借助 Claude Code 和 Amazon Bedrock 加速受监管工作负载

请注意，以下文章仅供参考。下文详述的方法未必适用于所有组织或合规计划。请务必根据您所在组织的合规要求及您可能承担的任何适用监管义务，对该潜在解决方案进行评估。

Anthropic Claude Opus 5.5 和 Claude Sonnet 5.5 在 AWS GovCloud（US）区域上线，为具有监管或合规要求（包括《国际武器贸易条例》ITAR）的工作负载引入了 AI 辅助开发的接入路径。Claude Sonnet 5 拥有 FedRAMP Class D（原 High）认证以及 DoD Impact Level 4 和 5（IL4/IL5）授权；Claude Opus 5.5 和 Claude Sonnet 5.5 则已在 Amazon Bedrock 上获得 FedRAMP Class D 认证（查看当前模型认证状态）。

本文将探讨如何在 AWS GovCloud（US）中的 Amazon Bedrock 上，结合 Anthropic 的 Agent 编程工具 Claude Code 使用这些模型。借助这一方案，您可以在保持合规一致性的同时，运行能够加快日常开发任务的 AI 辅助工作流。

AWS GovCloud（US）中的 Amazon Bedrock

AWS GovCloud（US）区域专为具有更高合规需求的美国客户设计。您可以将生成式 AI 工作负载部署到敏感环境中，同时维持合规控制。Amazon Bedrock 内置了以安全为中心的功能，包括：

内置数据保护：客户内容不会被存储、记录，或用于训练 AWS 模型，也不会与第三方共享。

FedRAMP Class D（原 High）认证和 DoD 云服务提供商（CSP）SRG IL4/IL5 授权路径，可支持政府机构的合规要求。有关当前模型级别的认证状态，请参阅 Amazon Bedrock 模型合规页面。

与 AWS GovCloud（US）中现有安全控制措施和合规框架集成，在提供额外授权路径的同时，维持与其他 AWS 区域相同的高安全标准。

AWS GovCloud（US）中的 Amazon Bedrock 支持两种端点接口：bedrock-runtime 和 bedrock-mantle。二者均由相同的底层 Mantle 推理引擎和零操作员访问（Zero Operator Access，ZOA）架构驱动。bedrock-runtime 端点使用 AWS SDK（InvokeModel 和 Converse API），并支持 Amazon Bedrock Guardrails、Amazon Bedrock Knowledge Bases、Agents 和调用日志记录。因此，它是大多数新应用程序的推荐选择，尤其适用于需要审计追踪的应用。bedrock-mantle 端点原生支持 Anthropic Messages API，并提供目前仅在该接口上可用的功能，例如服务端工具、后台推理和 Projects。这两个端点均可用于 Claude Opus 5.5、Claude Sonnet 5.5 和 Claude Sonnet 5；其中，bedrock-runtime 在两个 AWS GovCloud（US）区域（US-West 和 US-East）均可用，bedrock-mantle 则在 AWS GovCloud（US-West）可用。

Claude Code

Claude Code 是 Anthropic 的 Agent 编程工具，能够读取您的代码库、编辑文件、运行命令，并与您的开发工具集成。它由 AWS GovCloud（US）中 Amazon Bedrock 上的 Claude Opus 5.5、Claude Sonnet 5.5 等模型驱动，可直接在终端、首选集成开发环境（IDE）如 VS Code 和 JetBrains 中运行，也可借助 Claude Agent SDK 在后台运行。Claude Code 能够理解整个代码库，并可跨多个文件和工具协作完成任务。Claude Code 可以：

