Azure Functions

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Azure Functions

Azure Functions

@AzureFunctions

The official account of the Azure Functions product team ⚡️ YouTube: https://t.co/e0BelnsOyN GitHub: https://t.co/ttMazZg3mu

Redmond, WA Katılım Mart 2016
508 Takip Edilen40.7K Takipçiler
Azure Functions
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!): github.com/Azure-Samples/… Serverless agents runtime: learn.microsoft.com/en-us/azure/az… If you try it, I would love to hear the first workflow you customize.

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Azure Functions
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: aka.ms/functions-mcp-… #MSBuild
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Azure Functions
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! techcommunity.microsoft.com/blog/appsonazu…
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Azure Functions
Azure Functions@AzureFunctions·
Functions MCP extension now supports prompts⚡️ -User-invoked, parameterized workflows -Simple fn-based implementation aka.ms/func-mcp-promp… With full MCP coverage- tools, resources, prompts, unlock more complete & flexible dev experience building w/ Functions🚀#MCP #AgenticAI
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Azure Functions
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 🚀 aka.ms/functions-mcp-…
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Azure Functions
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: aka.ms/dts-ga-blog
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Azure Functions
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. techcommunity.microsoft.com/blog/appsonazu…
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Azure Functions
Azure Functions@AzureFunctions·
🚀 Early preview: Bring-Your-Own Remote MCP Server on Azure Functions! Keep your existing Python/Node/.NET MCP code and just host remotely on Flex Consumption plan w/ bursty, event-driven scaling, built-in security & serverless pricing. Try it now! aka.ms/BYO-remote-mcp #MCP
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Azure Functions
Azure Functions@AzureFunctions·
@bzbetty We plan to enable the new linux-based Flex Consumption plan there within the next couple of months.
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Azure Functions
Azure Functions@AzureFunctions·
@bzbetty Sorry for the confusion, agreed that is not straight forward - the Linux Consumption line to look at there is "Consumption Plan Linux" which doesn't show for New Zealand North. "Consumption Plan" is the Windows version - we will investigate how to add Windows there to clear it up
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Azure Functions
Azure Functions@AzureFunctions·
Following the guide gives you full control with each step, but automation options will also be made available in the next year 🔧
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Azure Functions
Azure Functions@AzureFunctions·
The expansion you were waiting for is finally here 🌍 - Azure Functions Flex Consumption is now enabled and generally available in West Europe and many other regions! 🚀 az functionapp list-flexconsumption-locations --query "sort_by(@, &name)[].{Region:name}" -o table
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Azure Functions
Azure Functions@AzureFunctions·
@KirkMarple @lilyyym1 We purposely did not document the vCPU for the different memory sizes as they are subject to change (usually for the better). But you can think of the 2GB instance size as having one vCPU and roughly proportional up and down from there.
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Kirk Marple
Kirk Marple@KirkMarple·
@lilyyym1 @AzureFunctions Great stuff! Not totally clear from the docs - what are the vCPU available in Flex Consumption plan? Does it scale with instance memory?
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