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AWS周报:GPT-6.1 Terra上线Bedrock

AWS Weekly Roundup: GPT-6.1 Terra on Bedrock, Step Functions as agent tools, and more (November 2, 2026)

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GPT-6.1 Terra的价格优势显著且已在Bedrock落地,Step Functions作为Agent工具的集成方案提供了可复用的工程范式,值得从业者关注。

The agentic launches that stayed with me last week had nothing to do with how capable a model is. They were about reach. AWS Step Functions, which already orchestrates over 220 AWS services, can now be handed to an agent as a tool, so workflows teams already trust became callable without a rewrite. In the same week, the AI blog published how one engagement platform exposed roughly 400 internal API operations the same way. Neither story involves rebuilding anything, only describing what exists and letting the agent find it.

上周令我印象深刻的 agentic(智能体)发布与模型的能力无关,而是关于覆盖范围。AWS Step Functions 已经编排了超过 220 个 AWS 服务,现在可以作为工具交给智能体使用,因此团队原本就信任的工作流无需重写即可被调用。同一周,AI 博客发布了一篇文章,介绍某个互动平台以相同方式暴露了大约 400 个内部 API 操作。这两个故事都不涉及重建任何东西,只是描述现有内容并让智能体去发现它们。

The other thread was cost. OpenAI’s newest Terra model reached Amazon Bedrock priced well below the model beside it, and two post-quantum launches landed for a deadline nobody can put on a calendar yet. Now, let’s get into this week’s AWS news…

另一个主题是成本。OpenAI 最新的 Terra 模型在 Amazon Bedrock 上的定价远低于其旁边的模型,此外还有两个后量子发布项目落地,尽管截止日期尚未明确到日历上。现在,让我们进入本周的 AWS 新闻……

Headlines

头条新闻

OpenAI GPT-6.1 Terra is now generally available on Amazon Bedrock, and what interests me is where it sits rather than what it tops. Terra is the everyday-workload line of the GPT-6 family. In OpenAI’s Agents’ Last Exam evaluation it scored 15 percentage points higher than GPT-5.6 Terra, performed on par with GPT-6 Astra, and completed tasks more than three times faster than both. Those are OpenAI’s figures, not an independent test. The price is what I would check first: input and output tokens are at least 50% lower than GPT-6.1 Sol and GPT-5.6 Terra. It takes up to 1 million input tokens with text and image input, and you can reach it from the Bedrock APIs or ChatGPT Work and Codex.

OpenAI GPT-6.1 Terra 现已在 Amazon Bedrock 上全面可用,而让我感兴趣的是它的定位而非它登顶了什么。Terra 是 GPT-6 系列中面向日常负载的型号。在 OpenAI 的 Agents’ Last Exam 评估中,它的得分比 GPT-5.6 Terra 高出 15 个百分点,表现与 GPT-6 Astra 持平,完成任务的速度比两者都快三倍以上。这些是 OpenAI 的数据,并非独立测试。价格是我首先会关注的:输入和输出 token 的价格至少比 GPT-6.1 Sol 和 GPT-5.6 Terra 低 50%。它支持最多 100 万个输入 token,可接受文本和图片输入,你可以通过 Bedrock APIs 或 ChatGPT Work 和 Codex 访问它。

AWS Step Functions workflows are now available as AI agent tools through Amazon Bedrock AgentCore Gateway, which connects agents to tools over the Model Context Protocol (MCP). The division of labor is the idea: the agent decides when to run a workflow and what input to pass; Step Functions runs each step exactly as you defined it. A support agent can trigger a refund, and the eligibility check, the manager approval, and the credit still happen in that order every time, because the ordering was never the model’s to improvise. Your existing Standard and Express workflows qualify as connector targets, and agents can also look up runs. It’s available in all Regions where AgentCore Gateway is, at standard rates.

AWS Step Functions 工作流现可通过 Amazon Bedrock AgentCore Gateway 作为 AI 智能体工具提供,该网关通过模型上下文协议(MCP)将智能体连接到工具。分工的理念在于:智能体决定何时运行工作流以及传递什么输入;Step Functions 则严格按照你定义的步骤执行每个环节。一个支持智能体可以触发退款流程,而资格检查、经理审批和信用额度发放等步骤每次都会按顺序发生,因为排序从来不是由模型即兴决定的。你现有的 Standard 和 Express 工作流均可作为连接器目标,智能体还可以查询运行记录。它在所有支持 AgentCore Gateway 的区域可用,按标准费率计费。

Last week’s launches

上周的发布

Here are some launches and updates from this past week that caught my attention:

以下是过去一周中引起我注意的一些发布和更新:

AWS Key Management Service now supports ML-KEM for post-quantum key encapsulation – You can now establish a shared secret with a post-quantum algorithm using AWS KMS keys, with private keys in FIPS 140-3 Level 3 validated HSMs. All three NIST FIPS 203 parameter sets are supported through Encapsulate, which produces a random 32-byte shared secret and its ciphertext, and Decapsulate, which recovers it. The threat is harvest now, decrypt later: an adversary records today’s key exchange and recovers the secret once quantum computers are powerful enough. It’s available everywhere KMS runs except the Middle East (UAE and Bahrain) and China Regions. Amazon Aurora PostgreSQL added post-quantum TLS key exchange the same week, on versions 18 and higher.

