AWS News - 2026-09-19

Amazon Simple Notification Service (Amazon SNS) now supports message payloads up to 1 MiB, a 4x increase from the previous 256 KiB limit, so you can publish larger messages to your SNS topics.

Amazon SNS is a fully managed pub/sub messaging service that enables you to decouple and scale microservices, distributed systems, and serverless applications. As workloads such as application integration, IoT, and generative AI increasingly exchange larger volumes of data in a single message, the previous 256 KiB limit required customers to offload or split payloads before publishing.

With this launch, you can publish message payloads up to 1 MiB by setting the new MaximumMessageSize topic attribute on both SNS Standard and SNS FIFO topics. Topics with MaximumMessageSize set above 256 KiB support Amazon SQS, Amazon Data Firehose, and AWS Lambda subscriptions, with up to 100 total subscriptions per topic.

Amazon SNS 1 MiB support is available today in all AWS Regions where Amazon SNS is available. To learn more about sending large payloads with Amazon SNS, see the Amazon SNS Developer Guide. 

 

Amazon Bedrock continues to expand its open weight model portfolio with the same security and governance that customers rely on. Today, Kimi K3 from Moonshot AI is generally available on Amazon Bedrock, giving you a powerful new option for coding and knowledge work.

According to Moonshot AI, Kimi K3 is its most capable model and the first open model to reach 2.8 trillion parameters. It combines native vision capabilities with a 1-million-token context window, making it well suited to long-running coding sessions across large repositories, multi-document analysis including scanned pages and screenshots, and extended agent workflows. Moonshot AI reports an approximate 2.5x improvement in scaling efficiency over Kimi K2. On Amazon Bedrock, Kimi K3 runs within the same security boundary as proprietary models, and the same controls for access, encryption, and auditing across your model portfolio. Kimi K3 is the first open weight model on Amazon Bedrock to support explicit prompt caching, helping reduce latency and input costs when reusing context across model calls.

Kimi K3 is available in all AWS Regions where Amazon Bedrock is available through cross-Region inferencing. To get started, visit the Amazon Bedrock Console. To learn more, see the Amazon Bedrock documentation and read the launch blog post.

AWS is announcing starting today, Amazon EC2 I7ie instances are now available in AWS Israel (Tel Aviv) region. Designed for large storage I/O intensive workloads, I7ie instances are powered by 5th Gen Intel Xeon Processors with an all-core turbo frequency of 3.2 GHz, offering up to 40% better compute performance and 20% better price performance over existing I3en instances. I7ie instances offer up to 120TB local NVMe storage density for storage optimized instances and offer up to twice as many vCPUs and memory compared to prior generation instances. Powered by 3rd generation AWS Nitro SSDs, I7ie instances deliver up to 65% better real-time storage performance, up to 50% lower storage I/O latency, and 65% lower storage I/O latency variability compared to I3en instances.

I7ie are high density storage optimized instances, ideal for workloads requiring fast local storage with high random read/write performance at very low latency consistency to access large data sets. These instances are available in 9 different virtual sizes and deliver up to 100Gbps of network bandwidth and 60Gbps of bandwidth for Amazon Elastic Block Store (EBS).

To learn more, visit the I7ie instances page.

Amazon Elastic Container Service Express Mode now supports specifying ARM64 as the CPU architecture for your service, making it easy to deploy ARM-based container images on AWS Graviton-powered compute and benefit from up to 40% better price-performance compared to x86-based instances.

Amazon ECS Express Mode makes it easy to rapidly launch containerized applications, including web applications and APIs, by orchestrating and managing the cloud architecture for your application. You provide your container image, and ECS Express Mode handles the rest, configuring networking, load balancing, auto scaling, and deployments, and providing your application with an auto-generated URL. With ARM64 architecture support, you can choose the compute architecture that fits your workload, whether you're optimizing for cost with Graviton, matching your existing fleet, or deploying images built natively for ARM.

You can configure the CPU architecture for new and existing Amazon ECS Express Mode services using the AWS Management Console, AWS CLI, AWS SDKs, and infrastructure as code (IaC) tools. This capability is available in all AWS commercial Regions and AWS GovCloud (US) Regions. To learn more, see the ECS Express Mode documentation.

AWS Continuum for penetration testing is a frontier agent that proactively secures applications throughout the development lifecycle by offering on-demand, customized penetration testing with real exploitability testing. Developers and security teams can now test login credentials and receive suggested domains before a penetration test runs. This makes it easier to configure an accurate network scope from the start, reducing misconfiguration and wasted test cycles.