• 在整个代码库中编写代码并修复跨多个文件的 bug。
• 解答有关代码架构和逻辑的问题。
• 执行并修复测试、代码检查及其他命令。
• 搜索 Git 历史记录、解决合并冲突，以及创建提交和拉取请求。
• 通过 Model Context Protocol（MCP）连接外部工具和数据源，包括 AWS Command Line Interface（AWS CLI）、Terraform 和 Kubernetes。
• 启动可同时处理任务不同部分的子 Agent。
• 使用 CLAUDE.md 记忆文件、用于可重复工作流的 skills，以及用于操作前后自动化的 hooks来自定义行为。
• 通过 GitHub Actions 或 GitLab CI/CD 自动执行重复性任务，并与持续集成和持续交付（CI/CD）集成。

如需了解更多信息，请参阅 Anthropic 的文章：Claude Code 教程和 Claude Code：Agent 编程最佳实践。

解决方案概览：在 AWS GovCloud（US）中尝试将 Claude Code 与 Amazon Bedrock 配合使用

本节提供逐步说明，介绍如何设置和配置 Claude Code，使其能在 AWS GovCloud（US）中与 Amazon Bedrock 协同工作，包括前提条件、安装命令、环境配置和验证步骤。

前提条件

开始前，请确保已具备以下条件：

• 已拥有可访问 Amazon Bedrock 的 AWS GovCloud（US）账户。
• 已为 Amazon Bedrock 配置适当的 AWS Identity and Access Management（IAM）角色和权限。您的 IAM 策略至少应包括：
  • 对于 bedrock-runtime：bedrock:InvokeModel、bedrock:InvokeModelWithResponseStream、bedrock:ListInferenceProfiles 和 bedrock:GetInferenceProfile。
  • 对于 bedrock-mantle（如果使用 Mantle 端点）：bedrock-mantle:CreateInference、bedrock-mantle:GetProject、bedrock-mantle:ListProjects 和 bedrock-mantle:ListModels。
  • 或者，附加 AmazonBedrockMantleInferenceAccess 托管策略。
• 已在 AWS GovCloud（US）账户中启用对 Claude Opus 5.5、Claude Sonnet 5.5 和 Claude Sonnet 5 的 Amazon Bedrock 模型访问权限。
• 已配置使用短期 API 密钥或 AWS SSO 登录获取的有效 AWS 会话凭证的 AWS CLI。

在 AWS GovCloud（US）中设置 Claude Code 与 Amazon Bedrock

使用您的凭证配置 AWS CLI 后，请使用以下任一方法安装 Claude Code：

macOS、Linux、WSL：

curl -fsSL https://claude.ai/install.sh | bash

Windows PowerShell：

irm https://claude.ai/install.ps1 | iex

Windows CMD：

curl -fsSL https://claude.ai/install.cmd -o install.cmd && install.cmd && del install.cmd

Homebrew（macOS/Linux）：

brew install --cask claude-code

如需其他安装方法，请参阅 Claude Code 安装文档。

选项 A：交互式设置向导（推荐）

1. 进入您的项目：
2. 启动 Claude Code：
3. 按登录向导操作：

在登录提示中，选择 3rd-party platform，然后选择 Amazon Bedrock。按照向导提示选择身份验证方式、区域（us-gov-west-1），并固定您的模型。该向导会自动将配置保存到您的设置文件中。

如果您此前已经配置过 Claude Code，请运行 /setup-bedrock 重新打开向导，并更新凭证、区域或固定的模型。

选项 B：手动配置环境变量

对于脚本化或企业部署，请设置以下环境变量：

export CLAUDE_CODE_USE_BEDROCK=1
export AWS_REGION='us-gov-west-1'
export ANTHROPIC_MODEL='us-gov.anthropic.claude-sonnet-5-5'

若要改用 Claude Opus 5.5 作为主模型：

export ANTHROPIC_MODEL='us-gov.anthropic.claude-opus-5-5'

若要固定特定模型版本，以实现一致的团队部署：

export ANTHROPIC_DEFAULT_OPUS_MODEL='us-gov.anthropic.claude-opus-5-5'
export ANTHROPIC_DEFAULT_SONNET_MODEL='us-gov.anthropic.claude-sonnet-5-5'

