Amazon Q Developer features

Amazon Q Developer Pro doesn't use customer content for service improvement.

Amazon Q is built on Amazon Bedrock, a fully managed service for building generative AI applications that offers a choice of high-performing foundation models (FMs) from Amazon and leading AI companies. Amazon Q uses multiple FMs to complete its tasks and uses logic to route tasks to the FM that is the best fit for the job. AWS implements automated abuse detection. Because Amazon Q is built on Amazon Bedrock, users inherit the controls implemented in Amazon Bedrock to enforce safety, security, and the responsible use of AI.

Getting used to a new code base can take months of digging through code, finding documentation, and becoming familiar with coding standards. Amazon Q Developer speeds up onboarding and minimizes trial and error by answering questions about your code base and suggesting relevant libraries, APIs, and more.

Amazon Q is available in your favorite IDE to help you supercharge your development. You can ask Amazon Q to explain program logic in an unfamiliar code base, quickly identify and fix bugs, or generate functional tests.

With the Amazon Q Developer Agent for software development ( /dev ), you can go from a natural language prompt to application feature in a fraction of the time. Access interactive step-by-step instructions, code, tests, and best practices, with Amazon CodeCatalyst or right from your favorite integrated development environment (IDE). Amazon Q understands your workspace structure and breaks down your prompt into logical implementation steps, which can include generating code, tests, API integrations, and more. You can collaborate with Amazon Q to review and iterate on the implementation, and, when ready, ask Amazon Q to help implement each step.

Amazon Q Developer generates real-time code suggestions ranging from snippets to full functions, based on your comments and existing code in the IDE and CLI, in over 25 languages, including Java, Python, or JavaScript. Amazon Q Developer has the highest reported code acceptance rates in the industry for assistants that perform multiline code suggestions, with BT Group recently reporting they accepted 37% of Amazon Q Developer's code suggestions and National Australia Bank reporting a 50% acceptance rate.

Amazon Q Developer agents can autonomously perform a range of tasks—everything from implementing features, documenting, and refactoring code to performing software upgrades. You can describe a new feature to Amazon Q in natural language (for example, develop an SMS notification system for delivery confirmation messages), and it will analyze your existing code base, map out a step-by-step implementation plan spanning multiple files, and upon your approval, run all the required code changes and tests in minutes.

Accelerate development by customizing Amazon Q Developer to generate even more relevant inline code recommendations and chat responses by making it aware of your internal libraries, APIs, best practices, and architectural patterns. Use the Amazon Q Developer chat in the IDE to ask questions about how your internal code base is structured, where and how certain functions or libraries are used, or how to use specific functions, methods, or APIs. Save time onboarding to a new code base, building new features, refactoring code, or improving application performance.

Speed up time from prototyping to production with AWS Console-to-Code, which provides a path for moving from your console prototypes to reusable code that can be deployed in production workloads. Use Amazon Q to capture your console actions and workflows, and in a few quick steps, generate code and create production workloads.

You can select a section of code for which you need assistance and initiate chat within the IDE to request actions such as "optimize this code," "add comments," or "write tests." Get quick suggestions and code without switching context so you can stay in the flow while streamlining your coding process.

With workspace context awareness, Amazon Q Developer can provide richer, project-wide assistance and code tailored to your development needs. When responding to chat requests, instructions, and questions, Amazon Q Developer can use its in-depth knowledge of your entire workspace, not just the current open files, to give more nuanced suggestions that speed up iteration and minimize rewrites.

Onboarding to a new code base that’s barely documented? Amazon Q Developer can now generate in-depth documentation within your source code, including data flow diagrams, so you can understand any code base faster. And as you're building new features, use /doc to keep your readme files up to date.

Beyond generating code, Amazon Q Developer scans code for hard-to-detect vulnerabilities, such as exposed credentials and log injection. With a single click, Amazon Q Developer automatically suggests remediations tailored to the application code, allowing you to quickly accept fixes with confidence.

Building on top of a code base with low test coverage? Amazon Q Developer can iteratively generate unit tests within your project so you can build on top of existing code bases with confidence.

Amazon Q Developer automates code reviews, allowing you to detect and resolve code quality issues such as logical errors, anti-patterns, code duplication, and security vulnerabilities in your applications. With automated code reviews, you can get immediate feedback, improve the quality of your code base, and increase the speed of iteration.

Ready to deploy your application, but you aren't an infrastructure expert? Amazon Q Developer can help generate deployment-ready infrastructure as code (IaC) for AWS CloudFormation, AWS Cloud Development Kit (AWS CDK), or Terraform, so you can get your application in the hands of users in a fraction of the time.

Amazon Q is available everywhere you need it, such as the in the AWS Management Console, integrated development environment (IDE), AWS documentation, through Microsoft Teams and Slack, CodeCatalyst, Amazon SageMaker, or through the AWS Console Mobile Application.

Amazon Q has been trained on over 17 years of AWS experience building in the cloud to provide referenceable and contextual guidance. Application architects can use Amazon Q to help accelerate their research and design by keeping AWS well-architected patterns and best practices at their fingertips. Developers can dive into an unfamiliar code base by having Amazon Q explain the program logic in natural language, quickly identify and fix bugs, and even implement complete features along with test cases. Developers can ship improvements and new features faster than ever before.

