Best practices for customizing Amazon Q Developer (DOP217)

Generative AI Stack and Amazon Q Developer

Introduction

  • The presentation covers the Generative AI stack of AWS services, focusing on Amazon Q Developer.
  • Amazon Q Developer is designed to help accelerate the entire software development lifecycle.

The Generative AI Stack

  • At the bottom, there are EC2 instances with GPU and other accelerator options to build and train generative AI models.
  • Bedrock was launched to make it easy to host models and provide configuration and customization capabilities.
  • Amazon Q, launched at re:Invent last year, comes in two flavors:
    • Q Business: Helps with building chatbots and conversational applications.
    • Q Developer: Focuses on improving the developer experience across the software development lifecycle.

Amazon Q Developer

  • Amazon Q Developer is integrated into various AWS experiences, such as the console, documentation, mobile apps, collaboration tools, and IDEs.
  • It is trained on publicly available code examples, but the challenge is that it doesn't know about the user's internal SDKs, APIs, and custom solutions.
  • Customization allows users to train Q Developer on their private code base, so it can learn about the unique aspects of their organization and make relevant suggestions.

Customization Preparation

  • To prepare for customization, users need to have at least 10 files and 2 MB of data in Java, JavaScript, Python, or TypeScript.
  • Best practices include using verbose method names, adding detailed comments, and providing examples of the intended usage of the code.
  • The more code examples provided (around 100 MB or more), the better the results, as long as the code is unique and not duplicated.

Customization Creation and Monitoring

  • Users can connect Q Developer to their existing code repositories, such as GitHub, Bitbucket, or GitLab, or directly ingest code from Amazon S3.
  • The customization process takes around an hour and results in a score, which may initially be low but can be improved with more examples.
  • It's important to grant access to the customization selectively, based on the specific needs of different teams or users.
  • Monitoring the performance of the customization through the Q Developer console and CloudWatch can help understand its effectiveness and identify areas for improvement.

Real-World Examples

  • Internal teams at Amazon, such as Prime Video, have seen a 30% increase in acceptance rates with the customized Q Developer.
  • External customers, like National Australia Bank, have reported a 60% increase in productivity over using Q Developer without customization.

Overall, the presentation highlights the benefits of using Amazon Q Developer, especially with customization, to accelerate the software development lifecycle and improve developer productivity.

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