AWS named as a Leader in the first Gartner Magic Quadrant for AI Code Assistants – LEARNALLFIX

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

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

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

On August 19, 2024, Gartner published its first Magic Quadrant for AI Code Assistants, which includes Amazon Web Services (AWS). Amazon Q Developer qualified for inclusion, having launched in general availability on April 30, 2024. AWS was ranked as a Leader for its ability to execute and completeness of vision.

We believe this Leader placement reflects our rapid pace of innovation, which makes the whole software development lifecycle easier and increases developer productivity with enterprise-grade access controls and security.

The Gartner Magic Quadrant evaluates 12 AI code assistants based on their Ability to Execute, which measures a vendor’s capacity to deliver its products or services effectively, and Completeness of Vision, which assesses a vendor’s understanding of the market and its strategy for future growth, according to Gartner’s report, How Markets and Vendors Are Evaluated in Gartner Magic Quadrants.

Here is the graphical representation of the 2024 Gartner Magic Quadrant for AI Code Assistants.

20240822_Gartner_MQ_AI_Code_Assistants_Graph AWS named as a Leader in the first Gartner Magic Quadrant for AI Code Assistants

Here is the quote from Gartner’s report:

Amazon Web Services (AWS) is a Leader in this Magic Quadrant. Its product, Amazon Q Developer (formerly CodeWhisperer), is focused on assisting and automating developer tasks using AI. For example, Amazon Q Developer helps with code suggestions and transformation, testing and security, as well as feature development. Its operations are geographically diverse, and its clients are of all sizes. AWS is focused on delivering AI-driven solutions that enhance the software development life cycle (SDLC), automating complex tasks, optimizing performance, ensuring security, and driving innovation.

My team focuses on creating content on Amazon Q Developer that directly supports software developers’ jobs to be done, enabled, and enhanced by generative AI in the Amazon Q Developer Center and Community. Aws.

I’ve had the chance to talk with our customers and ask why they chose Amazon Q Developer. They said it accelerates and completes tasks across the SDLC much more than general AI code assistants—from coding, testing, and upgrading to troubleshooting, performing security scanning and fixes, optimizing AWS resources, and creating data engineering pipelines.

Here are the highlights that customers talked about more often:

Available everywhere you need it – You can use Amazon Q Developer in any of the following integrated development environments (IDE), including Visual Studio Code, JetBrains IDEs, AWS Toolkit with Amazon Q, JupyterLab, Amazon EMR Studio, Amazon SageMaker Studio, or AWS Glue Studio. You can also use Amazon Q Developer in the AWS Management Console, AWS Command Line Interface (AWS CLI), AWS documentation, AWS Support, AWS Console Mobile Application, Amazon CodeCatalyst, or through Slack and Microsoft Teams with AWS Chatbot. Safe Software says, “Amazon Q knows how to use the many AWS tools. Because we can now accomplish more, we can extend our automation into other AWS services and use Amazon Q to help us get there.” To learn more, visit Amazon Q Developer features and Amazon Q Developer customers.

Customizing code recommendations – You can get code recommendations based on your internal code base. Amazon Q Developer accelerates onboarding to a new code base to generate even more relevant inline code recommendations and chat responses (in preview) by making it aware of your internal libraries, APIs, best practices, and architectural patterns. Your organization’s administrators can securely connect Amazon Q Developer to your internal code bases to create multiple customizations. According to the National Australia Bank (NAB), NAB has added specific suggestions using the Amazon Q customization capability tailored to the NAB coding standards. They’re seeing increased acceptance rates of 60 percent with customization. To learn more, visit Customizing Suggestions in the AWS documentation.

Upgrading your Java applications – Amazon Q Developer Agent for code transformation automates the process of upgrading and transforming your legacy Java applications. According to an internal Amazon study, Amazon has migrated tens of thousands of production applications from Java 8 or 11 to Java 17 with assistance from Amazon Q Developer. This represents a savings of over 4,500 years of development work for over a thousand developers (compared to manual upgrades) and performance improvements worth $260 million in annual cost savings. Transformations from Windows to cross-platform .NET are also coming soon! To learn more, visit Upgrading language versions with the Amazon Q Developer Agent for code transformation in the AWS documentation.

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