Azure OpenAI Realtime API Is Now GA — What .NET and Azure Engineers Need to Change Before April 30

TL;DR

Azure OpenAI’s Realtime API has moved from Preview to General Availability (GA), with the Preview protocol deprecated on April 30, 2026. If you’re building voice, audio, or low‑latency streaming experiences on Azure (especially from .NET), you need to update SDK versions, endpoint formats, and a few protocol details. The good news: most migrations take under an hour, and core behavior stays the same.

The news, narrowly focused

As of late March 2026, Microsoft has officially promoted the Azure OpenAI GPT Realtime API to GA and published a concrete migration guide for teams currently using the Preview version. The Preview protocol will stop working after April 30, 2026, so this is not a “when we get around to it” change. It’s a calendar event. (learn.microsoft.com)

This matters most to engineers building:

Voice assistants
Live transcription or translation
Real‑time copilots embedded in apps
Audio‑driven agents using WebSocket or WebRTC

In other words: latency-sensitive workloads where REST just won’t cut it.

What actually changed (and what didn’t)

Let’s separate signal from noise.

✅ What did not change

Model capabilities and audio formats
Core real‑time semantics (events, streaming, partial responses)
Overall architecture (client ↔ Realtime endpoint over WebSocket or WebRTC)

If your app logic works today, it will still work after migration.

⚠️ What did change

Microsoft cleaned up several Preview-era inconsistencies:

Endpoint URL format
- GA uses a standardized endpoint shape aligned with Azure AI Foundry conventions.
Event names
- Some event identifiers were renamed for consistency.
Session configuration schema
- Minor restructuring (mostly mechanical updates).
SDK requirements
- You must use a GA-compatible SDK and API version.

These changes are documented step by step in the official migration guide. (learn.microsoft.com)

.NET-specific impact

For .NET engineers, the biggest win is that this migration aligns cleanly with the Azure.AI.OpenAI client direction.

If you’re already on recent prerelease packages, you’re close. If not, expect to:

dotnet add package Azure.AI.OpenAI
dotnet add package Azure.Identity

And authenticate using Microsoft Entra ID instead of API keys (strongly recommended for production):

var client = new AzureOpenAIClient(
    new Uri(endpoint),
    new DefaultAzureCredential());

var realtimeClient = client.GetRealtimeClient("my-realtime-deployment");

This authentication and client pattern is now consistent across Azure OpenAI, Foundry models, and other Azure AI services, reducing mental overhead (and copy‑pasted auth code). (learn.microsoft.com)

Latency, cost, and operational considerations

Latency

GA does not introduce extra latency. In fact, Microsoft explicitly states that low‑latency behavior is preserved from Preview. If you see higher latency after migrating, it’s almost certainly a client-side regression (usually event handling). (learn.microsoft.com)

Cost

Pricing does not change as part of GA. Realtime models remain billed under Azure OpenAI’s existing pricing structure. However, GA typically signals that capacity limits and SLA expectations are stabilizing, which is good news for production workloads. (learn.microsoft.com)

Operations

Preview API traffic after April 30 will fail hard.
Blue/green deployment is recommended: migrate in a staging slot, validate audio round‑trips, then swap.
Abstract your endpoint and deployment names; future model retirements are still a thing (ask anyone who lived through GPT‑4.1). (learn.microsoft.com)

How long will this take?

Microsoft estimates 30–60 minutes for most migrations. That matches reality if:

Your app already uses supported SDKs
You haven’t hard‑coded event names everywhere (you know who you are)

Plan more time if you wrote a custom client or protocol wrapper during Preview.

Why this matters strategically

GA status is Microsoft’s way of saying: “You can bet a production system on this now.” It also means:

Better long-term compatibility with Azure AI Foundry
Fewer breaking changes going forward
Clearer lifecycle guarantees (Preview → GA → Deprecated → Retired)

If real‑time AI is part of your product roadmap in 2026, this is the API you should standardize on.