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GCP上之OpenClaw:具微VM隔离之安全多租户AI代理平台
Sivakumar Dh · 2026-05-24 · via DEV Community

引言

夫智能之器日进其能,则其运化之基,必固其安、其隔、其察、其御于内。众构共营,虽廉于用,然于制为甚艰。此弊者,在隔众之能既周,犹欲享器之速密耳。

古之容器,可运行工役,其效尚可,然皆栖于同核。若内用于系统,或可无碍。若处多租户之境,租户得以运行器具,执行脚本,甚或得觊文件之系,通于外界,则独恃容器,实为隐患。用微VM,既可强隔离工役,复能保其效率,方为得计。Firecracker者,乃基于VM之技,具隔离之誓,兼有容器之能,为之微VM之一实也。

此理易明:每户独享其资源(自有内核、文件系统、磁盘卷、网络边界)。凡租户之务,如配置、调度、监控、备份、恢复、认证及租户管理,皆行于共用之控面;而运行时则与控面自相隔离。

核心平台之理

其构分两面。

制御之境,掌形神,驭机枢,辨户属,调时序,察玄元,司存真,录迹彰,明政鉴.

数理之境,运真户之境。真户之域,独居微VM,授以灵机,配以神思,赐以玄盘,通以灵络。真户之灵台,别于他真。

此法尤适于智能平台,其中智能体可运行任意代码、工具、文件,调用API,浏览网络,或访问模型提供者。智能体愈强,隔离不力之风险愈大。其设计之旨,非“如何高效运行众多智能体”,实乃“如何运行众多智能体,而令一租户不为其他租户之患”。

微虚拟机何以重要

微VM之设,使各租户得有较之容器更为严密的隔离界限,盖因每租户皆得独享一客核与虚拟化之境。此乃要务,当租户得执行指令、安装软件、处理文书,或运用自主工具之时。

源模式以租户为单元,微VM隔离,独立根文件系统,租户专有数据卷,网络隔离,调度,主机弹性扩展,闲置回收,健康检测,网页管理,备份恢复,共享技能/配置分发。

此乃正道。此平台之弊,莫过于“一集群,一租户一命名空间,冀RBAC可解之。”此不足以为重任之代理。命名空间,乃管理之界,非固若金汤之安。

拟议之GCP系统架构

GCP之实现,当用无服务之控台,及基于Compute Engine之微VM之数据台。

于边陲,用户经HTTPS负载均衡之护,由云盾防护,以达平台。认证之事,则由身份平台掌之。API网关揭租户生命周期之API,如立租户、止租户、删租户、询状态、启备份、复工作空间、列主机容量是也。

云运行服务施控之理。Firestore存租户元数据、主机状态、配额信息、审计事件、备份状态及生命周期状态。云存储存根文件系统镜像、发布包、租户备份物、配置模板及共享技能包。

租户之务,运行于区域之管理实例群。每主皆为一计算引擎之虚拟机,启嵌虚拟化。及于启动,主下载核准之运行图像,自注于元数据库,报其容量,并启主代理。及于租户之立,调度者择一康健且容量充裕之主,命主代理创租户之微虚拟机。

每租户微VM各得自有之文件系统、持久数据卷、网络分接接口、CPU与内存之配额,及运行时之配置。租户之仪表盘,非设独立公端,乃经控代理路径而显之。

System Architecture

推荐之GCP参考架构

若欲达生产级之境,所荐架构若:

云盾以御WAF及DDoS之患
HTTPS负载均衡以应公门之需
API网关以导API之途而司其权
云行以驭控平面之务
Firestore以存元数据及生命周期之状
Pub/Sub以应异步之变

云存储,用于根文件系统、模板、备份及共享资源
密钥管理器,用于API密钥及运行时密钥
区域计算引擎管理实例组,用于微型虚拟机宿主
宿主虚拟机支持嵌套虚拟化
云监控与日志,用于可观测性

Terraform以复用之姿布设基建

此乃使无服务之管理诸务与固若金汤之租户运行基建截然分离

Deployment Architecture

主要之患

最大之患,乃自欺此仅为寻常之网络应用布设。非也。此乃平台工程也。

其次之患,在轻慢网络。租户微VM路由、私有桥接、NAT、代理仪表盘、出网控制及防火墙规则,皆需精心设计。网络疏忽,可破隔离之境.

再次之患,在生命周期管理薄弱。创租户易,而安妥清理、保存数据、回收闲置资源、恢复备份、处置启动失败,此乃平台之真谛。

第四患在影移。若根文件系统影、主代理及租户配置未版本化,终将有租户于诸主间行止殊异。

终章

于GCP之上构建安全多租户AI代理平台,固其事可成,然其设计非若寻常容器平台之简。良策者,当以无服务器之控台为纲,以微VM为基础之数据层。GCP所供构建之基石,足以成此模式,尤赖Compute Engine之嵌套虚拟化、Managed Instance Groups、API Gateway、Cloud Run、Cloud Storage、Firestore、Pub/Sub、Identity Platform、Secret Manager、Cloud Armor及Cloud Monitoring诸般利器。

直言之:若所求者乃可信之多方租用AI执行平台,则勿于隔离处吝啬。容器诚便,然便利非安全之模。至若能执行工具与代码之AI代理,微虚拟机级隔离乃正道也。