Browse Security Community (188)

Lee Stott invites AI engineers to a Microsoft Foundry Discord round table on using the Browser Automation Tool (BAT) to let agents drive real browser workflows via Playwright Workspaces, with a focus on setup basics, practical use cases, and the guardrails needed for responsible, auditable automation.

Jordan Selig explains how Microsoft Foundry’s new AI Gateway control plane lets platform teams create or associate an Azure API Management (APIM) gateway from the Foundry admin console, while keeping the runtime on Azure App Service. The post breaks down what Foundry now governs, what still belongs in APIM, and how to adapt an existing App Service agent sample.

VimalVerma outlines Hypervelocity Engineering (HVE) as an operating model for building and continuously evolving Azure AI Landing Zones, with a focus on platform engineering, Infrastructure as Code, Policy as Code, and security-by-design so enterprise AI platforms can scale without losing governance.

Lee Stott invites AI engineers to a Microsoft Foundry Discord round table on scaling agent apps beyond demos, focusing on how Foundry Toolbox, Skills, and Tool Search reduce tool sprawl, prompt bloat, and auth plumbing by centralizing tools behind a governed MCP endpoint with runtime discovery.

jordanselig explains the new stable Enterprise-Managed Authorization (EMA) extension for MCP and how it differs from a centrally governed OAuth setup using Microsoft Entra ID and Azure App Service Authentication. The post includes a working sample, a local EMA lab, and practical security details for deploying an Entra-governed MCP endpoint.

Suma SaganeGowda explains how Microsoft 365 built COSMIC, an internal platform layer on Azure Kubernetes Service (AKS), to standardize provisioning, deployments, security/compliance guardrails, and observability across globally distributed services so product teams can ship faster without taking on Kubernetes operational overhead.

Manasa Ramalinga lays out a practical reference map for governing enterprise AI and autonomous agents, focusing on how to turn responsible AI policy into enforceable controls, runtime visibility, and audit-ready proof using Microsoft’s governance, security, and observability services.

jordanselig shares a reference implementation for giving an AI agent both short-term conversation history and durable, user-scoped memory on Azure App Service, using Redis for bounded session history and Cosmos DB vector search for recall, with keyless auth via managed identity and a one-command azd + Bicep deployment.

akhilkarmalkar announces Azure Front Door edge actions (public preview), a way to run lightweight JavaScript during request processing at Microsoft’s global edge. The post explains where edge actions run in the Front Door pipeline, what scenarios they enable (routing, headers, auth checks), and how Hyperlight micro-VM isolation is used to keep execution secure.

jisunchoi explains how to replace “multi-model chaos” with a governed AI gateway on Azure using Azure API Management, covering cost controls (token quotas and budget-based model downgrades), security hardening (managed identity + private endpoints), observability with Application Insights, and a Terraform-based deployment you can integrate with GitHub Copilot.

abhimittal shows how to use Azure API Management (APIM) as an AI gateway in front of Azure AI Foundry to capture per-model token usage for governance. The post walks through an inbound policy that authenticates with managed identity, emits token metrics to Azure Monitor/Application Insights, and adds edge protection with Azure Front Door + WAF.

kinfey shares a reference implementation for running long-lived autonomous coding agents from Microsoft Teams, using MCP as the control plane and Azure Container Apps dynamic sessions as a Hyper-V-isolated sandbox. The post focuses on multi-agent orchestration, deployment reliability under platform timeouts, and practical security guardrails like auth, allowlists, private ingress, and managed identities.

supriyas lays out a practical, end-to-end lifecycle for building enterprise AI agents, using a banking “loan agent” example to show how to design guardrails, build with safety controls, test with evaluations and red teaming, deploy gradually, and continuously monitor and iterate using Microsoft Foundry and Azure services.

Nir Mashkowski shares customer examples of how Azure SRE Agent is being used to reduce incident triage and investigation time by having an AI-powered agent gather evidence, classify issues, and recommend next steps, with an emphasis on governance controls and operational “memory” for teams running production on Azure.

KishoreKumarPattabiraman explains why “golden paths” in platform engineering need to be treated as long-lived products, not one-off projects. Using examples like an AKS migration and identity modernization, the post lays out an operating canvas for ownership, guardrails, adoption strategy, and measurable feedback loops that keep paved paths trusted over time.

Sunita_AZ0708 documents a validated reference architecture for running Siemens Teamcenter on Azure Virtual Machines while using Oracle Exadata Database Service (Oracle Database@Azure) for the database tier, including identity integration, private cross-cloud networking, backup/recovery validation, and performance test results.

EldertGrootenboer explains how to secure Azure Service Bus namespaces using layered controls—firewall rules, service endpoints, private endpoints, and Network Security Perimeter—then ties the network layer to identity with Entra ID and managed identities, including practical notes on geo-replication and DNS.

daisami walks through adding production-grade auditing and telemetry to AI agents using Microsoft’s Agent Governance Toolkit (AGT) in a .NET (C#) sample. It shows how to append governance events to Azure Blob Storage, export OpenTelemetry metrics/traces to Application Insights, and apply default-deny policies with practical security guidance for log sanitization.

aakarshdhawan walks through how to enable Microsoft Entra ID B2B guest access for Power Apps (Canvas and Model-driven) that use Microsoft Dataverse, including the tenant invitation flow, environment access, licensing requirements, and Dataverse security roles needed to validate least-privilege access for external users.

pallakatos introduces kars, a Kubernetes-native runtime for running AI agents on Azure with a “treat agents as untrusted code” security model: per-agent sandboxes, policy enforced via CRDs, zero credentials in the agent process, and an end-to-end encrypted inter-agent mesh designed for governance at scale on AKS.

wmarkley announces GA support for client-side, end-to-end data integrity in Azure Blob Storage using CRC64-NVME in the latest Azure Blob SDKs. The post explains how checksum validation works on upload/download, why CRC64-NVME is preferred over MD5, performance considerations, and the minimum SDK versions needed to enable it.

jometzg walks through building an autonomous PIM elevation audit workflow using Azure SRE Agent, including how to move from interactive chat exploration to a headless scheduled subagent that queries Log Analytics and emails a daily alignment report to stakeholders.