然后进入您的项目并启动 Claude Code：

cd your-code-project
claude

选项 C：使用 Bedrock Mantle 端点

Bedrock Mantle 原生支持 Anthropic Messages API，可在 AWS GovCloud（US-West）中使用。要通过 Mantle 路由 Claude Code：

export CLAUDE_CODE_USE_MANTLE=1
export AWS_REGION='us-gov-west-1'

当同一会话中同时需要 bedrock-runtime 和 bedrock-mantle 时：

export CLAUDE_CODE_USE_BEDROCK=1
export CLAUDE_CODE_USE_MANTLE=1

注意：Guardrails 和调用日志记录仅可通过 bedrock-runtime 端点使用。对于需要这些合规功能的部署，请使用 bedrock-runtime 端点（选项 A 或 B）。

验证您的配置

通过检查终端中是否出现 Welcome to Claude Code! 消息，验证 Claude Code 是否正在运行。运行 /status 命令以确认模型和提供商。根据您的配置，提供商行应显示 Amazon Bedrock 或 Amazon Bedrock (Mantle)。

如需详细了解如何为 Amazon Bedrock 配置 Claude Code，请参阅 Amazon Bedrock 上的 Claude Code。

在组织内部署 Claude Code 时的注意事项

Claude Code 现已正式发布，下一步是决定如何在整个组织内进行部署。请考虑安全、治理和合规方面的基础架构：

使用 AWS IAM Identity Center 集中治理对 Claude Code 的身份和访问权限。 这样可确保仅经授权的开发者能够访问。此外，借助 IAM Identity Center，开发者可通过临时的、基于角色的凭证访问资源，从而免除使用静态访问密钥的需求并有助于提升安全性。打开 Claude Code 前，请使用 aws configure sso --profile <PROFILE_NAME> 配置 AWS CLI 以使用 IAM Identity Center 配置文件。随后，使用所创建的配置文件登录：aws sso login --profile <PROFILE_NAME>。

考虑自动配置默认环境变量。 这包括本文列出的环境变量，例如 AWS_REGION、CLAUDE_CODE_USE_BEDROCK、ANTHROPIC_MODEL、ANTHROPIC_DEFAULT_OPUS_MODEL 和 ANTHROPIC_DEFAULT_SONNET_MODEL。这将配置 Claude Code 自动连接到 Amazon Bedrock，为跨团队开发提供一致的基线。组织可先向开发者提供自助式操作说明，或使用设置文件集中管理配置。

对于大型企业部署，请考虑实施 适用于 Amazon Bedrock 的 Claude Code 指南。 该指南帮助组织在严格控制 AI 资源访问权限的同时部署 Claude Code，对接现有身份基础设施，并提供开发者生产力和使用模式的可观测性。

审查服务配额，并根据活跃开发者数量设置适当的每分钟 Token 数（TPM）和每分钟请求数（RPM）。 请确保拥有足够的 TPM 和 RPM 配额来支持团队使用。相关指导请遵循速率限制建议。

固定模型版本以实现一致的团队部署。 如果未固定版本，sonnet 和 opus 等模型别名将解析到 Claude Code 的内置默认模型，而默认模型可能在不同版本间发生变化。Claude Code 默认将 Claude Opus 5.5 用作主模型，因此未固定版本的部署将按 Opus 的每 Token 费率计费。若要让团队持续使用 Claude Sonnet 5.5，请将 ANTHROPIC_MODEL 设置为其完整模型 ID。使用 ANTHROPIC_DEFAULT_OPUS_MODEL 和 ANTHROPIC_DEFAULT_SONNET_MODEL 控制团队迁移至新模型的时机。在 AWS GovCloud（US）中，请对跨区域推理配置文件 ID 使用 us-gov. 前缀。

实施成本监控和按用户划分的 Token 防护机制。 Claude Code 会话可能消耗大量 Token，特别是 Claude Opus 5.5，其每 Token 成本高于 Claude Sonnet 5.5。根据 Anthropic 的说法，Claude Opus 5.5 相比 Claude Opus 5 使用更少 Token 完成任务，并且每 Token 价格更低。请考虑以下措施：

