• 8 Windows Server VMs, 100% in Azure, no on-prem servers
• Currently PAYG, planning to switch to Azure Hybrid Benefit using our own qualified Windows Server licenses (36-month term)
• Roles: Domain Controller, SQL Server, file server, app server
• Employees access apps on the app servers via browser from local Windows PCs — not RDS/Terminal Services
• RDP used only by admins
• Local sites connect to Azure via site-to-site VPN, so local users/devices reach these servers over that link

Our MSP says that once we bring our own licenses under AHB, we’ll need Windows Server User/Device CALs because local clients are accessing the servers.

Is that actually correct? My read of Microsoft’s guidance is that Windows Server on Azure under AHB doesn’t require base CALs for access, full stop regardless of where the clients sit. Am I missing something?

I finally got the email from my company saying my Azure Subscription which was a part of the VS Enterprise Subscription is going to be deleted as MS has retired those benefits.
It was a great playground and experimental sandbox for me to learn new concept or even test weird scenarios without affecting any company resource. I guess all good things comes to an end. I no longer have any reason to recommend VS Subscription anymore for my team.

I will keep it short - No Drama.

1. Login Azure portal - Signin logs - set "filters - Local time" "Last 7 days" - review the logs - close it. i want to search review signIN logs again . Whytf i need to re-apply same filter again n again.

2. Why we don't have Conditional access policy - "creator name" , "Last modified by" "last 24 hr trigger events" attribute on policy

The night before last one of our VMs migrated to a different host at Azure. Azure provides no notifications of host migrations because they consider them not too be disruptive. This host migration paused all of the hardware, including the accelerated NIC for approximately 1 minute. This caused a cascading failure in our replicated DB setup which has been an absolute nightmare to recover from.

The support ticket was opened with Severity B. This is because we were not hard down at the time. The description for Severity B is:

Customer’s business has moderate loss or degradation of services but work can reasonably continue in an impaired manner.

The SLA for a Standard support plan for the initial response is less than 4 hours. It has been almost 25 hours and the only response we have received is an AI generated one with some troubleshooting steps that it thinks might be useful. They of course were not useful and I need to talk to a live person.

Do AI generated responses meet their less than 4 hours SLA?
When I opened the support ticket I selected that I am available 24/7 and would like to be contacted by phone. I have had no calls from Azure at all and not one update to the ticket other than the useless AI response.

I used to think Azure support was bad a couple of years ago but it seems to be getting even worse.

We have been spending between $40 and $70K per month at Azure and they are going to lose us completely as a customer. Since the Front Door outage a year ago it's been a series of ongoing events and issues for us that Azure support really don't give a shit about. Their response times are getting worse and the quality of their responses are also getting worse. We made the decision a short while ago this morning to migrate all of our Azure resources to AWS. We have a much better relationship with them and they have not failed us like Azure does.

I need a place to store all my on demand and ambient (always on) group rbac role assignments user for human identities. I'm unsure if I should create these at the tenant root group or one level below that. which in my case is the company name.

Best practice seems to suggest not doing anything at the tenant root group, but then that means certain admin users can't access tenant root group as they are provisioned role assignments in tenant-root-group/<companyname>

Hi,

We're remediating a legacy environment (everything in Azure Subscription 1, 300-ish resources, click ops) with Azure Landing Zones and IaC.

We've already deployed the ALZ accelerator, but we're essentially blocked from going ahead with migrating things into separate subscriptions because of the limit.

I raised a support ticket and they increased our limit from 5 to 10, which is very unhelpful. I explained what we're trying do, but they keep saying I need a business justification even though I've explained we're following their best practices.

Any ideas?

Anyone else experiencing issues?
We started noticing at two seperate customers at the moment.

Getting the following error code straight after performing mfa.

Hi folks, analyst by trade, not a DBA or high level SQL users so please be gentle!

I've been given access to our Azure usage logs, in an Azure table and I want to use it, to see the volumes of queries being executed by db (each customer has their own db on the server) and importantly, what objects, they are querying so that we know our heavy use objects by customer etc. Literally any input from others that have been down this road would be welcomed... We're kicking out about 500,000 log rows/day and I'm looking to potentially extract monthly or fortnightly for the previous month or fortnight so scale may be an issue.

