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AWS End User Messaging and Amazon SES now offer AI agent skills for the AWS MCP Server - devamazonaws.blogspot.com

AWS End User Messaging and Amazon SES now publish AI agent skills for the AWS MCP Server, enabling developers to build and send messages by asking their AI coding agent in plain language. Previously, developers had to navigate multiple documentation pages and management console screens to complete messaging tasks. Now, each skill provides your agent with step-by-step, validated guidance for tasks like verifying sending identities, building branded Rich Communication Services (RCS) agents, and sending production emails. These skills integrate with popular AI coding agents including Claude Code, Codex, Cursor, and Kiro. For example, you can ask Amazon SES to verify a sending identity and send your first production email. You can ask AWS End User Messaging to build a branded RCS agent and send yourself a rich message with cards and buttons. The skills eliminate the need to manually search documentation or switch between console screens, allowing you to complete messaging workflows direct...
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Amazon ElastiCache Global Datastore now supports tagging and tag-based access control - devamazonaws.blogspot.com

Amazon ElastiCache now supports resource tagging and tag-based access control (TBAC) for Global Datastore. Previously, ElastiCache supported tagging on all resources except Global Datastore, which prevented customers from applying a single, consistent permission and cost-allocation model across their ElastiCache fleet. With this launch, you can use AddTagsToResource, RemoveTagsFromResource, and ListTagsForResource on a Global Datastore, and reference those tags as conditions in IAM policies and Service Control Policies (SCPs) to grant permissions based on tag attributes rather than enumerating individual resources. Tag changes on a Global Datastore propagate automatically to every Region it spans, so access-control and cost-allocation policies stay consistent without per-Region operations. There is no additional cost for this feature, and no change to how you create or manage Global Datastores. This feature is available in all AWS Regions where ElastiCache Global Datastore is availab...
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[MS] When working with Win32 FILETIME, don't forget that you have std::chrono now - devamazonaws.blogspot.com

Some time ago, I was looking at a pull request, and saw that the code was manually calculating the "number of minutes since the last change" by doing annoying math. static const DWORD c_TicksPerSecond = 10000000; static const DWORD c_SecondsPerMinute = 60; uint64_t FileTimeToULongLong(FILETIME time) { ULARGE_INTEGER value; value.LowPart = time.dwLowDateTime; value.HighPart = time.dwHighDateTime; return value.QuadPart; } DWORD GetMinutesSinceLastChange() { FILETIME now; GetSystemTimeAsFileTime(&now); uint64_t now64 = FileTimeToULongLong(now); uint64_t last64 = FileTimeToULongLong(m_lastChange); if (now64 < last64) { return 0; } uint64_t diff = last64 - now64; return static_cast<DWORD>(diff / (static_cast<uint64_t>(c_dwSecondsPerMinute) * static_cast<uint64_t>(c_TicksPerSecond))); } Okay, first of all, we have helpers in the Windows Implementation Library (wil) to save you ...
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Amazon EMR on EKS now supports IPv6 Amazon EKS clusters - devamazonaws.blogspot.com

Today, AWS announces that Amazon EMR on EKS now supports running workloads on IPv6 Amazon Elastic Kubernetes Service (Amazon EKS) clusters. Amazon EMR on EKS enables data platform and analytics teams to run open-source big data frameworks such as Apache Spark and Apache Flink on Amazon EKS. With IPv6 support, teams operating at scale can now run these workloads on IPv6 Amazon EKS clusters, giving them access to the vastly larger address space of IPv6 as their analytics workloads grow. You can now scale large Spark and Flink workloads using the expanded IPv6 address space, which removes the need for IPv4 conservation workarounds such as secondary CIDR ranges or prefix delegation. High-executor jobs, such as 500-executor Spark jobs, can run concurrently without planning around address limits. To submit workloads, use StartJobRun, Spark Connect Interactive Endpoints, and Amazon SageMaker Unified Studio with no additional configuration, while the Flink, Livy, and Spark Operators are also ...
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[MS] Building the new GitHub Copilot Inline Suggestions Model: Part Two - devamazonaws.blogspot.com

See how GitHub Copilot added completions to its unified inline suggestions model, refined ghost text and editor behavior, and improved user satisfaction. Read the full article Post Updated on September 23, 2026 at 01:00AM Thanks for reading from devamazonaws.blogspot.com
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Amazon CloudWatch Omni: AI-first observability for agents and applications - devamazonaws.blogspot.com

AWS announces the general availability of Amazon CloudWatch Omni, an evolution of Amazon CloudWatch. Omni is an AI-powered observability experience organized around your teams and the applications they run, so that you can observe and troubleshoot your applications and agents in one place. It combines the interoperability of OpenTelemetry with the scale and reliability of CloudWatch. And it meets you wherever you work: a standalone web experience with single sign-on (SSO) for your team, or a local IDE extension for getting hands-on with your agents. With CloudWatch Omni, you create spaces in your central accounts to see telemetry across your AWS accounts and Regions, as well as other clouds, including Azure workloads. Omni automatically discovers services, maps dependencies, and surfaces golden metrics to help streamline your operational workflows. Using Omni, you can interact with telemetry however you prefer: via chat, through a guided point-and-click path in the console, or directl...
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Amazon EMR 7.14 is now available - devamazonaws.blogspot.com

Amazon EMR 7.14 is now available with new features across Amazon EMR on EC2, Amazon EMR on EKS, and Amazon EMR Serverless, along with version upgrades for additional applications. This release also upgrades Apache Spark to 3.5.8 and Apache Iceberg to 1.10.1. Apache Iceberg materialized views now refresh faster on tables with updates and deletes, using change data capture to read only the data files affected by a change. On Amazon EMR on EKS, clusters now support Spark Connect endpoints for interactive Spark sessions with token-based authentication, and can run workloads on IPv6 Amazon EKS clusters. On Amazon EMR Serverless, the storage limit for Spark jobs increases from 200 GiB to 1 TiB, giving more room for shuffle data. Amazon EMR 7.14 is available in all AWS Regions where Amazon EMR is available. To learn more, visit the Amazon EMR 7.14 Release Guide , or get started by creating a cluster from the Amazon EMR console . Post Updated on September 22, 2026 at 09:00AM
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