AWS 密钥管理服务 (KMS) 现已支持 ML-KEM 用于后量子密钥封装——您现在可以使用 AWS KMS 密钥与后量子算法建立共享密钥,其中私钥存储在通过 FIPS 140-3 Level 3 验证的 HSM 中。Encapsulate(生成随机 32 字节共享密钥及其密文)和 Decapsulate(恢复该密钥)均支持 NIST FIPS 203 的全部三个参数集。此举旨在应对“先收集、后解密”的威胁:攻击者记录当前的密钥交换过程,待量子计算机足够强大时再恢复密钥。该功能在除中东地区(阿联酋和巴林)和中国区域外的所有 KMS 运行区域可用。Amazon Aurora PostgreSQL 也在同一周对 18 及以上版本添加了后量子 TLS 密钥交换功能。

AWS IAM Identity Center now supports cross-Region trusted identity propagation – You can now carry a user’s identity with their request to AWS services in another Region. This removes a genuine architectural constraint: trusted identity propagation used to require every service accessing that identity to sit in the same Region, which left two unappealing options, broad IAM roles that cannot distinguish individual users, or consolidating all your services into a single Region. Now the identity travels with the request automatically, so you grant access by user and group membership and audit who accessed what. It’s available at no additional cost everywhere IAM Identity Center runs.

AWS IAM Identity Center 现已支持跨区域可信身份传播——您现在可以将用户的身份随请求一起携带至其他区域的 AWS 服务。这消除了一项真实的架构限制:以往可信身份传播要求访问该身份的每个服务都位于同一区域,导致只有两个不太理想的选项:无法区分单个用户的宽泛 IAM 角色,或将所有服务整合到单一区域。现在,身份会随请求自动传输,因此您可以按用户和用户组权限授予访问权,并审计谁访问了什么内容。该功能在 IAM Identity Center 运行的所有区域均可免费使用。

Amazon ECS now supports GPU sharing with NVIDIA Multi-Process Service (MPS) – You can now run multiple Amazon ECS tasks concurrently on a single NVIDIA GPU, the practical answer to work that only ever uses a fraction of one, like small-model inference and multi-model serving. You declare the GPU memory each container needs and can optionally cap its share of GPU compute, and ECS places tasks on GPUs with available capacity as your services scale, with no code changes. It works on ECS Managed Instances and ECS on Amazon EC2, and on Managed Instances it watches the MPS control daemon and replaces the instance if it turns unhealthy. It’s available in all commercial and AWS GovCloud (US) Regions.

Amazon ECS 现已支持通过 NVIDIA 多进程服务 (MPS) 进行 GPU 共享——您现在可以在单个 NVIDIA GPU 上并发运行多个 Amazon ECS 任务,这是针对仅使用少量 GPU 资源的工作负载(如小模型推理和多模型服务)的实际解决方案。您可以声明每个容器所需的 GPU 内存,并可酌情限制其占用的 GPU 计算份额;当您的服务扩展时,ECS 会将任务放置在具有可用容量的 GPU 上,且无需更改代码。该功能适用于 ECS Managed Instances 和 Amazon EC2 上的 ECS;对于 Managed Instances,它会监控 MPS 控制守护进程,并在实例变得不健康时替换该实例。该功能在所有商业区域和 AWS GovCloud (US) 区域均可用。

AWS Lambda supports Seekable OCI (SOCI) lazy loading for Lambda Managed Instances – You can now have AWS Lambda fetch only the files needed at each stage of startup instead of pulling a whole container image first, which AWS puts at up to 70% off container startup time. You create a SOCI index, push it to Amazon ECR, point the image URI at the indexed tag, and Lambda detects it automatically. The technique also reached Amazon SageMaker AI training and processing jobs, with benchmarks: lazy loading held at 3 to 11 seconds regardless of image size, against a median 3 minutes 42 seconds for a 13.2 GB image, a range they report as 8x to 46x.

AWS Lambda 支持 Seekable OCI (SOCI) 懒加载功能,用于 Lambda 托管实例——您现在可以让 AWS Lambda 仅在启动的每个阶段获取所需的文件,而不是先拉取整个容器镜像,从而将容器启动时间缩短高达 70%。您需要创建 SOCI 索引,将其推送到 Amazon ECR,并将镜像 URI 指向带索引的标签,Lambda 会自动检测到它。该技术也扩展到了 Amazon SageMaker AI 训练和处理作业,基准测试显示:无论镜像大小如何,懒加载时间保持在 3 到 11 秒之间,而 13.2 GB 镜像的中位时间为 3 分 42 秒,速度提升了 8 倍到 46 倍。

Amazon EKS Auto Mode now supports Kubernetes Gateway API – You can now declare how traffic reaches your applications with Gateway and HTTPRoute resources on Amazon EKS without installing a separate controller, and EKS Auto Mode provisions and manages the underlying AWS load balancing infrastructure. You get HTTP and gRPC routing, cross-namespace routing, weighted traffic splitting, header-based routing, and automatic TLS certificate discovery through AWS Certificate Manager. Existing Ingress workloads keep working alongside them, so this is additive rather than a migration. Gateway API support is included with EKS Auto Mode; standard load balancing charges apply.

