AWS DevOps & Developer Productivity Blog

Category: Amazon Q

Multi-Cloud Code Deployments using Amazon Q Developer with Echo3D

Overview Founded in 2018, echo3D built a revolutionary 3D digital asset management (DAM) platform to address the surging demand for immersive content across industries. The company’s platform enables enterprises to seamlessly store, secure, optimize, and share 3D content, serving over 200,000 professionals across energy, healthcare, gaming, retail, and beyond. echo3D’s platform has become the go-to […]

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Accelerating AWS Infrastructure Deployment: A Practical Guide to Console-to-Code

In today’s cloud-first environment, Infrastructure as Code (IaC) has become crucial for managing cloud resources effectively. However, organizations often face significant challenges in adopting IaC practices, including steep learning curves, complex syntax requirements, and difficulty translating manual operations into code.  Amazon Q Developer‘s Console-to-Code feature addresses these challenges by providing an intuitive bridge between manual AWS […]

AWS named as a Leader in the 2025 Gartner Magic Quadrant for AI Code Assistants

We are excited to share that AWS has been named a Leader in the 2025 Gartner Magic Quadrant for AI Code Assistants for the second year in row. This recognition highlights for us Amazon Q Developer’s commitment to innovation and delivering exceptional customer experiences. We believe this Leader placement showcases our rapid pace of innovation, […]

Introducing an Interactive Code Review Experience with Amazon Q Developer in GitHub

Code reviews are one of the most valuable rituals in software development. They help ensure quality, maintain consistency, and foster growth as engineers. But they’re also one of the most time consuming steps in the software development lifecycle. A common pattern I’ve seen is a developer opening a pull request (PR), receiving automated or peer […]

Measuring Developer Productivity with Amazon Q Developer and Jellyfish

Modern software development teams face increasing pressure to deliver high-quality code faster, while managing growing system complexity. Developers often spend significant time on necessary, but undifferentiated work, or “toil”. Toil is often manual, repetitive, and of limited enduring value, making it a strong candidate for automation or delegation to generative AI tools. The re:Invent 2024 […]

Mastering Amazon Q Developer with Rules

When I first started working with Amazon Q Developer, I was impressed by its capabilities, but I quickly found myself in a familiar pattern. Development teams using AI assistants face a common challenge: repeatedly explaining coding standards, workflow preferences, and established patterns in every conversation. This repetitive setup reduces productivity and creates inconsistent AI guidance […]

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Introducing AWS Cloud Control API MCP Server: Natural Language Infrastructure Management on AWS

Today, we’re officially announcing the AWS Cloud Control API (CCAPI) MCP Server. This MCP server transforms AWS infrastructure management by allowing developers to create, read, update, delete, and list resources using natural language. As part of the awslabs/mcp project, this new and innovative tool serves as a bridge between natural language commands and AWS infrastructure […]

AI-Driven Development Life Cycle: Reimagining Software Engineering

Business and technology leaders are constantly striving to improve productivity, increase velocity, foster experimentation, reduce time-to-market (TTM), and enhance the developer experience. These North Star goals drive innovation in software development practices. This innovation is increasingly being powered by artificial intelligence. Particularly, generative AI powered tools such as Amazon Q Developer and Kiro have already […]

Troubleshooting Elastic Beanstalk Environments with Amazon Q Developer CLI

Troubleshooting Elastic Beanstalk Environments with Amazon Q Developer CLI

Introduction Developers working with AWS find AWS Elastic Beanstalk to be an invaluable service that makes it straightforward to deploy and run web applications without worrying about the underlying infrastructure. You simply upload your application code, and Elastic Beanstalk automatically handles the details of capacity provisioning, load balancing, scaling, and monitoring, which allows you to […]