AWS DevOps & Developer Productivity Blog

Category: Amazon Q

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 […]

Streamline DevOps troubleshooting: Integrate CloudWatch investigations with Slack

Infrastructure alerts pose a challenge for DevOps teams, particularly when they occur outside of regular business hours. The complexity isn’t merely in receiving notifications, it lies in rapidly assessing their severity and determining the root cause. This challenge is compounded when upstream service disruptions cascade into multiple downstream alerts, creating a confusion of notifications that […]

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GitOps continuous delivery with ArgoCD and EKS using natural language

Introduction ArgoCD is a leading GitOps tool that empowers teams to manage Kubernetes deployments declaratively, using Git as the single source of truth. Its robust feature set, including automated sync, rollback support, drift detection, advanced deployment strategies, RBAC integration, and multi-cluster support, makes it a go-to solution for Kubernetes application delivery. However, as organizations scale, […]

Managing Amazon Q Developer Profiles and Customizations in Large Organizations

As organizations scale their development efforts, AI coding assistants that understand organization-specific patterns and standards lead to more efficient development processes and higher quality software delivery. Amazon Q Developer Pro helps address this challenge by allowing organizations to customize the AI assistant with their proprietary code and development practices. Through Amazon Q Developer profiles, teams […]