Browse All Community (255)

stevenbucher announces public preview support for versioning custom Azure Policy definitions and initiatives, including how to create new versions, pin assignments to major/minor versions, and validate which version is effective via REST API, portal, CLI, and PowerShell.

Nivas Narayanasamy lays out a practical architecture for making private Azure VMware Solution workloads reachable by Azure AI Foundry agents without moving data. The post shows how to use MCP “bridge” servers on VNet-integrated Azure Container Apps, with ExpressRoute, private endpoints, Entra managed identity, and Key Vault-backed secrets to keep access private and read-only.

Mayuri Gupta announces the public preview of Azure Red Hat OpenShift hosted control planes, explaining how the control plane can run as a Microsoft-managed service while worker nodes stay in the customer subscription. The post covers operational benefits, Azure integrations (identity, monitoring, IaC), security controls, supported regions, and preview pricing.

Pamela_Fox shares the full set of MCP Live session recordings and resources, covering the Model Context Protocol’s latest spec updates, MCP server/client development in VS Code and GitHub Copilot, enterprise governance with Microsoft Foundry Toolboxes, and evolving MCP authentication patterns.

Satoshi Kubota proposes using a Data Center WordCode Layer (DCWL)—a fixed-length 32-bit word encoding originally aimed at Azure text-processing workloads—to speed up Copilot for Windows and other Windows client text-heavy pipelines such as local RAG, semantic search, and log analysis.

nzthiago explains the new GA support for site-scoped certificates and end-to-end TLS in Azure Functions Flex Consumption, including certificate sources (Key Vault, managed certs, uploads), how to expose certs to code on Linux workers, and how to implement inbound and outbound mutual TLS safely.

Wuyi Weng explains how Azure SRE Agent can use an Azure Managed Grafana dashboard (via the MCP endpoint) as executable context to investigate GitHub Copilot telemetry in Application Insights, turning panel queries, variables, and descriptions into fast, accurate triage and per-session diagnoses.

Gaurav Bhardwaj walks through a practical “refund agent” example to show why AI agent observability needs more than green HTTP checks, and how to use Microsoft Foundry plus Azure Monitor (Application Insights and Log Analytics) to trace runs, evaluate tool-call correctness, set alerts, and bake in security and privacy controls.

kedikala lays out a practical security framework for agentic apps on Azure, focusing on how to keep tool calls safe when untrusted content can steer an agent toward sensitive reads or risky writes. The post breaks controls down across identity, retrieval, request validation, execution constraints, and outcome verification.

Wiliam_Rosa breaks down how Spark Structured Streaming’s Real-time mode (as implemented in Azure Databricks) can cut anomaly-detection latency from seconds to sub-millisecond, using an Ethereum transaction pipeline that classifies events as ALLOW or QUARANTINE based on protocol invariants and sensitive-payload checks.

jordanselig explains a new public preview capability in Azure Managed Connectors: sending trigger events directly to Azure App Service apps. The post covers how the App Service destination is configured, how managed-identity callbacks are authenticated with App Service built-in auth (Easy Auth), and includes an end-to-end sample with Bicep and Azure Developer CLI.

Rohon Mohapatra explains how the Citadel reference architecture builds on AI landing zones and Microsoft Foundry to standardize enterprise AI operations—covering shared access controls, observability, identity, and security governance across multiple teams and workloads.

KimVaddi explains why many oil & gas AI initiatives stall on inconsistent business meaning rather than data volume, and argues that the “meaning layer” is the real readiness bottleneck. The post connects OSDU, Azure Data Manager for Energy, and Microsoft Fabric IQ’s preview ontology capability as a practical path to governed, cross-domain reasoning.

Steven Truitt shares a hands-on walkthrough of using Microsoft Discovery as AI assistance to take a small chip-design project from a rough spec through C and HLS, into Verilog RTL, and finally to physical layout and basic timing/power optimization using open-source EDA tooling.

mnshnth announces that workload orchestration for Azure Arc is now available in the Azure portal, focusing on a portal-first onboarding flow that lets teams deploy a pre-packaged app to an Azure Arc-enabled Kubernetes cluster in minutes and then scale the same approach across distributed sites.

kchoi announces a public preview feature in Azure Arc Site Manager that centralizes monitoring and management of Azure Local workloads across multiple sites, including Azure Local virtual machines and Kubernetes clusters, with bulk actions plus grouping, filtering, and search to speed up day-to-day operations.

AzureAndrewChen announces the general availability of Dell Managed PowerScale for Microsoft Azure, a Dell-operated managed file storage service that can be provisioned and managed through Azure-native interfaces. The post highlights supported protocols, scale limits, and how the service integrates with Azure networking and Blob Storage tiering.

HilaryWang announces a public preview feature for Azure Virtual Machine Scale Sets that lets Azure automatically choose availability zones based on SKU availability, capacity signals, and your placement constraints, reducing the need to maintain region-specific zone lists for multi-region zonal deployments.

willchap describes a practical framework for evaluating scientific AI systems—execution, optimization, and exploration—using three RF engineering design challenges. The post shows how Microsoft Discovery orchestrates agentic workflows that combine analytical reasoning with HFSS simulations, while surfacing assumptions, trade-offs, and decision points for human guidance.

ellievail announces general availability of user-bound user delegation SAS for Azure Storage, which restricts a user delegation SAS token so it can only be used by a specific Microsoft Entra ID identity. The post explains how it works with RBAC, cross-tenant scenarios, and how to generate and share tokens safely.

