A step-by-step guide to enable search in the semantic kernel agents using bing grounding in Azure Foundry AI Agent using A2A.
In this post we explore the evolution from Azure IoT Operations Data Processor Pipelines to Dataflows, why we adopted a hybrid strategy with custom Rust pods, and the architectural lessons we learned building event detection systems at the edge.
When setting up an experiment is complex, agents can automate the process to make it faster and more reliable.
How we built a production-ready MCP server with OAuth 2.1 authentication and On-Behalf-Of flow for Microsoft Graph, navigating a rapidly evolving specification.
Agentic systems have some discretion in the parameters they sent to tooling, but there are cases, such as experimentation, when you need 100% adherence to a set of parameters.
How we built a minimal, scalable GitOps workflow for edge applications using Azure IoT Operations, Azure DevOps, and a multi-repo strategy. Includes pipeline templates and scripts for real-world deployments.
Learn how to streamline AI development by using Microsoft Devtunnels to connect local services with Azure Machine Learning evaluation pipelines, eliminating deployment delays while maintaining comprehensive cloud-based validation.
This blog details how the Azure AI Evaluation SDK can be used to assess the performance of a small language model for function calling, such as Phi-4-mini-instruct, and view the results in Microsoft Foundry.