• 实施按用户划分的 Token 防护机制，为每位开发者强制执行每日 Token 限额，并在达到 80% 和 100% 阈值时发出告警。该模式使用 Amazon CloudWatch 调用日志、AWS Lambda 和 Amazon DynamoDB，以近实时方式跟踪和强制执行限额。
• 使用提示词缓存来降低成本并改善响应时间。5 分钟和 [1-h

Please note that the following post is intended for informational purposes only. The approach detailed below may not be suitable for all organizations or compliance programs. It is important to evaluate this potential solution against the compliance requirements of your organization and any applicable regulatory obligations you may have.

The availability of Anthropic Claude Opus 5.5 and Claude Sonnet 5.5 in the AWS GovCloud (US) Regions introduces an on-ramp for AI-assisted development for workloads with regulatory or compliance requirements, including International Traffic in Arms Regulations (ITAR). Claude Sonnet 5 holds FedRAMP Class D (formerly High) certification and DoD Impact Level 4 and 5 (IL4/IL5) authorization, and Claude Opus 5.5 and Claude Sonnet 5.5 hold FedRAMP Class D certification on Amazon Bedrock (verify current model certification status).

In this post, we explore how to use these models on Amazon Bedrock in AWS GovCloud (US) with Claude Code, Anthropic’s agentic coding tool. With this solution, you can run AI-assisted workflows that speed up everyday development tasks while maintaining compliance alignment.

Amazon Bedrock in AWS GovCloud (US)

AWS GovCloud (US) Regions are designed specifically for US customers with elevated compliance needs. You can deploy generative AI workloads to sensitive environments while maintaining compliance controls. Amazon Bedrock is built with security-focused features, including:

Built-in data protection where customer content isn’t stored, logged, or used to train AWS models or shared with third parties.

FedRAMP Class D (formerly High) certification and DoD Cloud Service Provider (CSP) SRG IL4/IL5 authorization pathways, supporting government agencies’ compliance requirements. See the Amazon Bedrock models compliance page for current model-level certification status.

Integration with existing security controls and compliance frameworks available in AWS GovCloud (US), maintaining the same high security standards as other AWS Regions while providing additional authorization pathways.

Amazon Bedrock in AWS GovCloud (US) supports two endpoint surfaces, bedrock-runtime and bedrock-mantle, both powered by the same underlying Mantle inference engine with Zero Operator Access (ZOA) architecture. The bedrock-runtime endpoint uses the AWS SDK (InvokeModel and Converse APIs) and supports Amazon Bedrock Guardrails, Amazon Bedrock Knowledge Bases, Agents, and invocation logging. This makes it the recommended choice for most new applications, particularly those requiring audit trails. The bedrock-mantle endpoint supports the Anthropic Messages API natively and provides access to capabilities currently available only on that surface, such as server-side tools, background inference, and Projects. Both endpoints are available for Claude Opus 5.5, Claude Sonnet 5.5, and Claude Sonnet 5, with bedrock-runtime available in both AWS GovCloud (US) Regions (US-West and US-East) and bedrock-mantle available in AWS GovCloud (US-West).

Claude Code

Claude Code is Anthropic’s agentic coding tool that reads your codebase, edits files, runs commands, and integrates with your development tools. Powered by models such as Claude Opus 5.5 and Claude Sonnet 5.5 on Amazon Bedrock in AWS GovCloud (US), it operates directly in your terminal, your preferred integrated development environments (IDEs) such as VS Code and JetBrains, and in the background with the Claude Agent SDK. Claude Code understands your entire codebase and can work across multiple files and tools to get things done. Claude Code can:

• Write code and fix bugs spanning multiple files across your codebase.
• Answer questions about your code’s architecture and logic.
• Execute and fix tests, linting, and other commands.
• Search through Git history, resolve merge conflicts, and create commits and pull requests.
• Connect to external tools and data sources with the Model Context Protocol (MCP), including the AWS Command Line Interface (AWS CLI), Terraform, and Kubernetes.
• Spawn sub-agents that work on different parts of a task simultaneously.
• Customize behavior with CLAUDE.md memory files, skills for repeatable workflows, and hooks for pre/post-action automation.
• Automate recurring tasks and integrate with continuous integration and continuous delivery (CI/CD) through GitHub Actions or GitLab CI/CD.

