Example prompts for optimizing your application with GitHub Copilot for Azure Preview
If you're unfamiliar with Azure or you just want the tooling and AI to do most of the work, you can ask GitHub Copilot for Azure Preview to help you optimize the performance of your Azure resources. Use best practices to achieve the best results.
Example prompts to optimize your app
If you want to use GitHub Copilot for Azure Preview for help with optimizing your application, you can start with an open-ended question or request. Then, add details like specific services and technologies for better results. Try the following example prompts.
| Service | Optimize prompt examples |
|---|---|
| Azure App Service |
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| Azure SQL |
|
Prompts to evaluate AI models
The Online Experimentation GitHub Copilot extension plugin is a powerful tool designed to streamline the process of online A/B model evaluation for AI application developers. This plugin is part of a broader initiative to enhance the developer experience by integrating experimentation capabilities directly into the development workflow.
This includes two components:
- An experimentation copilot plugin for the @azure extension. This chatbot assists with experimentation, generates feature flag code and metric, helps evaluate and summarize experiment results, and more.
- A GitHub action that can be invoked as part of the AI development workflow in GitHub to start experiments and refresh and link to experiment results.
The goal of this project is to provide a seamless and efficient way for developers to conduct experiments and analyze results without leaving their development environment. It supports the creation and management of experiments and metrics, leveraging Azure services such as Azure App Config for configuration delivery and Azure AI for model monitoring metrics.
The preview of this plugin includes a code-first user experience in partnership with Azure App Config, enabling streamlined evaluation and experimentation in GitHub. This includes out-of-the-box model monitoring metrics and custom metrics. The public preview will evolve this into a full streamline integration and easy-to-use user experience in both App Config and AI Studio.
Azure AI evaluation is already publicly available, but if you are interested in trying out our online experimentation feature please sign up for our preview to learn more.
Optimize code level performance
If you use Applications Insights Profiler for .NET, you can perform code-level performance optimizations with GitHub Coplit. This feature is under development, so at this time a separate @Code_Optimization (instead of @azure) extension needs to be used for optimizing code-level performance. For details on installing and using Code Optimizations, see Code Optimizations extensions for Visual Studio and Visual Studio Code (preview) - Azure Monitor.
Related content
- Understand what GitHub Copilot for Azure Preview is and how it works.
- Get started with GitHub Copilot for Azure by installing the software and writing your first prompt.
- Follow the quickstart to understand how to include GitHub Copilot for Azure Preview in your software development workflow. The quickstart describes how to deploy services to Azure, monitor their status, and troubleshoot problems.
- See example prompts for learning more about Azure and understanding your Azure account, subscription, and resources.
- See example prompts for designing and developing applications for Azure.
- See example prompts for deploying your application to Azure.
- See example prompts for troubleshooting your Azure resources.