Azure Functions

The official account of the Azure Functions product team ⚡️
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[Azure Functions @AzureFunctions]

@LearnerBR The GA timeline is still being determined. Your feedback will help us identify what’s needed to reach GA!

[Azure Functions @AzureFunctions]

See how to build, run, and debug Azure Functions Hosted Skills directly in GitHub Copilot with the Hosted Skills Canvas ⚡️

https://t.co/eCARGVXNdJ

#AzureFunctions #GitHubCopilot

[Azure Functions @AzureFunctions]

@m365show Yes. Durable Functions persists the plan and workflow state. Retries re-run only the affected activity, and worker restarts resume unfinished work rather than rebuilding the plan or rerunning completed steps. Tools still need to be idempotent because activities are at-least-once.

[Azure Functions @AzureFunctions]

See how Dynamic Workflows in Azure Functions Hosted Skills turn AI-generated plans into durable execution ⚡️
https://t.co/l2OORm5qGW
#AzureFunctions #Serverless #AI

[Tamir Dresher @tamir_dresher]

Since joining the Durable Task team, I’ve noticed something interesting.
A lot of people stay away from some of the really good stuff because Durable orchestration feels a bit like magic.
And when something feels like magic, it’s hard to trust it.

So I wanted to peel back one small part of that magic and show what actually happens when an orchestration hits await?

The answer is not simply “the function pauses and continues later.”

I wrote a deep dive into replay, activity completion, IsReplaying, and what Durable Task actually persists under the hood.
https://t.co/Jz143pGCyf

#DTS @AzureFunctions

[Azure Functions @AzureFunctions]

Connect Azure Functions to more services with Managed Connectors 🚀
Get access to 1.7k integrations including Microsoft 365, Teams, SharePoint, Dataverse, etc. with less integration code!
Check out this demo and see how to use connectors in Functions 👉 https://t.co/ssvS3Zz5cr

[Azure Functions @AzureFunctions]

Manvir Kaur joins @shanselman on #AzureFriday to show off Managed Connectors in #AzureFunctions: 200+ triggers and 1,400+ actions, now with the power of code and Functions scale. Emails, Teams, Dataverse and more. 🚀

📹 https://t.co/t5mGZFcfoK

#Connectors #Azure #Serverless

[Azure Functions @AzureFunctions]

TLS/SSL certificates and end-to-end TLS encryption are now generally available on Azure Functions Flex Consumption ⚡️

Docs: https://t.co/fZ62IW7MwK
Azure update https://t.co/8ezu2LbsVk

#AzureFunctions

[Azure Functions @AzureFunctions]

See how to build an event-driven expense processor using the Azure Functions Serverless Agents Runtime
🎥 https://t.co/QeMjpm6HtC
Sample: https://t.co/mGHWKUZjFf: https://t.co/wwTGZfmiOj
#AzureFunctions #ServerlessAgents #AI

[Azure Functions @AzureFunctions]

Learn how Paul created an M365 Inbox agent using Azure Functions' serverless agents runtime and how you can too ⬇️

[Paul Yuknewicz @paulyuki99]

I put together a practical sample for a thing I keep wanting as a builder:

an agent that automates my Microsoft 365 workflow, but lives in a repo, debugs locally, deploys with IaC, and runs serverlessly.

The sample is an M365 Inbox Agent on Azure Functions' Serverless Agents feature:

- urgent VIP mail -> Teams (triggered on new emails)
- action-required mail -> grounded draft replies
- daily briefing -> inbox (triggered every morning)
- rules -> markdown
- guardrails -> code, python
- auth -> Entra / managed identity
- deployment -> azd + Bicep
- local dev -> sample inbox data + dry run

This is for the custom edge cases a power user and builder hits, connected to many more systems and data sources.

These are YOUR Frontier Agents, for the last-mile stuff every team has:

- "Keep it in a repo so I can review changes"
- "Let me debug the thing before it touches real mail"
- "Reach an internal API or database that isn't in any connector catalog"
- "Pin my own model, prompt, and dependency versions, and roll back a bad one"
- "Run in my own Azure subscription with my own networking, billing, and managed identity"

And because the serverless agent includes Markdown plus real code, it can run tools and enforce things the model cannot talk its way around:

- a hard never-send guardrail: code checks the recipient against an allowlist before any send, so "never email outside my org without approval" is enforced in code, not hoped for in a prompt
- a sandboxed code interpreter: the agent writes a small Python snippet to crunch a messy attachment or reconcile a spreadsheet, runs it in an isolated sandbox, and feeds the exact result back instead of eyeballing numbers in the model

And it is your function. Serverless billing, high scale, no platform-imposed turn limits or connector throttling. You pay for what runs and you push whatever limits you want: fan out across thousands of messages, run long jobs, hold your own rate limits, scale to zero when the inbox is quiet. The ceiling is your Azure subscription, not someone else's agent quota.