To learn more, see Anthropic’s articles: Claude Code tutorials and Claude Code: Best practices for agentic coding.

Solution overview: Try Claude Code with Amazon Bedrock in AWS GovCloud (US)

This section provides step-by-step instructions for setting up and configuring Claude Code to work with Amazon Bedrock in AWS GovCloud (US), including prerequisites, installation commands, environment configuration, and verification steps.

Prerequisites

Before you get started, make sure that you have the following in place:

• An AWS GovCloud (US) account with access to Amazon Bedrock.
• Appropriate AWS Identity and Access Management (IAM) roles and permissions for Amazon Bedrock. At minimum, your IAM policy should include:
  • For bedrock-runtime: bedrock:InvokeModel, bedrock:InvokeModelWithResponseStream, bedrock:ListInferenceProfiles, and bedrock:GetInferenceProfile.
  • For bedrock-mantle (if using the Mantle endpoint): bedrock-mantle:CreateInference, bedrock-mantle:GetProject, bedrock-mantle:ListProjects, and bedrock-mantle:ListModels.
  • Alternatively, attach the AmazonBedrockMantleInferenceAccess managed policy.
• Amazon Bedrock model access to Claude Opus 5.5, Claude Sonnet 5.5, and Claude Sonnet 5 enabled in your AWS GovCloud (US) account.
• AWS CLI configured with valid AWS session credentials using short-term API keys or AWS SSO login.

Set up Claude Code with Amazon Bedrock in AWS GovCloud (US)

After configuring AWS CLI with your credentials, install Claude Code using one of the following methods:

macOS, Linux, WSL:

curl -fsSL https://claude.ai/install.sh | bash

Windows PowerShell:

irm https://claude.ai/install.ps1 | iex

Windows CMD:

curl -fsSL https://claude.ai/install.cmd -o install.cmd && install.cmd && del install.cmd

Homebrew (macOS/Linux):

brew install --cask claude-code

For additional installation methods, see Claude Code installation docs.

Option A: Interactive setup wizard (recommended)

1. Navigate to your project:
2. Launch Claude Code:
3. Run through the login wizard:

At the login prompt, select 3rd-party platform , then Amazon Bedrock. Follow the wizard prompts to choose your authentication method, region (us-gov-west-1), and pin your models. The wizard saves configuration to your settings file automatically.

If you have previously configured Claude Code, run /setup-bedrock to reopen the wizard and update your credentials, region, or model pins.

Option B: Manual environment variable configuration

For scripted or enterprise deployments, set the following environment variables:

export CLAUDE_CODE_USE_BEDROCK=1
export AWS_REGION='us-gov-west-1'
export ANTHROPIC_MODEL='us-gov.anthropic.claude-sonnet-5-5'

To use Claude Opus 5.5 as the primary model instead:

export ANTHROPIC_MODEL='us-gov.anthropic.claude-opus-5-5'

To pin specific model versions for consistent team deployments:

export ANTHROPIC_DEFAULT_OPUS_MODEL='us-gov.anthropic.claude-opus-5-5'
export ANTHROPIC_DEFAULT_SONNET_MODEL='us-gov.anthropic.claude-sonnet-5-5'

Then navigate to your project and launch Claude Code:

cd your-code-project
claude

Option C: Using the Bedrock Mantle endpoint

Bedrock Mantle supports the Anthropic Messages API natively and is available in AWS GovCloud (US-West). To route Claude Code through Mantle:

export CLAUDE_CODE_USE_MANTLE=1
export AWS_REGION='us-gov-west-1'

When both bedrock-runtime and bedrock-mantle are needed in the same session:

export CLAUDE_CODE_USE_BEDROCK=1
export CLAUDE_CODE_USE_MANTLE=1

Note: Guardrails and invocation logging are available exclusively through the bedrock-runtime endpoint. For deployments requiring these compliance features, use the bedrock-runtime endpoint (Option A or B).

