What is Amazon Q used for?

Amazon Q is used both as an AI coding assistant for developers and as a business assistant that answers natural-language questions over internal company data and AWS resources.

How is Amazon Q different from GitHub Copilot?

Both are AI coding assistants, but Amazon Q is more tightly integrated with the AWS ecosystem, including infrastructure troubleshooting and cost/security recommendations, while [GitHub Copilot](/glossary/github-copilot) focuses primarily on code generation within the editor.

Does Amazon Q only work for developers?

No, Amazon Q also has a business-focused variant aimed at non-developer employees who need to query internal data and get AI-generated business insights.

What powers Amazon Q under the hood?

Amazon Q is built on top of foundation models made available through AWS's generative AI services, including [Amazon Bedrock](/glossary/amazon-bedrock).

AI Tools

Amazon Q

By Amazon Web Services

IntermediateTool12.6K learners

Amazon Q is AWS's generative AI assistant, offering tools for software development (code generation, debugging, and modernization) and for business use (querying internal data and generating business insights) via natural language.

#AmazonQ #AITools#Tool#Intermediate#GitHubCopilot #AmazonBedrock #AmazonSageMaker #ArtificialIntelligence#Glossary#SkillVeris

Definition

Amazon Q is AWS's generative AI assistant, offering tools for software development (code generation, debugging, and modernization) and for business use (querying internal data and generating business insights) via natural language.

Overview

Amazon Q is offered in variants aimed at different users: a developer-focused assistant integrated into IDEs and the AWS console that can generate and explain code, review pull requests, and help modernize legacy applications, and a business-focused assistant that lets employees ask natural-language questions over internal company data and AWS resources. Both are built on top of AWS's broader generative AI stack, drawing on foundation models made available through services like Amazon Bedrock. On the developer side, Amazon Q's code-focused capabilities sit alongside tools like GitHub Copilot in the growing category of AI coding assistants, but with tighter integration into AWS-specific workflows such as infrastructure troubleshooting and cloud cost or security recommendations. Because Q is embedded directly into AWS's console and developer tooling, it's positioned as an AI layer across the AWS experience rather than a single standalone product, which fits into the broader shift toward AI agents and agentic workflows explored in the AI Agents & Agentic Workflows course.

Key Features

Natural-language code generation, explanation, and debugging assistance
Integration with IDEs and the AWS Management Console
Business variant for querying internal company data and documents
AWS-specific troubleshooting, cost, and security recommendations
Application modernization assistance for legacy codebases
Built on foundation models available through Amazon Bedrock
Context-aware suggestions based on a project's existing code and AWS resources

Use Cases

Generating and explaining code within an IDE

Reviewing and improving pull requests with AI assistance

Answering natural-language questions over internal business data

Troubleshooting AWS infrastructure and configuration issues

Assisting with legacy application modernization projects

Summarizing AWS cost, security, or operational recommendations

Frequently Asked Questions

From the Blog

Cloud & Cybersecurity

AWS for Beginners: Cloud Computing Fundamentals

Amazon Web Services is the world's most widely used cloud platform. This guide covers the core services every developer needs — EC2 (virtual servers), S3 (storage), IAM (access control), VPC (networking), and RDS (databases) — with practical setup instructions and free tier guidance.