Amazon EKS Auto Mode 现在支持 Kubernetes Gateway API——您现在可以在 Amazon EKS 上使用 Gateway 和 HTTPRoute 资源声明流量如何到达您的应用程序,而无需安装单独的控制器,EKS Auto Mode 会配置和管理底层 AWS 负载均衡基础设施。您可以获得 HTTP 和 gRPC 路由、跨命名空间路由、加权流量拆分、基于标头的路由,以及通过 AWS Certificate Manager 实现的自动 TLS 证书发现。现有的 Ingress 工作负载可以与它们并行运行,因此这是增量添加而非迁移。Gateway API 支持包含在 EKS Auto Mode 中;适用标准负载均衡费用。

For a full list of AWS announcements, be sure to keep an eye on the What’s New with AWS page.

如需查看完整的 AWS 公告列表,请务必关注 AWS What’s New 页面。

Other AWS news

其他 AWS 新闻

Here are some additional posts and resources that you might find interesting:

以下是一些您可能感兴趣的额外帖子和资源:

How Nubank automated disaster recovery with the AWS DevOps Agent – Nubank serves more than 140 million customers across Brazil, Mexico, and Colombia, and classifies over 300 business flows as critical, each tested on a regulator’s schedule. Nubank reports that handing evidence collection and report writing to the AWS DevOps Agent cut a test cycle from about 4.3 hours to roughly 40 minutes, and quadrupled flow coverage in 2026 to more than 160. One execution terminated more than 900 EKS instances under synthetic traffic with AWS Fault Injection Service, producing the evidence its regulator needed.

Nubank 如何利用 AWS DevOps Agent 实现灾难恢复自动化——Nubank 为巴西、墨西哥和哥伦比亚的超过 1.4 亿客户提供服务,并将 300 多个业务流程分类为关键业务,每个流程都按照监管机构的计划进行测试。Nubank 报告称,将证据收集和报告撰写工作交给 AWS DevOps Agent,将测试周期从约 4.3 小时缩短至约 40 分钟,并在 2026 年将流程覆盖率提高了四倍,达到 160 个以上。一次执行使用 AWS Fault Injection Service 在合成流量下终止了 900 多个 EKS 实例,生成了监管机构所需的证据。

How MoEngage turned over 400 APIs into agent tools with AgentCore Gateway – Roughly 400 internal REST API operations, built by 25 teams, sitting in private VPCs across seven Regions, with tenant identity that could never become a parameter the model gets to set. MoEngage estimates the managed path saved about six months of platform engineering. The detail worth stealing: a full tool listing would have crossed 20,000 tokens per connection, so agents search for tools by describing a task instead of receiving the catalog.

MoEngage 如何通过 AgentCore Gateway 将 400 多个 API 转化为代理工具——大约 400 个内部 REST API 操作,由 25 个团队构建,分布在七个区域的私有 VPC 中,且租户身份无法成为模型可设置的参数。MoEngage 估计,这种托管路径节省了约六个月的平台工程时间。值得借鉴的细节是:完整的工具列表会使每个连接超过 20,000 个 token,因此代理通过描述任务来搜索工具,而不是接收目录。

Reducing petabyte-scale S3 storage costs with evidence-based lifecycle rules – The hard part isn’t deciding to act, it’s knowing which data has gone cold and where it can safely live. This uses S3 Storage Lens groups and Storage Class Analysis to prove access patterns before moving anything. In the engagement described, 5.8 PB of logs in Amazon S3 Standard at approximately $241,000 per month showed an access ratio below 0.1% past 90 days, and a 90-day transition to Glacier Instant Retrieval cut the bill by roughly 70%, a figure the author ties to that workload.

基于证据的生命周期规则降低 PB 级 S3 存储成本——难点不在于决定采取行动,而在于知道哪些数据已变冷以及它们可以安全地存放在哪里。该方法利用 S3 Storage Lens 组和存储类别分析,在移动任何数据之前验证访问模式。在描述的案例中,位于 Amazon S3 Standard 的 5.8 PB 日志每月费用约为 241,000 美元,其在过去 90 天的访问率低于 0.1%,将其过渡到 Glacier Instant Retrieval(冰川即时检索)后,账单减少了约 70%,这一数字与作者所指的该工作负载相关。

Upcoming AWS events

即将举行的 AWS 活动

Check your calendar and sign up for upcoming AWS events:

查看您的日历并注册即将举行的 AWS 活动:

AWS re:Invent – re:Invent returns to Las Vegas from November 30 to December 4, with more than 2,200 sessions. The event catalog is live and reserved seating is open, so register and claim your spots before they fill up.

AWS re:Invent – re:Invent 将于 11 月 30 日至 12 月 4 日重返拉斯维加斯,提供超过 2,200 场会议。活动目录已上线,预留座位开放中,因此请尽早注册并抢占席位,以免满员。

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