/cdx → AI Builder, Azure → environment-provisioning
Environment Provisioning
Part of the scenario: Innovate with Azure AI Apps & Agents - The Developer's Journey
This demonstration showcases streamlined environment provisioning using Microsoft Dev Box through the Azure portal. It provides a technical walkthrough on setting up a preconfigured, ready-to-code development environment without manual installation of SDKs or dependencies, significantly reducing setup time. The use case highlights seamless transition from development to deployment on Microsoft Azure, serving as a blueprint for enabling fast, consistent, and scalable developer environments in enterprise workflows. Runs in a live demo tenant with realistic data — you try the real thing, not a slide deck.
More demos in this story
6 relatedAccelerate development with GitHub Copilot coding agent
This demonstration showcases how to accelerate software development using GitHub Copilot coding agent capabilities. It provides a technical walkthrough on leveraging AI-assisted code generation, contextual suggestions, and automated workflows to enhance developer productivity and reduce development time. The use case highlights seamless integration into development environments, improved code quality, and faster delivery cycles, serving as a blueprint for building efficient, AI-powered software engineering practices.
Enterprise AI controls & the agent control plane
This demonstration showcases the implementation of enterprise-grade governance using an AI control framework and centralized agent control plane. It provides a technical walkthrough on enforcing policies, managing agent identities, monitoring activities, and ensuring compliance across AI agents. The use case highlights secure orchestration, auditability, and lifecycle management, serving as a blueprint for controlling and governing AI agents at scale in enterprise environments.
From Dev to Prod in One Click
This demonstration showcases a seamless “Dev to Prod in One Click” workflow using Visual Studio Code and GitHub Copilot. It provides a technical walkthrough on cloning repositories, configuring MCP servers, leveraging AI to generate infrastructure-as-code (Bicep), and automating CI/CD pipeline creation and deployment to Azure. The use case highlights AI-driven development, automated best practices, and rapid deployment, serving as a blueprint for achieving efficient, end-to-end application delivery with minimal manual intervention.
GitHub Advanced Security (with GitHub Secret Protection & GitHub Code Security)
This demonstration showcases the implementation of secure DevOps practices using GitHub Advanced Security, focusing on GitHub Secret Protection and GitHub Code Security. It provides a technical walkthrough on detecting and preventing exposed secrets, performing automated code scanning, and identifying vulnerabilities across repositories, while integrating security checks into CI/CD pipelines. The use case highlights proactive risk mitigation, automated remediation, and governance controls, serving as a blueprint for building scalable, secure, and developer-friendly application security in mode
Hosted agents in Foundry Agent Service
This demonstration showcases the design, deployment, and orchestration of AI-powered hosted agents using the Microsoft Foundry Agent Service. It provides a technical walkthrough on creating and managing agents, integrating tools and APIs, and enabling multi-agent workflows for business use cases such as customer support and loyalty management. The use case highlights secure governance, scalability, and real-time execution, serving as a blueprint for building and managing production-ready AI agents in an enterprise environment.
Integrating a Microsoft Foundry Agent into Copilot Studio
This demonstration showcases the integration of a Microsoft Foundry agent into Copilot Studio to enable seamless interaction between custom AI agents and conversational interfaces. It provides a technical walkthrough on connecting agents, exposing capabilities as tools, and orchestrating responses within Copilot Studio. The use case highlights enhanced extensibility, unified user experiences, and streamlined deployment, serving as a blueprint for integrating enterprise-grade AI agents into conversational applications.