Browse All Azure Content (628)

Pooja Pradhan outlines an Azure-focused approach to move from drift detection to diagnosis by combining IaC signals (Terraform/Bicep), Azure Resource Graph, and Activity Logs, then using an AI model to generate a human-readable root cause analysis with impact and recommended remediation steps.

junjieli announces updates to Foundry Toolkit that bring an end-to-end image generation workflow into VS Code, including discovering and deploying GPT-Image-2 to an Azure AI Foundry project, iterating in an Image Playground, and exporting ready-to-paste API code.

Valini Sunthwal describes a multi-repo Azure platform that uses Terraform, versioned releases, and daily reconciliation to detect and recover from infrastructure drift across many subscriptions. The post breaks down repo boundaries, pipeline design, drift detection tiers, and security practices like OIDC, Key Vault, and private endpoints.

PrabalDeb lays out a practical reference architecture for running diffusion model workloads on Azure Kubernetes Service (AKS), focusing on GPU/CPU lane separation, dispatch and autoscaling options (Kubernetes-native vs Service Bus + KEDA), secure ingress and identity, durable storage for outputs and model caches, and end-to-end observability for both apps and GPU hardware.

Vineela Suri explains how to configure Azure SRE Agent with Azure Monitor to cut alert fatigue: use reinvestigation cooldowns, tiered response plans, and scheduled hygiene reports to consolidate noisy alerts, improve thresholds, and keep LLM token costs under control.

Vineela Suri explains how the Azure SRE Agent plugin marketplace works: teams publish plugins (skills + MCP connectors) to a shared GitHub repo, and any SRE Agent instance can discover and install them. The post walks through an AKS incident investigation example and the marketplace.json manifest structure.

skundapura explains how to observe and troubleshoot AI agent workloads in Azure AI Foundry, comparing tracing and telemetry support across Microsoft Agent Framework, Semantic Kernel, LangChain/LangGraph, and the OpenAI Agent SDK using OpenTelemetry with Azure Monitor and Application Insights.

Jason Helmick announces the GA release of Microsoft Desired State Configuration (DSC) v3.2.0, covering new built-in Windows resources, experimental Bicep orchestration over gRPC, expanded WhatIf support, version pinning, expression language updates, and adapter/extension improvements, plus install and support lifecycle details.

dbandaru shows how to connect the New Relic-hosted MCP server (Preview) to Azure SRE Agent, including API key setup, RBAC considerations, and how to create a New Relic-focused subagent/skill so the agent can query NRQL, traces, logs, metrics, alerts, and dashboards via natural language.

prabhattomar explains how to build a Kubernetes-native DBaaS-style SQL platform using Crossplane to provision Azure Database for PostgreSQL Flexible Server, including private networking, DNS-based read/write endpoints, and an active-passive multi-region HA/DR approach with replica promotion and Traffic Manager routing.

Sokuma announces the public preview of Azure Monitor Service Level Indicators (SLIs) and explains how SLIs/SLOs, error budgets, and burn-rate alerting help teams measure real customer impact (availability and latency) using Azure Monitor metrics at the Service Group level.

skundapura outlines a phased approach to migrate file-based application logging from Splunk to Azure Application Insights on VMs, using Azure Monitor Agent and Log Analytics, then mapping alerts and optionally adding SDK instrumentation for deeper traces and metrics with security and PHI considerations.

Samarpitaa explains where Azure AI Foundry IQ fits (and doesn’t) for enterprise agent knowledge access, then shows a reference approach for querying Foundry IQ knowledge bases directly via the Azure AI Search Python SDK with permission-aware retrieval and citations.

Shah_Viral explains how to build an enterprise “knowledge copilot” on Azure using Foundry IQ knowledge bases and Azure AI Search agentic retrieval, including C#/.NET setup, MCP-based agent connection, and key trade-offs around preview maturity, cost, latency, and security controls like ACLs and Purview labels.

dikshashakya explains how to turn long-form video transcripts into structured Standard Operating Procedures (SOPs) using GraphRAG to build a knowledge graph and Azure OpenAI to generate grounded sections like scope, definitions, responsibilities, and step-by-step procedures.

Microsoft Developer shares a short sponsor session from Azure Cosmos DB Conf 2026 where Andrew Ruffin (AMD) explains how AMD EPYC hardware impacts Azure Cosmos DB performance, including performance-per-dollar claims and how lower per-request cost can translate into better RU efficiency and scaling.

Microsoft Developer hosts a Cosmos DB Conf 2026 session where Sergiy Smyrnov demonstrates migrating an AdventureWorks-based ASP.NET/EF Core app from a relational database to Azure Cosmos DB for NoSQL, using GitHub Copilot and Cosmos DB Agent Kit prompts to plan the move and rewrite the data layer.

Microsoft Developer hosts James Codella’s deep dive into Azure Cosmos DB querying and indexing, focusing on how partition routing and index choices affect performance and RU cost, with practical guidance on SQL features, index types, and tuning high-RU queries.

Microsoft Developer shares Yohan Lasorsa’s session on why “vector search by default” often fails in RAG, and how to improve retrieval quality by using agentic RAG with Azure Cosmos DB hybrid search (vector + full-text) so an AI agent fetches the right context when it actually needs it.

Microsoft Developer hosts Eric Boyd explaining how to use Azure Cosmos DB as a coordination mechanism for distributed workflows, covering lock/lease and leader-style patterns, saga orchestration for long-running work, and the production tradeoffs around retries, contention, hotspots, and multi-region consistency.