Amazon SageMaker使企业能够构建和部署AI代理，并更好地控制性能、成本和基础设施。与开源Strands Agents SDK的集成允许部署SageMaker JumpStart中的基础模型，通过SageMaker MLflow促进代理创建，增强可观察性。这种方法为组织提供了对其AI代理部署的架构控制，支持A/B测试和持续改进等功能。 AI
影响 使企业能够构建和部署AI代理，并更好地控制性能、成本和基础设施。
排序理由 博客文章详细介绍了将SDK与云提供商的ML平台集成以构建AI代理。
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In this post, we demonstrate how to build AI agents using Strands Agents SDK with models deployed on SageMaker AI endpoints. You will learn how to deploy foundation models from SageMaker JumpStart, integrate them with Strands Agents, and establish production-grade observability u…
🤖 Build Strands Agents with SageMaker AI models and MLflow In this post, we demonstrate how to build AI agents using Strands Agents SDK with models deployed on SageMaker AI endpoints. You will learn how to deploy foundation models from SageMaker JumpStart,... 📰 Source: Artificial…
📰 Build AI Agents with SageMaker & MLflow in 2026: End-to-End Tracing, A/B Testing & Real-Time Obse... Build AI agents using the Strands Agents SDK with SageMaker AI models and MLflow for end-to-end observability, A/B testing, and continuous improvement in production environments…
📰 SageMaker ve MLflow ile Strands Agents: 2026'da AI Ajanları Geliştirin (MLflow Tracing ile) Amazon SageMaker ve MLflow’un Strands Agents SDK ile entegrasyonu, yapay zeka ajanları geliştirme alanında bir devrim yaratıyor. Bu entegrasyon, model takibi, yeniden kullanılabilirlik v…