (Frankfurt, Ireland, and London). For more information about AWS Regions and where Deadline Cloud is available, see the AWS Region table. To learn more about AWS Deadline Cloud and its regional availability, visit the AWS Deadline

Amazon Relational Database Service (RDS) Proxy now supports end-to-end IAM authentication for connections to Amazon Aurora and RDS database instances. This feature allows you to connect from your applications to your databases through RDS Proxy using AWS Identity and Access Management (IAM) authentication. End-to-end IAM authentication simplifies credential management, reduces credential rotation overhead, and enables you to leverage IAM's robust authentication and authorization capabilities throughout your database connection path. With end-to-end IAM authentication, you can now connect to your databases through RDS Proxy without needing to register or store credentials in Secrets Manager. End-to-end IAM authentication is available for MySQL and PostgreSQL database engines in all AWS Regions where RDS Proxy is supported. Many applications, including those built on modern serverless architectur

Amazon Elastic Container Service (Amazon ECS), a fully managed container orchestration service, now makes it easier to create and update task definitions in the AWS Management Console with generative AI assistance from Amazon Q Developer. This new capability helps customers complete their task definitions faster and more efficiently using AI-generated code suggestions. Customers can use the inline chat capability to ask Amazon Q Developer to generate, explain, or refactor task definition JSON with a conversational interface. You can inject generated suggestions at any point in the task definition and accept or reject the changes proposed. Amazon ECS has also enhanced the existing inline suggestions feature to utilize Amazon Q Developer. Now in addition to the existing property-based inline suggestions, the Amazon Q Developer suggestions can autocomplete whole blocks of sample code. These updates are available in