The AI Wire

Lead dispatchtechcommunity.microsoft.com ▸ azure· filed 2 Oct 2026

Federated Agent Factory: Microsoft's Reference Architecture for AI Agents Across Entra Tenants

Microsoft's reference architecture for multi-tenant AI agent governance uses a federated agent factory, keeping agent identities and data within business-unit tenants while a governing tenant sets standards and operational views. It specifies runtime enforcement via Azure API Management for pro-code agents and Agent 365/Purview for Copilot Studio agents, with policy-as-code for per-action authorization. Several components remain in preview, including the dedicated AI Gateway tier and multitenant agent management.

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No. 087

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techcommunity.microsoft.com ▸ tooling· filed 2 Oct 2026

Open-source demo separates AI model proposals from sandboxed tool execution

An open-source demo runs a Copilot-based food-ordering assistant on Azure Kubernetes Service, with tool executions confined to per-session sandboxes built from OpenSandbox and Kata Containers. The project separates model-proposed actions from actual execution, showing the execution platform determines whether and how proposals become actions. It also documents operational issues including image warmup timing and a Markdown rendering fix.

techcommunity.microsoft.com ▸ product· filed 27 Sept 2026

Azure Container Apps Sandboxes: per-agent microVMs with egress controls

Azure Container Apps Sandboxes runs untrusted agent workloads in hardware-isolated microVMs that start in under a second, making it practical to give each task its own machine. Outbound traffic is forced through a default-deny proxy that can enforce allowlists, inject authentication headers outside the sandbox, and send requests to a customer webhook for approval. Microsoft says preview usage passed one million sandboxes created per day; pricing is per vCPU-core-second and GiB-second.

microsoft.com ▸ product· filed 27 Sept 2026

Microsoft launches Copilot Managed Runtime public preview with SDK and CLI

Microsoft has made Copilot Managed Runtime available in public preview, adding an SDK and CLI so apps built with external tools can run inside a Microsoft 365 tenant with Entra identity, organizational policies, and a centralized admin inventory. The runtime handles provisioning, deployment, versioning, and governance while keeping code Git-backed and editable. Pricing and production timelines are not yet specified, and consistency of policy enforcement across third-party integrations remains to be tested.

techcommunity.microsoft.com ▸ product· filed 25 Sept 2026

Microsoft Foundry Insights public preview automatically analyzes agent traces for unknown failure patterns

Microsoft Foundry Insights is now in public preview, automatically scanning agent traces in Azure Monitor Application Insights to surface recurring failure patterns teams did not anticipate. It flags findings with categories, severity, and likely causes, and complements rather than replaces monitoring and evaluation. Evidence quality and scan results depend on telemetry; an empty scan does not prove an agent is problem-free.

learn.microsoft.com ▸ product· filed 18 Sept 2026

Microsoft Foundry Agent Endpoints: Stable URLs, Version Pinning, and No Traffic Splitting

Microsoft Foundry agents receive stable endpoints at creation and route traffic by a version selector, but the default "always use latest" policy means any new version goes live immediately unless an administrator pins a specific version. There is no traffic splitting, so rollbacks are all-or-nothing, and production teams must rely on manual pinning. Entra ID-only authorization and an opt-in public endpoint for Microsoft 365 are among the operational constraints.

azure ▸ tooling· filed 10 Sept 2026

Microsoft Introduces MCP Server for Azure Update Discovery, With Only Lifecycle Details

Microsoft has introduced the Release Communications (MRC) MCP server for AI-powered discovery of Azure product updates, but the announcement only supplies lifecycle-stage categories and omits technical and access details. The page does not say whether the server exposes the same update feed as the Azure Updates site, nor how it handles preview-versus-launched distinctions. As a result, the practical value for MCP-driven tooling remains unspecified.

azure ▸ tooling· filed 10 Sept 2026

Microsoft introduces APIOps CLI for Git-based Azure API Management configuration

Microsoft has announced APIOps CLI, an open-source command-line tool that manages Azure API Management configuration through Git-based workflows. It extracts existing APIM configuration into versioned artifact files, supports pull-request review and CI/CD pipeline scaffolding, and publishes approved configuration back into environments. The tool is intended to address manual configuration changes and limited change visibility by treating API configuration as code.

azure ▸ azure· filed 10 Sept 2026

Azure API Management AI Gateway adds OpenTelemetry observability and cost limit policies

The AI Gateway tier of Azure API Management now emits OpenTelemetry logs, traces, token metrics, and estimated cost metrics, and supports calendar-based cost limit policies that can block requests when projected budgets are reached. The update also refines provider onboarding and expands Anthropic Messages compatibility. Because spend figures are estimates, teams using hard blocks should verify the gap between projections and final billing.

azure ▸ tooling· filed 10 Sept 2026

Microsoft Offers MCP Server for Azure Updates With Limited Details

Microsoft has made an MCP server, Microsoft Release Communications, available through the Azure Updates page, describing it as enabling AI-powered discovery of Azure Updates. The listing stops at a link and a purpose statement: it offers no sample queries, data coverage, authentication, or operational details. Engineers can only follow the link to documentation; the feed's query behavior and scope remain unverified.

azure ▸ development· filed 6 Sept 2026

Microsoft Foundry details six-phase process for migrating LLM models

Microsoft Foundry has detailed a six-phase process for moving LLM-powered applications between model generations, with model retirement dates now built into the platform lifecycle. The guidance emphasizes that swapping model names can silently change response formatting, schemas, and tool behavior, and that validation and canary rollouts are necessary because offline evaluation can miss production issues. A worked example ends in a deliberate split deployment rather than a clean cutover.