Lee Stott explains the Model Context Protocol (MCP) and why it’s becoming a practical standard for connecting LLM apps to tools and data. The post highlights recent updates to Microsoft’s MCP for Beginners curriculum, including spec alignment, validated SDK samples, and a security-focused refresh with concrete fixes and audits.

RajyaLaxmiYellajosyula announces the Oracle AI Database@Azure AI adoption playbook and outlines the main blueprint patterns for building AI experiences on Oracle data using Microsoft services, with a strong emphasis on security, governance, and regulated-industry requirements.

ssaroiu explains how Microsoft built a production-oriented Rowhammer defense into the Azure Cobalt 200 SoC, focusing on practical cloud-scale constraints like performance overhead, configurability across DRAM quality, and operating the protection safely with privacy-preserving telemetry in confidential computing environments.

VikasBhatia summarizes how Azure Confidential Computing is maturing for sovereign and regulated workloads, highlighting recent GA and preview milestones across confidential VMs, hardware-rooted security, key protection, and operational capabilities like confidential live migration, plus how these controls fit into broader governance and compliance requirements.

bexelbie explains what the Microsoft UEFI CA 2011 expiration in June 2026 means for Linux systems using UEFI Secure Boot, why expiration isn’t the same as revocation, and what can actually cause boot failures when vendors move to 2023-only signed shims.

vzisiadis walks through how to put Azure API Management (APIM) in front of MCP servers to handle authentication and authorization, from basic Entra ID token validation to interactive OAuth sign-in from VS Code, app-role based access control, and governing external MCP servers like GitHub via passthrough and tool-level blocking.

jordanselig explains why most Model Context Protocol (MCP) servers are being deployed without real authentication, then walks through a defense-in-depth reference architecture on Azure App Service using Entra ID OAuth, managed identity, Key Vault, private networking, API Management, and monitoring to reduce common MCP attack paths.

devanshirastogi explains upcoming changes to Azure Firewall explicit proxy and provides a migration walkthrough for PAC file–based setups, including moving PAC retrieval to customer-managed Azure Storage and using Managed Identity with the right RBAC roles. The guide includes portal steps plus PowerShell and Azure CLI examples for configuring Firewall Policy.

varghesejoji introduces the ARM MCP Server and a GitHub catalog of 24 proof-of-concept agents that use Model Context Protocol tools to query Azure Resource Graph and (optionally) deploy ARM templates. The post focuses on safe, repeatable “determinism” patterns for governance, FinOps, and SRE workflows in Azure.

OpeSam-Olowu explains what Microsoft announced at Build 2026 for running AI locally on Windows in telecom environments, covering Microsoft Foundry on Windows (Windows AI APIs, Foundry Local, and Windows ML), new on-device Aion models, and OS-level controls for secure, governed agent execution.

ShubhraS announces the general availability of Microsoft Signing Transparency (MST), a SCITT-aligned transparency ledger that logs production builds for selected Microsoft cloud services. The post explains how customers can independently verify code integrity using cryptographic proofs and audit trails, and introduces the Ledger Explorer tool for offline verification.

Gaurav Bhardwaj describes a hybrid Azure-based document extraction architecture for construction drawings and project documentation, combining deterministic field extraction with bounded LLM verification. The post breaks down the event-driven pipeline, confidence gating, cost trade-offs, and the security controls needed to run this kind of document intelligence workflow in production.

Jay Li explains how to migrate large Azure hub-and-spoke environments away from ExpressRoute hairpin routing through Microsoft Enterprise Edge (MSEE) and toward Azure Virtual Network Manager (AVNM) mesh. The post covers scale limits, enabling High-Scale Private Endpoints (HSPE), rollout/rollback strategy, and how to keep security inspection and segmentation intact.

samcogan explains how to use Azure API Management (APIM) as an MCP gateway to control which tools an agent can see and invoke when connecting to an MCP server. The post covers governance patterns (allowlist vs deny-list), plus auth, logging, network isolation, and streaming-related trade-offs.

Jamesdld23 explains how to avoid the 230-second HTTP timeout in Azure Functions by splitting long-running sync work into an HTTP “request” function that enqueues a message and a queue-triggered function that performs the job, with practical PowerShell and Azure CLI examples plus Entra ID-based auth hardening.

Mahesh Sundaram announces a public preview in Azure Monitor that lets platform teams collect Azure resource platform logs at scale using Data Collection Rules (DCRs), replacing per-resource diagnostic settings with a centralized, policy-driven model that supports governance, cost control, and modern identity-based access.

Heather Poulsen outlines a governance-first blueprint for building scalable agentic AI systems, focusing on how to embed consistent controls and quality checks across user interactions, agent orchestration, integrations, data, and models so systems can scale without losing trust and oversight.

Heather Poulsen shares an event session overview on designing Azure AI Landing Zones as a production-ready foundation for deploying AI applications and AI agents at scale, with guardrails for networking, identity, security, governance, and cost control using Microsoft’s recommended architecture frameworks.