AWS发布Claude Code远程智能体指南
AWS Machine Learning Blog发布指南和示例，介绍如何在Amazon Bedrock AgentCore上将Claude Code作为远程编码智能体运行。每项任务都在用户AWS账户内的独立AgentCore Runtime会话中执行，并返回GitHub拉取请求供人工审查和合并。示例还展示了私有网络、短期凭证、最小权限和Amazon Bedrock数据控制措施。
该指南提供了一套把编码任务交给隔离远程智能体、并在代码合并前保留人工审批的实施模式，但其中的安全和能力主张均来自AWS。
You might already run Claude Code locally on your laptop, backed by Amazon Bedrock. This post shows how to go a step further: run it as a remote agent on Amazon Bedrock AgentCore, a platform to build, connect, and optimize agents at scale, with any framework or model. The sample uses AgentCore runtime, a capability of Amazon Bedrock AgentCore, so every task runs in its own isolated session inside your AWS account. You offload a coding task, close the laptop, and come back to the result.
We first discuss why teams choose Amazon Bedrock for Claude Code and highlight a few key security characteristics. Then, we discuss the remote agent architecture and walk through an accompanying sample, sample-remote-coding-agent, that implements it. The sample runs each task in its own AgentCore runtime session and returns a GitHub pull request for you to review and merge. Along the way, we show how the Amazon Bedrock data controls stay intact when a task runs remotely.
Why customers run Claude Code on Amazon Bedrock
Customers choose Amazon Bedrock as Claude Code’s model provider for many reasons. These include billing and credits through their existing AWS account with no per-seat licenses, audit logging in AWS CloudTrail, and geographic inference profiles for data residency. Amazon Bedrock also provides three valuable security characteristics:
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