产品简介
Amazon Q Developer 是亚马逊云科技（AWS）推出的生成式AI编程助手，专为加速软件开发全生命周期而设计。它深度集成200余项AWS服务，能够帮助开发者在代码编辑器、命令行乃至AWS管理控制台中高效完成编码、调试、架构优化等任务。基于AWS的深厚技术积累，Amazon Q Developer 提供了业界领先的多行代码补全接受率，并支持从代码生成到安全扫描、架构建议的全面功能。
随着 AWS 在代理式 AI 方向持续投入，2026/8/31 AWS Agent Registry 正式可用，为组织内跨团队的代理、工具、技能与自定义资源提供统一、可搜索、可治理的目录，进一步强化了 Amazon Q Developer 所依托的代理生态。
核心功能
- 智能代码补全与生成：基于生成式AI提供多行代码建议，拥有业界最高的代码接受率（据BT Group报告），显著提升编码效率。
- AWS服务深度集成：原生支持200余项AWS服务，可在IDE或命令行中直接调用AWS API、生成云资源代码，并优化云成本与资源。
- 全生命周期自动化代理：具备代理能力，可自主执行功能实现、文档编写、测试、代码审查、重构及软件升级等任务，覆盖开发全流程。2026/8/31 AWS Agent Registry 正式可用，为组织内代理、工具、技能与自定义资源提供统一、可搜索、可治理的目录，便于代理能力的规模化管理与复用。
- 安全扫描与修复建议：自动扫描代码中的安全漏洞和潜在问题，并提供修复建议，帮助开发者构建更安全的应用程序。
- 架构与成本优化指导：集成于AWS管理控制台，并支持Microsoft Teams和Slack，提供云架构建议、成本优化方案及资源管理指导。
- 多IDE与命令行支持：提供VS Code、JetBrains、Visual Studio、Eclipse等主流IDE插件，以及命令行工具，灵活适配不同开发环境。
适合谁用
以下类型的用户会特别受益于 Amazon Q Developer：
- 在AWS云环境中快速构建和部署应用，利用代码补全和AWS服务集成提升开发效率
- 对现有代码进行安全扫描、重构和升级，确保代码质量与安全性
- 通过架构建议和成本优化功能，降低云资源开销并优化系统设计
- 团队协作时，在Slack或Teams中直接获取AWS资源管理和架构指导
- 借助 AWS Agent Registry 统一管理组织内的代理、工具与技能，支撑代理式开发流程的规模化落地
优点亮点
- 深度集成AWS生态，对云开发者极为友好
- 多行代码补全接受率业界领先，提升编码速度
- 覆盖开发全生命周期，从编码到部署优化一站式解决
- 支持多种IDE和命令行，灵活适配不同工作流
- 提供安全扫描和架构建议，增强应用可靠性与成本效益
- 依托 AWS Agent Registry，代理、工具与技能可在组织内统一治理与复用
价格与方案
采用Freemium模式，提供免费套餐（Free Tier）供开发者快速上手，高级功能需付费订阅。具体定价请参考AWS官网。
总结与建议
Amazon Q Developer 最适合在AWS生态中进行云开发的团队和个人。其核心优势在于对AWS服务的深度集成、业界领先的多行代码补全接受率，以及覆盖开发全生命周期的自动化能力，能够显著提升开发效率、代码安全性和云资源管理效益。
版本演进
- Run multi-node inference workloads using Ray LLM Deep Learni （2026-10-12）：Learn how to deploy one large language model across two GPU nodes on Amazon EKS using the multi-node Ray LLM Deep Learning Containers, with separate prefill and decode nodes behind one OpenAI-compatib
- Share GPU clusters across teams with isolation and fairness （2026-10-08）：A reference architecture for securely sharing one Amazon SageMaker HyperPod EKS cluster across multiple teams, using AWS IAM Identity Center for authentication, per-team SageMaker Domains and Kubernet
- Beyond hours saved: Building the business case for agentic a （2026-10-07）：The RPA-era ROI model misses most of the value agentic automation creates. This post gives AI center of excellence leaders a framework to size the full value of agents across time savings, exception h
- Responsible AI governance: How AWS positions customers to al （2026-10-06）：AWS invests in tools that help customers align with international standards for responsible AI governance. In this post, we explore the AI system impact assessment: what it is, how it improves enterpr
- Downgrading user roles in Amazon Quick （2026-10-05）：Amazon Quick doesn't offer a direct console path to downgrade a user from Admin or Author to Reader. This post walks through two reliable methods: a manual delete-and-recreate approach and an AWS CLI
- Enhancing industrial safety AI with synthetic data on Amazon （2026-09-17）：Learn how to build a synthetic data augmentation pipeline on Amazon SageMaker AI and Amazon Rekognition that generates photo-realistic, auto-labeled training images for industrial safety AI. This appr
- Improving HCLS AI reasoning with open-source agent skills （2026-09-16）：AI agents on foundation models often misapply healthcare and life sciences decision frameworks, citing the right guideline but applying it incorrectly. This post shares 38 open-source agent skills acr
- Build an AI-powered product tagging system with Amazon SageM （2026-09-15）：Manually tagging thousands of catalog products is slow and inconsistent. This walkthrough shows how to customize Qwen3-8B with supervised fine-tuning (SFT) and reinforcement learning with verifiable r
- Integrating Outlook with Amazon Quick for AI-powered email a （2026-09-03）：Integrate Microsoft Outlook with Amazon Quick to automate email management, calendar scheduling, and workflow coordination. This post walks through the end-to-end setup and shows automation scenarios
- Modernizing and scaling support operations with generative A （2026-09-02）：Learn how to build a generative AI-based support operations platform on AWS that converts training videos into structured SOPs, applies Retrieval-Augmented Generation to guide ticket resolution, and u
- From theory to delivery: How Atos upskilled 400 engineers in （2026-09-01）：When Atos set out to upskill 400 engineers in agentic AI, hands-on learning was the missing ingredient. Over three days, engineers built multi-agent systems on AWS through an AI League event. This pos
- Manage agents, tools and skills at scale with AWS Agent Regi （2026-08-31）：AWS Agent Registry is now generally available: a single, searchable, governed catalog for the agents, tools, skills, and custom resources across your organization. This post explains what Registry is
- Batch write and discover records in Amazon SageMaker Feature （2026-08-28）：Amazon SageMaker Feature Store now supports two new APIs: BatchWriteRecord writes up to 25 records across multiple feature groups in a single call, and ListRecords enumerates record identifiers within
- Governed reports with Amazon Quick Desktop and Amazon FSx fo （2026-08-25）：Build a governed weekly reporting workflow with Amazon Quick Desktop and Amazon FSx for NetApp ONTAP. An Amazon S3 access point exposes an approved folder to a Quick knowledge base, and a custom skill
- Introducing new Ray capabilities on SageMaker HyperPod （2026-08-24）：Amazon SageMaker HyperPod now offers managed Ray support on Amazon EKS. Create and monitor Ray clusters, connect JupyterLab and Code Editor notebooks to live clusters, get out-of-the-box observability