That is where this pattern gets interesting.

The agent itself is markdown. The skills are markdown too. So the workflow stays readable:

- who counts as a VIP
- what should be skipped
- what escalates
- what gets summarized
- what gets a draft reply

Then Azure Functions gives it production shape:

- event trigger when mail arrives
- timer trigger for the daily briefing
- Application Insights traces
- serverless billing
- managed identity
- M365 connector actions and AUTH (unsung hero to this)
- private repo customization
- repeatable deploy

I like this because it gives you both ends:

1. markdown agents for the reasoning and policy
2. normal developer ergonomics for everything around them

Local mode is intentionally safe. You can run it against sample inbox JSON, see the exact Teams post or email reply it would produce, and call no connector at all.

When you are ready, wire the Outlook and Teams connectors and deploy.

The anchor version is mostly markdown on purpose, with a little Python where I wanted hard rails and code-based tools (not required, but useful). It keeps the story clean: readable agent policy, real M365 actions, Azure Functions production shape, and real code when you want a hard guardrail or a sandboxed computation.

My mental model:

>the out-of-box agents are the product experience; this sample is the builder path for the workflows only your team has.<

This m365 & Teams sample (try it!): https://t.co/xyv9roA3L9

Serverless agents runtime: https://t.co/2JGUaJhaNd

If you try it, I would love to hear the first workflow you customize.

[Azure Functions @AzureFunctions]

Building #Serverless #Agents on #AzureFunctions = writing a Markdown file.

YAML sets the trigger (timer, HTTP, Service Bus, email…), the body is the agent's instructions. No harness code - MAF handles it. Some examples:

@InfoQ's article covering it: https://t.co/gVIUfPlPaT

[Azure Functions @AzureFunctions]

The Azure Functions MCP extension has had a breakout year 🚀
From "tools only" → a full MCP platform:
✅ tools, resources, prompts
✅ MCP Apps (interactive UI)
✅ built-in auth + rich types
and more! Check out: https://t.co/KqNKUH1TQ7
#MSBuild

[Azure Functions @AzureFunctions]

Azure Functions at Build 2026: serverless agents in a .agent.md file, 1,400+ M365 and SaaS connectors as triggers, Go as a first-class language, full MCP support, new CLI, On-demand Sandboxes for DTS and much more!
https://t.co/1J4QZuZZUL

[Azure Functions @AzureFunctions]

Functions MCP extension now supports prompts⚡️
-User-invoked, parameterized workflows
-Simple fn-based implementation
https://t.co/LLZsfBnDJb

With full MCP coverage- tools, resources, prompts, unlock more complete &amp; flexible dev experience building w/ Functions🚀#MCP #AgenticAI

[Azure Functions @AzureFunctions]

⚡️Learn how Azure Functions uses AI to speed up RCA and mitigation without losing accuracy! https://t.co/Dd6AMEqibh

[Azure Functions @AzureFunctions]

Java 25 is now GA on Azure Functions 🚀🎉
Start building with the latest Java runtime today!
Try it out -&gt; https://t.co/8f8wb6mh24

#AzureFunctions #Java

[Azure Functions @AzureFunctions]

📌MCP Apps let tools return interactive UIs (dashboards, forms, etc.) not just text in AI clients
📌That means true app-like experiences built into AI conversations.

Build and deploy MCP Apps at scale with Azure Functions 🚀 https://t.co/oHyCGMHVr2

[Azure Functions @AzureFunctions]

Azure Functions Durable Task Scheduler is now GA and Consumption in Public Preview. A high-performance, reliable, and scalable backend for Durable Functions or apps leveraging the Durable Task SDKs. Learn more here: https://t.co/w2JmqRPEHs

[Azure Functions @AzureFunctions]

🚀The Azure Functions MCP extension is now GA, making it easier than ever to host remote MCP servers. And now you can also host MCP SDK–based servers on Functions. If you've already built these servers, just deploy as-is. Serverless, secured, and flexible. https://t.co/LyYJe15T5o

[Azure Functions @AzureFunctions]

Huge Azure Functions drop at #Ignite2025: https://t.co/Q5eQQIWP6j #Azure #Serverless #AzureFunctions