Category: Amazon Q Developer

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 […]

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 […]

As a developer who has embraced the power of the Model Context Protocol (MCP)to enhance my workflows, I’m thrilled to see the addition of custom agents in the Amazon Q Developer CLI. This new feature takes the capabilities I’ve come to rely on to a whole new level, allowing me to seamlessly manage different development […]

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 […]

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 […]

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 […]

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, […]

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 […]

Amazon Q Developer is the most capable generative AI–powered assistant for software development, helping developers perform complex workflows. Amazon Q Developer command-line interface (CLI) combines conversational AI with direct access to AWS services, helping you understand, build, and operate applications more effectively. The Amazon Q Developer CLI executes commands, analyzes outputs, and provides contextual recommendations […]

Earlier today, Amazon Q Developer announced Model Context Protocol (MCP) support in their Integrated Development Environment (IDE) plugins for Visual Studio Code and JetBrains. This allows developers to connect external tools or MCP servers to Q Developer, enabling more context-aware responses and complex workflows. MCP support has already been available in Amazon Q Developer for […]