1. I've been able to recompile the statements where they split to multiple log rows due to statement length being >4,000 characters, using a simple STRING_AGG. This gives me back, my full user executed statement (allbeit wrapped in SQL's view of the statement with aliasses everywhere etc).

2. I want to know, understand from this fully recompiled statement, what objects, my users are querying. I can't utilise just a '[X].[Y]' format string given the aliassing that SQL does in the back-end (as it adds an auto generated alias to every field). I do however have a list of 8,500 tables that are our customer facing objects as a reference list. Ideally I'd like to generate a field that concatenates all of the objects identified in my recompiled statement, that exist in this 8,500 row reference list.

Any guidance, signposting or help that anyone could offer would be superb. For a company using Azure with customers, I feel that this is the REAL intelligence that we need to understand how customers are using the product. Just struggling with getting it up and running given the scale etc and wondering how others have approached... Apologies if being a thicko, but here to be educated too!

TIA

I’m building a payroll AI agent as a portfolio project and would appreciate your conceptual feedback.

Please look at the architecture diagram included in the GitHub repository and let me know if any component, connection or data flow is incorrect or missing.

The project uses:

• Streamlit as the user interface.
• Microsoft Foundry to host the agent with gpt-5-mini.
• Python tools to analyze structured payroll CSV files.
• Azure Blob Storage, Azure AI Services and Azure AI Search to process and retrieve information from unstructured legal documents through RAG.
• azure.yaml and Azure Developer CLI (azd) to configure and deploy the project.

I would particularly like to know whether the separation between structured-data tools and RAG retrieval is conceptually correct.

Diagram context

• payroll_data: Structured CSV payroll records with columns such as department, pay grade, base salary, gross pay and overtime pay.
• payroll_document: Unstructured legal and regulatory documents concerning payroll, FLSA guidance and overtime rules.
• Python modules: Agent tools, workflows, validation logic, memory and middleware.

Architecture diagram, source code and project details:
https://github.com/RicardoCasado/payroll-agent-ai-search

DFS Namespace with root-consolidation works a treat for on-premises file server migrations moving to Azure Files or similar. DFS Namespace in a failover cluster environment adds the extra level of redundancy and availability. What if we have cloud-native environments or want to move this off traditional on-premises environments to Azure? do we just build the same environment on IaaS or can we trim down and build better?

Just completed 1 project using azure AI.

Its called service retirement. It will just send mail every month to the SMEs that which service will retire, what will be the impact what action need to be taken.

If anyone doing any other Azure AI projects please comment!!

Hey all,

I work at a consultancy company, and I've just been asked to run a one-day Azure course for this year's new trainees. I found out fairly last minute — the course is next week — so I'm scrambling a bit to put together solid content.

Audience: The trainees should have covered cloud concepts in school, but most have little to no hands-on experience with Azure (or cloud platforms in general).

Format: One day, roughly 6 hours, so time management is going to be critical.

I'd love this community's input on:

• Overall approach — how would you structure a one-day intro course like this?
• Course material — any good sources you'd recommend (Microsoft Learn, YouTube series, specific books/courses)?
• Topics — what's essential to cover vs. what can be skipped for a first exposure?
• Demos/POCs — what would you actually show live to make concepts click?
• Exercises — any hands-on labs that work well for beginners in a limited timeframe?

Any tips, resource links, or "wish someone told me this before my first course" advice are much appreciated. Thanks in advance!

Hey all — wanted to share something I built rather than pretend to be a random user, since that's not fair to this sub.

I'm Thiago, an MCT, and I built Azurecertified.com — a practice exam platform for AZ-900/104/204/305. It's not a d7mp (I don't think d7mp are a real path to passing), it's questions built to cover the actual exam objectives. AZ-104 is $14.90.

Not trying to spam the sub — genuinely just think it could help some of you studying for AZ-104. Happy to answer questions about the exam or the platform either way.