Sudha Mahajan explains how Azure Migrate Network Planning adds network-aware discovery and assessment to VMware lift-and-shift migrations, helping teams capture dependencies, translate source constructs into Azure networking recommendations, surface readiness issues, and include network costs and security intent in the migration business case.

viveksingla announces the general availability of Ephemeral OS Disk full caching for Azure VMs and VM Scale Sets, explaining how caching the entire OS image on local storage improves OS disk read reliability and latency, and showing how to enable it via Azure CLI and ARM templates.

MinseokSong walks through a reference implementation that uses Microsoft Foundry and an Azure Function to classify incoming support emails, then uses Power Automate to validate the AI recommendation against a SharePoint allow-list, require human approval, and create an Outlook draft (without sending).

christinchen announces the general availability of Azure Copilot’s Troubleshooting Agent, a built-in experience in the Azure portal that helps teams investigate and resolve operational issues faster by combining resource context, supported diagnostics, and recommended actions—while keeping customers in control through identity and RBAC.

MarkRussinovich lays out a practical decision framework for choosing between two availability zones, three zones, or service-managed zone redundancy in Azure, focused on meeting single-zone failure objectives while balancing capacity, durability, and operational complexity.

bharadwajr explains how the Azure team built GEM (Great Experiences Matter), an AI-enabled “feedback-to-fix” loop that aggregates customer feedback at scale, turns it into prioritized insights, and creates actionable Azure DevOps work items with an auditable evidence trail and human review.

pratikpanda explains a practical way to make shared Azure DevOps pipeline templates easier to adopt by replacing long parameter lists with a manifest object built at pipeline-assembly time, then validating that manifest with versioned JSON Schema checks so deployments fail fast when the contract is broken.

kshatzkamer outlines a reference architecture for “orchestrated media intelligence”: an orchestration layer that connects trusted data, specialized AI models/agents, cloud infrastructure, and governance across end-to-end media workflows. The post uses Azure OpenAI, Azure AI Speech, and Azure AI Foundry examples to show how to keep humans accountable while scaling automation.

newmancheng explains how Microsoft Discovery combined agentic AI, computational predictors, and wet-lab feedback to design and validate a novel organic negolyte for redox flow batteries, with a focus on preserving negative results as durable knowledge that improves subsequent design rounds.

carlottacaste introduces “Inside Microsoft Foundry: Quickstart”, a video series focused on the practical work of building and shipping AI agents with Microsoft Foundry and the Microsoft Agent Framework, including model selection, grounding in your own data, tracing, evaluation, and moving from prototype to production.

devanshirastogi rounds up five recent Azure Firewall capabilities—some now generally available and others in public preview—covering explicit proxy support, IPv6 dual-stack filtering, HTTP header insertion, auto-learned SNAT routes via Azure Route Server, and higher-throughput IDPS with TLS inspection for Azure Firewall Premium.

rgarofalo walks through a hands-on build that locks down Azure AI Foundry both inbound (Private Endpoint) and outbound (agent egress via network injection), including the DNS zones you must create, how to prove public access is actually blocked, and how to troubleshoot opaque agent tool-call failures like 424 errors.

Christine Caggiano, Joshua Bradley, Steven Truitt, and William Chappell describe how Microsoft Discovery’s Discovery Engine adds CLIO (a self-adaptive “cognitive loop”) to improve agentic scientific problem-solving, and share benchmark results from Agent’s Last Exam showing higher scores and better consistency through multi-model, evidence-driven exploration.

wolfgangdesalvador introduces a public preview optimization for Azure Blob Storage List Blobs that returns results in Apache Arrow format, cutting response size and client parsing cost. The post explains the required REST headers and SDK versions, shows a Python decoding example, and shares rclone benchmarks demonstrating large speedups with parallel listing.

pranabpaul walks through the first part of building a retail assistant demo using Microsoft Fabric and Azure AI Foundry, focusing on setting up the Azure environment, provisioning Fabric capacity, loading sample data into a Lakehouse, creating an ontology, and wiring a Fabric Data Agent to query that data.

pranabpaul continues the 3IQ Retail Assistant demo by wiring unstructured PDF content into an Azure AI Foundry agent using Azure Blob Storage and Azure AI Search, including the RBAC permissions needed for managed identities and the networking trade-offs involved when publishing the agent to Microsoft 365 Copilot.

Mohammed Barqawi introduces Logic App Storage Inspector, a read-only Kudu site extension that helps troubleshoot Azure Logic Apps Standard by inspecting the underlying storage for workflow history, versions, and queue health, with guidance on installation, configuration settings, and managed identity permissions.

Dalibor Kovacevic explains how to use Azure SRE Agent’s advanced ServiceNow filtering to route the right incidents to the right response plan, then control how much autonomy the responder has (Autonomous vs Review) while you preview and tune matching before enabling it.

yairgil explains how the Azure Copilot Observability Agent can use Azure Monitor Log Analytics Basic and Auxiliary table plans as investigation evidence, helping teams reduce log costs while still correlating alerts, metrics, traces, topology, and recent changes during incident response—especially in high-volume AKS environments.

kinfey explains why “AI agent infrastructure” needs stronger security boundaries than traditional model hosting, using kars (an open-source Agent Reference Stack for Kubernetes) to show how to isolate agent runtimes, broker identity, govern tools/MCP, control egress, enforce token budgets, and produce auditable evidence for incident response.