Previously, identifying all the URLs your application reaches required manual effort, and authentication failures were only discovered after a full test cycle completed, costing time and resources. With this launch, when you add login credentials during test configuration, AWS Continuum authenticates into your application exactly as a real user would, capturing every accessible domain reached during login and surfacing them as in-scope URL suggestions. You can review accessible domains, validate credentials, and confirm the agent covers the right endpoints, all before the real test begins. Accessible domains are returned regardless of whether the credential test succeeds, fails, or times out. You can learn more about this feature in our updated documentaiton.

This capability is available in all regions where AWS Continuum for penetration testing is available and is detailed on the AWS Continuum product page.

Starting today, Amazon Elastic Compute Cloud (Amazon EC2) X8i instances are available in the South America (São Paulo) region. These instances are powered by custom Intel Xeon 6 processors available only on AWS. X8i instances are SAP-certified and deliver the highest performance and fastest memory bandwidth among comparable Intel processors in the cloud. They deliver up to 43% higher performance, 1.5x more memory capacity (up to 6TB), and 3.3x more memory bandwidth compared to previous generation X2i instances.

X8i instances are designed for memory-intensive workloads like SAP HANA, large databases, data analytics, and Electronic Design Automation (EDA). Compared to X2i instances, X8i instances offer up to 50% higher SAPS performance, up to 47% faster PostgreSQL performance, 88% faster Memcached performance, and 46% faster AI inference performance. X8i instances come in 14 sizes, from large to 96xlarge, including two bare metal options.

To get started, visit the AWS Management Console. X8i instances can be purchased via Savings Plans, On-Demand instances, and Spot instances. For more information visit X8i instances page.

今月は「エージェントに現場を任せるとき、境界線をどこに引くか」をピックアップトピックとしてお届けしつつ、8 月に公開された製造業向けのブログとサービスアップデートをご紹介します。

先週、Kiro Crew をフルタイムで開発している私たち3人は、7日間で 1,000 件の pull request をマージしました。1日あたり 120 件を超え、そのすべてが CI とレビューを通っています。Kiro Crew は、このフルタイムのエンジニア3人を中心に、500 人近い熱心なコミュニティコントリビューターとともに開発されています。 この数字を狙っていたわけではありません。並行して開発を進めるやり方が次々に限界にぶつかり、それを越えるたびに少しずつ到達した結果です。ボトルネックにぶつかるたびに、1人がより多くのセッションを回せる新しい進め方が生まれました。振り返ると、その変化は5つの段階に整理できます。最新の段階が、私たちが Crew Mode と呼んでいるものです。コーディングエージェントを使っているなら、あなたもこの梯子のどこかにいます。そして今いる段階が、次に壊れるものを教えてくれます。

ReadyOn runs a multi-tenant platform on Amazon EKS that handles highly sensitive enterprise data. This post describes their Four Walls model: four independent layers of tenant isolation combining Kubernetes namespaces, Karpenter node pools, Amazon VPC security groups, and per-tenant Amazon Aurora databases for zero-trust defense in depth.

Deploy production-ready Hugging Face models on Amazon SageMaker AI using six open-source agent skills. Point a coding agent at a model and get back a real-time endpoint with the right serving container, autoscaling, Amazon CloudWatch alarms, and a verified teardown path.

Today we are announcing the new AgentCore runtime, a capability of Amazon Bedrock AgentCore built for the speed, flexibility, and cost efficiency that production agents demand. It reclaims memory as sessions release it and delivers consistent cold starts regardless of image size or concurrency.

Migrate a multi-model healthcare AI agent from self-managed Amazon ECS with AWS Fargate to Amazon Bedrock AgentCore runtime, preserving triple-model orchestration and vector-enhanced knowledge retrieval while reducing infrastructure management. The framework-agnostic pattern applies across healthcare, financial services, and manufacturing.

Kimi K3 from Moonshot AI is now available on Amazon Bedrock, giving you a powerful new open-weight option for coding and knowledge work. It offers native vision, a 1-million-token context window, and explicit prompt caching to reduce latency and input costs.

Amazon SageMaker AI shipped 13 inference launches in year-to-date across two deployment paths: fully managed endpoints and Amazon SageMaker HyperPod Inference. This post reviews each launch, from inference recommendations and capacity-aware instance pools to tiered KV caching and disaggregated prefill and decode.

Learn how to run AI agent tool calls in secure, isolated sandboxes using AWS Lambda MicroVMs. This post shows how to architect a self-hosted control plane that launches a fresh, VM-isolated MicroVM for each agent session, keeping credentials, networking, and governance entirely within your own AWS account.