Amazon Q Developer has knowledge of your AWS account resources and bill and can use this information to help you better understand and manage your infrastructure. For example, ask what instances are currently running in US East (N. Virginia) and Amazon Q will list them for you. As always, security comes first. Users of Amazon Q Developer have the same access to account and bill information as their existing AWS role permissions. If they can't access it without Amazon Q, they can't access it with Amazon Q either.

Amazon Q can help you make quick and cost-effective decisions for your optimal compute instance type before building your workloads. Amazon Q generates personalized Amazon Elastic Compute Cloud (Amazon EC2) instance type suggestions, using context from your actions in the console. Its natural language interface provides a straightforward way for you to describe your workload and needs and receive best-matched instances.

Chat with Amazon Q in the console or through chat applications and easily query and explore your AWS infrastructure without writing scripts or navigating through multiple console pages.

Use Amazon Q to retrieve your cost data from AWS Cost Explorer so you can more easily understand your cloud expenditure.

Amazon Q helps diagnose common errors in the console in seconds with expert guidance and actionable step-by-step solutions. When encountering an error in the console, you can ask Amazon Q to diagnose it in a single step. Amazon Q will provide context on the likely cause of the error and explicit steps to remediate it, all informed by AWS best practices.

Amazon Q works alongside you to help investigate and remediate operational issues quickly from within the console or through chat applications.

Amazon Q Developer is available in Microsoft Teams and Slack to help your team monitor, operate, and troubleshoot AWS resources. Operationalize DevOps runbooks and incident response tasks with customizable notifications from Amazon Q, follow-up actions like "Show Logs", and command aliases. Investigate incidents with incident hypotheses, diagnostic troubleshooting capabilities, and custom workflows, all without context switching between tools.

Chat with Amazon Q Developer in Amazon OpenSearch Service to reduce time to operational insights—quickly set up monitoring, investigate issues, analyze patterns, and create visualizations using in-context assistance and natural language interactions. This reduces mean time to resolution, enables more self-service troubleshooting, and helps teams extract greater value from their operational data.

When you ask Amazon Q to help you analyze network connectivity problems, it works with VPC Reachability Analyzer to check your connections and inspect your network configuration to identify potential issues. Then Amazon Q provides guidance on how to resolve or further diagnose the issue. Using the conversational capabilities of Amazon Q and Reachability Analyzer together creates an intuitive way for you to quickly understand your network connectivity issues.

Amazon Q can help you upgrade your Java applications. Amazon Q can identify and update mandatory package dependencies and frameworks, update deprecated code, incorporate security best practices, and generate tests to validate the upgraded application will run.

Amazon Q Developer helps right in your IDE to automate the conversion of embedded SQL from Oracle to PostgreSQL. Amazon Q detects Oracle SQL statements in your Java application and converts them to PostgreSQL. Review and accept proposed changes, see a summary of the transformation, and get recommended next steps as you verify and test transformed code.

Using Amazon Q Developer transformation capabilities in a web experience, modernization teams can use natural language interaction with autonomous, generative AI agents infused with .NET domain expertise to analyze versions, project types, dependencies, and propose modernization plans. After plan approvals, agents refactor code, transform tests, and validate Linux readiness. The capabilities are also available in the Visual Studio IDE.

Using Amazon Q Developer transformation capabilities in a web experience, modernization teams can use natural language interaction with autonomous, generative AI agents infused with mainframe and cloud expertise to analyze, document, decompose, and refactor mainframe applications with team reviews and approvals.

Using Amazon Q Developer transformation capabilities in a web experience, modernization teams can use natural language interaction with autonomous, generative AI agents infused with VMware transformation expertise for on-premises server inventory analysis, dependency identification, network translation, and migrating of resources to Amazon EC2 with team reviews and approvals.

In just a few steps, keep applications updated to the latest supported versions, gain performance benefits, and remove vulnerabilities from using unsupported versions.

Build data integration pipelines using natural language with Amazon Q data integration in AWS Glue, with limited Apache Spark or SQL expertise. Build data integration jobs faster, reduce complexity of troubleshooting issues, and get expert integration help with Amazon Q.

Ask Amazon Q generative SQL your queries using natural language and get SQL code recommendations in the Amazon Redshift Query Editor. Amazon Q analyzes user intent, query patterns, and schema metadata for actionable data insights.

Amazon Q Developer assists you throughout machine learning (ML) development in Amazon SageMaker Studio, across data preparation, model training, and model deployment. Get help to debug and fix errors as you run code within the IDE.

Amazon Q Developer is available in Amazon SageMaker Canvas. State your objective in natural language, and Amazon Q will translate it for ML and walk you through a solution using data science best practices.

Amazon Q Developer is available in Amazon SageMaker Unified Studio. Ask about available governed data for projects, quickly ramp up on collaborations, and get help authoring code, generating SQL, integrating data, troubleshooting, and more.