Verify your configuration

Verify that Claude Code is running by checking for the Welcome to Claude Code! message in your terminal. Run the /status command to confirm your model and provider. The provider line should show Amazon Bedrock or Amazon Bedrock (Mantle) depending on your configuration.

To learn more about configuring Claude Code for Amazon Bedrock, see Claude Code on Amazon Bedrock.

Considerations when deploying Claude Code to your organization

With Claude Code now generally available, the next step is deciding how to deploy it across your organization. Consider your foundational architecture for security, governance, and compliance:

Use AWS IAM Identity Center to centrally govern identity and access to Claude Code. This verifies that only authorized developers have access. Additionally, using IAM Identity Center, developers can access resources with temporary, role-based credentials, alleviating the need for static access keys and helping enhance security. Prior to opening Claude Code, make sure that you configure AWS CLI to use an IAM Identity Center profile by using aws configure sso --profile <PROFILE_NAME>. Then log in using the profile you created: aws sso login --profile <PROFILE_NAME>.

Consider automated configuration of default environment variables. This includes the environment variables outlined in this post, such as AWS_REGION, CLAUDE_CODE_USE_BEDROCK, ANTHROPIC_MODEL, ANTHROPIC_DEFAULT_OPUS_MODEL, and ANTHROPIC_DEFAULT_SONNET_MODEL. This will configure Claude Code to automatically connect to Amazon Bedrock, providing a consistent baseline for development across teams. Organizations can start by providing developers with self-service instructions, or use settings files to manage configuration centrally.

Consider implementing Guidance for Claude Code with Amazon Bedrock for large enterprise deployments. The guidance helps organizations deploy Claude Code while maintaining strict control over AI resource access, connecting to existing identity infrastructure and providing observability for developer productivity and usage patterns.

Review service quotas and set appropriate tokens per minute (TPM) and requests per minute (RPM) based on the number of active developers. Make sure that you have enough TPM and RPM quotas to support your team’s usage. For guidance, follow the rate limit recommendations.

Pin model versions for consistent team deployments. Without pinning, model aliases such as sonnet and opus resolve to Claude Code’s built-in defaults, which may change between releases. Claude Code defaults to Claude Opus 5.5 as its primary model, so an unpinned deployment is billed at the Opus per-token rate. To keep teams on Claude Sonnet 5.5, set ANTHROPIC_MODEL to its full model ID. Use ANTHROPIC_DEFAULT_OPUS_MODEL and ANTHROPIC_DEFAULT_SONNET_MODEL to control when your team moves to a new model. In AWS GovCloud (US), use the us-gov. prefix for cross-region inference profile IDs.

Implement cost monitoring and per-user token guardrails. Claude Code sessions can be token-intensive, particularly with Claude Opus 5.5, which carries a higher per-token cost than Claude Sonnet 5.5. According to Anthropic, Claude Opus 5.5 completes tasks using fewer tokens than Claude Opus 5, at a lower price per token. Consider the following:

• Implement per-user token guardrails to enforce daily token limits per developer, with alerting at 80% and 100% thresholds. This pattern uses Amazon CloudWatch invocation logging, AWS Lambda, and Amazon DynamoDB to track and enforce limits in near real time.
• Use prompt caching to reduce costs and improve response times. Both 5-minute and 1-hour TTL options are available for supported models.
• Consider defaulting teams to Claude Sonnet 5.5 (lower cost than Claude Opus 5.5) and reserving Claude Opus 5.5 for tasks requiring deeper reasoning or longer autonomous runs. For workloads that require IL4/IL5 authorization, default to Claude Sonnet 5.

