Browse Artificial Intelligence Community (123)

NagaSurendran details practical strategies for organizations migrating from Heroku, focusing on how Azure and its integrated tools—including GitHub Copilot and Microsoft Foundry—enable modern, secure, and intelligent cloud-native applications.

Lee_Stott explores how to build On-Call Copilot, an AI-driven, multi-agent incident triage and reporting solution using Microsoft Agent Framework, Foundry Hosted Agents, Model Router, and Azure OpenAI—detailing the technical patterns, code, and deployment steps for practical DevOps engineers.

shashban presents an overview of the Azure Copilot Migration Agent, highlighting its integration with GitHub Copilot to simplify, accelerate, and govern large-scale Azure migrations for developers and IT teams.

Mandy Whaley outlines how GitHub Copilot and the new modernization agent are bringing AI-powered automation to every stage of application modernization, with end-to-end workflows integrating deeply into Azure and developer toolchains.

Sanchit Mehta presents a detailed look at how the Azure SRE Agent autonomously investigates and resolves incidents, often identifying and fixing its own issues. The post explains how architectural choices—like filesystem workspaces and context layering—make these advanced AI-driven capabilities possible.

dchelupati introduces the Azure SRE Agent’s general availability, describing its new operational and automation features for Site Reliability Engineering on Azure, including integration, workflow orchestration, and deep diagnostic capabilities.

dchelupati explores how Deep Context transforms the Azure SRE Agent, enabling it to learn and act like your best SRE by leveraging continuous code access, persistent memory, and automation for incident response.

Mayunk_Jain announces the GA release of Azure SRE Agent, highlighting its AI-powered DevOps automation for Azure. The piece covers technical architecture, operational outcomes, integration resources, and learning opportunities for reliability-focused teams.

Coryskimming from Microsoft introduces the packed line-up for Azure at KubeCon Europe 2026, spotlighting hands-on AKS labs, AI/ML workload sessions, security, cloud-native DevOps practices, and open-source solutions from Microsoft's top engineers.

damocelj offers a practical walkthrough on securely deploying LLM inferencing with vLLM and NVIDIA NIM microservices in air-gapped Azure Kubernetes Service clusters, tackling network isolation, GPU configuration, and model artifact challenges.

bobmital shares a hands-on playbook for optimizing enterprise LLM inference on Azure, guiding technical teams through architecture, hardware selection, quantization, and model serving best practices across AKS, Ray Serve, and vLLM.

anbonagi presents a comprehensive analysis of the Model Context Protocol (MCP) and mcp-cli tool, highlighting dynamic tool discovery approaches for AI agents and strategies to optimize token usage in real-world integrations.

Jan-Kalis details how Azure Container Apps Dynamic Sessions can securely execute AI-generated and agent-run code using isolated sandboxes, with MCP integration, code interpreters, and custom containers. This practical guide illustrates setup, security, and deployment best practices.

sgangaramani offers a comprehensive guide to building production-ready agentic AI systems, highlighting how Microsoft Azure AI Foundry, Copilot Studio, and related tooling enable scalable and governed enterprise automation beyond chatbots.

bobmital examines the architectural and economic challenges of large language model inference at enterprise scale, with a focus on Azure and Anyscale’s Ray integration for distributed AI workloads.

kinfey explores Phi-4-Reasoning-Vision-15B, Microsoft's new vision reasoning SLM. The article provides developers with detailed design analysis, example code, and real-world applications for visual understanding and actionable decision-making.

harshul05 explains how Generative Pages bring AI-powered page design to Power Platform, enabling developers to create model-driven app interfaces by describing requirements in natural language.

pratikpanda explains how the Agent Skills SDK lets developers give AI agents reliable, context-aware skills using an open format and Python SDK, with integration for Microsoft agent ecosystems.

bobmital examines the unique challenges of enterprise-scale LLM inference, focusing on the interplay of accuracy, latency, and cost in Azure deployments using Anyscale Ray and AKS. This article provides actionable insights for architects and engineers deploying AI workloads in the cloud.

AnaviNahar introduces Azure Databricks Lakebase, now generally available, highlighting its serverless architecture and AI-native features for building real-time, intelligent applications on Azure.