Empowering Azure CLI developers with AI


When we redesigned the Azure CLI in 2016, our goal was to create a simple, easy to use, tool for managing Azure.  Since then, Azure has grown tremendously from supporting multiple clouds in various locations across the globe, on/off premises services, and scenario-specific technologies, such as Azure IoT and AI/ML tools. 


With over 2500 commands, tens of thousands of parameters, and new Azure features being developed daily, maintaining simplicity in Azure CLI is a challenge. In this post, we want to introduce you to three of our AI-powered features we’ve developed to ensure the Azure CLI remains easy to use, consistent, and “evergreen”.  These features include: generating up-to-date examples, enabling natural language search in command line, and assisting with failure recovery. We will share with you our learnings and journey below.


Learning new software and APIs requires up to date documentation with multiple examples covering the main common scenarios. However, the fast pace of modern software causes documentation, especially examples, to quickly become stale.


We’ve addressed the problem of incomplete and stale documentation by developing an AI-powered platform that automatically generates and updates examples for our command line tools (Azure CLI and Azure PowerShell) ensuring


  • Up-to-date examples: generate new examples with each new Azure CLI (and Azure PowerShell) release, ensuring the documentation is always up-to-date.
  • Representative of actual usage: Unlike bare-bones examples usually found in documentation that only cover basic scenarios, our examples are based on actual usage patterns and therefore represent how current users use the software in practice.
  • Informed by our educational content: Our platform ingests over 14,000 pages of blogs, tutorials, and samples to ensure consistency (naming, sample values, etc.) across our learning resources. 


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