See the Claude Code Monitoring Implementation guide for additional observability patterns.

Consider permissions, memory, and MCP servers for your organization. Security teams can configure managed permissions for what Claude Code is and is not allowed to do, which cannot be overwritten by local configuration. In addition, you can configure CLAUDE.md memory files across projects to auto-add common workflows, style conventions, and coding standards to align with your organization’s preferences. Deploy your CLAUDE.md file into an enterprise directory so all developers inherit the same baseline. Use hooks to enforce pre/post-action automation such as auto-formatting or lint checks.

Choose the appropriate endpoint for your compliance requirements. The bedrock-runtime endpoint supports Guardrails, invocation logging, and cross-region inference within both AWS GovCloud (US) Regions (US-West and US-East). The bedrock-mantle endpoint supports the Anthropic Messages API natively and is available in AWS GovCloud (US-West). Guardrails and invocation logging are exclusive to bedrock-runtime today, so for deployments requiring comprehensive audit trails and content filtering, bedrock-runtime is recommended.

Conduct a thorough security assessment before deployment. Evaluate Claude Code’s capabilities against your organization’s security policies. Amazon Bedrock secures the inference layer, but Claude Code runs on local developer machines and requires separate evaluation and risk management. Apply controls such as managed permissions, invocation logging, and per-user token limits, as you would for other third-party software running in your environment.

Conclusion

The availability of Claude Opus 5.5 and Claude Sonnet 5.5 on Amazon Bedrock in AWS GovCloud (US) provides organizations with a compliance-aligned path to AI-assisted development for regulated workloads. Claude Sonnet 5, with FedRAMP Class D (formerly High) certification and DoD IL4/IL5 authorization, offers the strongest compliance coverage for sensitive environments. Claude Sonnet 5.5, with FedRAMP Class D certification, is a step up from Claude Sonnet 5 on coding and knowledge work at a lower cost per task. Claude Opus 5.5, with FedRAMP Class D certification, brings deeper reasoning and longer autonomous task capabilities for workloads where that certification level is sufficient.

Combined with Claude Code, teams can adopt agentic coding workflows directly in their terminal, IDE, or CI/CD pipelines while data remains within AWS GovCloud (US) infrastructure. Whether you choose the bedrock-runtime endpoint for full Guardrails and logging support, or the bedrock-mantle endpoint for native Anthropic Messages API access, you can tailor the deployment to your organization’s compliance and operational requirements.

For more information

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About the authors

Bradley Wyman

Bradley is a Solutions Architect on the AWS Aerospace & Satellite team, where he helps Aerospace & Satellite customers leverage cutting-edge technologies to solve complex business challenges. With a deep passion for Generative AI, Agentic Development, and workload modernization, Bradley brings specialized expertise in helping organizations transform their operations through innovative cloud solutions. He is dedicated to making advanced AI technologies accessible and impactful for aerospace and satellite customers, enabling them to push the boundaries of what’s possible in their industry.

Doug Hairfield

Doug is a senior solutions architect who helps organizations harness the power of AI to solve real-world problems. He brings a depth of experience helping public sector customers design their workloads in high compliance environments. When he’s not architecting cloud solutions, you’ll find him being a girl dad and enjoying time with his family.

Keith Martin

Keith began his career as a software engineer at NASA Mission Control, where system reliability in human spaceflight operations is non-negotiable. He has since applied that discipline to architecting trading systems in the energy sector, guiding AWS Aerospace & Satellite customers through AWS GovCloud (US) and high-compliance deployments, and now leading automation and AI solutions at AWS Infrastructure Systems in Supply Chain Operations Excellence. His perspective on AI is straightforward: it is one tool among many, delivering value only when supported by solid data foundations and well-defined objectives.