🚨As organizations build more AI powered applications, choosing the right model for every request becomes increasingly important. Not every prompt requires a large and expensive reasoning model, while more complex workloads often benefit from advanced models with higher capabilities. Microsoft Foundry Model Router addresses this challenge by automatically selecting the most appropriate model for each request based on factors such as complexity, quality requirements, latency, and cost. In this blog, we will deploy Microsoft Foundry Model Router using Bicep and explore how Infrastructure as Code can simplify the deployment and management of intelligent AI routing workloads on Azure. https://medium.com/microsoft/deploy-and-use-the-foundry-model-router-using-azure-bicep-0339eddaaffa

With Azure Linux 4.0 Microsoft ❤️ Linux even more! In this video I look at what's new and where we can use it.

https://youtu.be/_9C1d4PZ2Lc

ALSO don't forget today's AMA at 10:00 AM PST, hope to see you there - https://youtube.com/live/hXRPm7r4Q14?feature=share

00:00 - Introduction

00:12 - History

02:42 - Why Azure Linux?

05:28 - Architecture

08:24 - Where can be used

09:01 - Lifecycle

09:19 - Looking at Azure Linux

11:41 - Using with WSL

13:10 - Azure Container Host

16:03 - Summary

16:40 - Close

a bit new to azure and all the different components and services. I have extensive experience with on prep services/devices etc. Typically we would name objects/resources based on their location, type (physical vs virtual) and role.

Can you recommend or give insight into how you are naming your Azure resources for clarity and documentation?

A few months have passed since Global Azure 2026, but we finally have the chance to share the official recap video of our event in Veneto, Italy! 🇮🇹

It was an amazing day: hundreds of attendees, dozens of speakers and sessions, multiple tracks, and most importantly, a great community of people passionate about Microsoft Azure and cloud technologies.

A huge thank you to all the speakers who shared their knowledge and experience, to our sponsors and partners who made the event possible, and of course to everyone who joined us and helped create such a great atmosphere.

🎬 Here’s the recap video:
https://www.youtube.com/watch?v=u5_Dh7zu2MQ

We’re already working on the next edition of Global Azure Veneto.

Hope to see some of you there in 2027! ☁️💙

— Azure Meetup Veneto

Okay so MS has a reference implementation in Learn about container app jobs -based agents that scale on demand at https://learn.microsoft.com/en-us/azure/container-apps/tutorial-ci-cd-runners-jobs?tabs=bash&pivots=container-apps-jobs-self-hosted-ci-cd-azure-pipelines#create-a-self-hosted-agent-as-an-event-driven-job

Whenever the agent pool has (devops)jobs in queue, KEDA azure-pipelines scaler will scale (containerapp)jobs up in hopes that those will reduce queue count.

Now imagine the container job not doing anything to the job due to networking, auth or borken container image issues. What happens is, the scaler will just see queue being > 0 in 15sec and do the same thing again ad infinitum. I don't think there is a way to configure some sort of a a cooldown or retry limit for the scaler.

This obv can result to problems, but is not a "bug". Do you know any ways to configure the scaler, devops or container app to stop trying in cases like this?

We are a ZIA/ZPA shop, roughly 4,000 seats, renewal in about seven months. Not shopping for the sake of it, but the AI requirements landed after our last contract and I want to know whether we are better off expanding here or looking at Cato.

Where we are with Zscaler on the AI side: SSL inspection is solid, the AI app category exists, DLP works about as well as our policies deserve. What I am less clear on is inline prompt-level control versus app-level allow/block, and how much of the newer AI functionality is included versus a separate SKU.

The Cato pitch we got leaned heavily on single-pass processing and one policy engine covering network, security, and AI, plus their inline inspection story. Sounded clean in the demo. Skeptical of demos.

Asking here specifically because I want the incumbent perspective: if you have added AI controls on top of an existing ZIA deployment, was it configuration or a new purchase; how has inspection performance held up on streaming LLM responses; has anyone actually evaluated Cato head to head and stayed, and what kept you; and for anyone who left, what was the deciding factor?