扩展代理式AI：避免供应商锁定的企业模式

AI 摘要

AWS 机器学习博客发布文章，探讨企业在多框架、多模型、多提供商的“多一切”环境中扩展代理式 AI 系统的架构模式，强调通过分离控制平面与执行平面、统一可观测性、集中治理等原则避免供应商锁定，并指出 Amazon SageMaker 在模型生命周期管理中发挥基础作用。文章基于企业实践，提出了管理复杂性的实用准则，旨在帮助 ML 团队在保持灵活性的同时实现规模化。

正文节选

Scaling agentic AI: Enterprise patterns without vendor lock-in Scaling agentic AI across an enterprise requires architectural patterns that preserve flexibility while avoiding vendor lock-in. This post is Part 2 of our series on multi-agent systems at scale. In this post, we examine how machine learning (ML) teams operate agentic AI systems across a “multi-everything” environment of frameworks, models, and providers. We also cover the principles that let those systems scale together. In Advanced

发布时间：2026-08-21 00:24

抓取时间：2026-08-21 01:09

来源机构：AWS