Azure SDK February 2026 Ships: Native DI, Content Understanding, and `azd` That Knows When an AI Is Driving

Published: February 27, 2026

Ecosystem: .NET · Azure · AI

TL;DR

The Azure SDK February 2026 release (dropped yesterday) is a quiet-but-consequential drop for .NET AI developers. The headliners: native Microsoft.Extensions.DependencyInjection and Microsoft.Extensions.Configuration support baked into Azure SDK clients, a new Azure.AI.ContentUnderstanding preview NuGet for multimodal document/audio/video analysis, and an azd CLI that now auto-detects when an AI coding agent is at the wheel and skips interactive prompts accordingly. None of these are flashy keynote moments — but collectively they tighten the seams between Azure AI services and production-grade .NET apps significantly.

The Release That Snuck Up On You

Every month the Azure SDK team ships a release post. Most engineers skim it the way they skim their dependabot PRs — quickly and with mild guilt. This month, though, it’s worth a closer read. Three updates stand out specifically for teams building AI-powered applications on .NET and Azure.

1. Azure SDK Clients Are Now First-Class ASP.NET Core Citizens

The biggest ergonomic win: this release adds core support for Microsoft.Extensions.Configuration and Microsoft.Extensions.DependencyInjection, enabling better integration with ASP.NET Core applications and other .NET hosts. This matters more than it sounds. Prior to this, wiring up Azure SDK clients in a typical ASP.NET Core Program.cs required manual builder.Services.AddSingleton(...) boilerplate and a custom configuration-binding shim. Now, Azure clients can participate in the standard .NET host model the same way HttpClient or Entity Framework do. The update also implements support for client certificate rotation in the Azure.Core transport layer, enabling dynamic token binding scenarios where transport instances can be updated with new client certificate configurations at runtime without requiring full pipeline reconstruction. For teams running zero-downtime certificate rotation in regulated environments (finance, healthcare), this is a meaningful operational improvement — no more recycling the entire app pool when a cert rolls over.

And yes, the release also fixes a NullReferenceException that occurred when calling GetHashCode() on default(AzureLocation) — which is the kind of bug that only reveals itself at 2 AM in production. You’re welcome.

Practical integration (before/after):

// Before: manual wiring
var credential = new DefaultAzureCredential();
var client = new ContentUnderstandingClient(
    new Uri(config["AzureAI:Endpoint"]), credential);
builder.Services.AddSingleton(client);

// After: idiomatic .NET host model (with Feb 2026 SDK)
builder.Services.AddAzureClients(clients =>
{
    clients.AddContentUnderstandingClient();
    clients.UseCredential(new DefaultAzureCredential());
});
// Endpoint resolved automatically from IConfiguration

2. Azure AI Content Understanding — Multimodal, Finally Packaged for .NET

Azure Content Understanding in Foundry Tools is available as part of the Microsoft Foundry Resource in the Azure portal. It uses generative AI to process and ingest many types of content, including documents, images, videos, and audio, into a user-defined output format. Content Understanding offers a streamlined process to reason over large amounts of unstructured data, accelerating time-to-value by generating an output you can integrate into automation and analytical workflows. The GA API (2025-11-01) has been live for a while. What’s new is the .NET SDK path is now real. The preview release of the .NET NuGet for the Content Understanding SDK is now available. You can install it with: dotnet add package Azure.AI.ContentUnderstanding --prerelease The Python side got its own beta in this same wave: this version is the initial beta release of the Azure AI Content Understanding client library for Python, introducing the ContentUnderstandingClient for analyzing documents, audio, and video content using Azure AI Foundry’s content understanding capabilities — developers can now extract meaningful insights from various content types through a unified API. The service is genuinely useful for the classic enterprise document-processing scenarios: Content Understanding includes prebuilt analyzers designed for industry-specific scenarios including tax preparation, procurement document processing, contract analysis, call center analytics, media analysis, and much more. Cost model: Pay for only what you use — there are no upfront costs with Azure Content Understanding pay-as-you-go pricing. That said, multimodal processing (especially video) can rack up tokens fast. Test with representative samples before committing to production throughput estimates.

Quick start:

dotnet add package Azure.AI.ContentUnderstanding --prerelease

using Azure.AI.ContentUnderstanding;
using Azure.Identity;

var client = new ContentUnderstandingClient(
    new Uri("https://<your-resource>.cognitiveservices.azure.com/"),
    new DefaultAzureCredential());

// Analyze a PDF invoice using a prebuilt analyzer
var result = await client.AnalyzeAsync(
    "prebuilt-invoice",
    BinaryData.FromStream(File.OpenRead("invoice.pdf")));

⚠️ Preview caveat: The .NET package is still --prerelease. Do not use it for production workloads without evaluating breaking-change risk. The service itself (2025-11-01 API) is GA, but the SDK surface may shift.

3. `azd` Now Knows When an AI Agent Is Driving

This one is small but delightful. azd now detects when it’s running inside an AI coding agent and skips interactive prompts automatically, so automated workflows don’t hang. If you’ve ever watched a CI pipeline — or an AI coding agent’s tool-call loop — grind to a halt because azd provision decided to ask an interactive “Are you sure?” question, you know exactly why this matters. The February azd release (versions 1.23.3–1.23.6) closes that gap. AI-driven workflows that call azd as a shell tool can now proceed without human babysitting. azd also now supports JMESPath queries, giving you the ability to filter and transform JSON output directly in the terminal. The new --query flag lets you filter and transform JSON output from any azd command using JMESPath expressions — great for scripting and automation.

# Get just the endpoint URL from azd env output
azd env get-values --query "AZURE_OPENAI_ENDPOINT"

# List only resource names from a show command
azd show --query "services[].name"

Where This Fits: The Bigger Picture

All of this connects to a broader direction Microsoft has been moving in for the past year. Semantic Kernel is an open-source library that enables AI integration and orchestration capabilities in your .NET apps; however, for new applications that require agentic capabilities, multi-agent orchestration, or enterprise-grade observability and security, the recommended framework is now Microsoft Agent Framework. Agent Framework builds on the Microsoft.Extensions.AI.Abstractions package and provides concrete implementations of IChatClient for different services, including OpenAI, Azure OpenAI, Azure AI Foundry, and more — this is the recommended approach for .NET apps that need to build agentic AI systems with advanced orchestration, multi-agent collaboration, and enterprise-grade security and observability. Built-in observability via OpenTelemetry, Microsoft Entra security integration, and responsible AI features including prompt injection protection are included, along with standards-based interoperability through open standards like the Agent-to-Agent (A2A) protocol and Model Context Protocol (MCP) for agent discovery and tool interaction. The February SDK release is a small but meaningful step in that direction: making Azure AI services feel like native .NET infrastructure rather than bolted-on REST clients.

Practical Takeaways for Engineers

Area	What to do
DI integration	Upgrade Azure SDK packages; refactor manual `AddSingleton` client wiring to `AddAzureClients`
Content Understanding	Add `Azure.AI.ContentUnderstanding --prerelease`; evaluate against your Doc Intelligence workflows
`azd` in CI/CD or AI agents	Upgrade to `azd` 1.23.x; use `--query` for JSON filtering in scripting
Agent development	New apps → Microsoft Agent Framework; existing Semantic Kernel apps → plan migration path
Authentication	Always prefer `DefaultAzureCredential`; the new cert-rotation support is bonus hardening

Azure SDK February 2026 Ships: Native DI, Content Understanding, and azd That Knows When an AI Is Driving