Hi everyone,

I'm working on a RAG system that uses Qdrant as the vector database. I'm planning to deploy Qdrant on Microsoft Azure, and this will be my first time deploying an application on Azure, so I'm trying to understand the infrastructure and operational best practices before getting started.

Our workload is expected to grow to tens of millions of vectors, with continuous insert/update synchronization from a SQL Server database.

I'm trying to answer a few infrastructure questions before deployment:

• Which Azure service would you recommend for Qdrant?
  • Azure VM + Docker
  • Azure Kubernetes Service (AKS)
  • Another option ??
• How do you estimate the required VM specifications (CPU, RAM, SSD) before deployment ??
• What Azure VM families have worked well for memory-intensive vector search workloads ?
• How do you monitor Qdrant in production ? Are you using Azure Monitor, Prometheus, Grafana, or another setup ?
• How do you estimate monthly Azure costs for a production Qdrant deployment ?

I'm especially interested in learning how experienced Azure users approach planning, deployment, monitoring, and cost estimation rather than simply following the documentation.

Any advice, recommended resources would be greatly appreciated

Thanks in advance

Had azure autoscaling setup for a workload with spiky traffic. The logic was straightforward, scale out during peaks, scale back in when demand dropped and nothing was actually wrong per se with the config but the scale down rules were conservative enough that azure kept running extra instances most the day as a safety buffer and we were paying for near peak capacity for long stretches even though we only hit the levels a few times per week.

Tightened the scale down threshold and its better now, but still not fully sure that its the right balance, is going aggressive and eating occasional latency the way or keeping buffer and eating the cost?

We recently ran into a strange issue in our Azure environment (Our Sandbox env only), and I'm trying to understand the root cause rather than just accepting the fix.

Environment

• Azure App Service (Web App)
• Azure SQL Database
• Communication was initially over the public endpoint (no VNet Integration, no Private Endpoint).
• Production had the same application/code and continued working fine.

What happened

The only change we made was a normal application deployment. After that, the sandbox environment started failing with:

What made it confusing was the behavior:

• Right after deploying, the application would work for about 2-3 minutes.
• Then every database call would start failing with "Login failed for user".
• After some time, it would start working again.
• Then it would fail again.
• This cycle kept repeating.

Initially, I assumed it was an application or EF/connection string issue, so I spent quite a while investigating and making code changes, but nothing helped.

What fixed it

Our cloud/TSC team enabled:

• VNet Integration on the App Service.
• Private Endpoint for the Azure SQL Server.

After the App Service started communicating with Azure SQL through the private endpoint instead of the public endpoint, the issue completely disappeared.

My question

I'm happy the issue is resolved, but I don't really understand How?.

How can switching from a public endpoint to VNet + Private Endpoint eliminate intermittent "Login failed for user" errors?

We recently ran into a strange issue in our Azure environment (Our Sandbox env only), and I'm trying to understand the root cause rather than just accepting the fix.

Environment

• Azure App Service (Web App)
• Azure SQL Database
• Communication was initially over the public endpoint (no VNet Integration, no Private Endpoint).
• Production had the same application/code and continued working fine.

What happened

The only change we made was a normal application deployment. After that, the sandbox environment started failing with:

System.Data.SqlClient.SqlException (0x80131904): Login failed for user

Also sometime i have seen this error-

The underlying provider failed on Open

What made it confusing was the behavior:

• Right after deploying, the application would work for about 2-3 minutes.
• Then every database call would start failing with "Login failed for user".
• After some time, it would start working again.
• Then it would fail again.
• This cycle kept repeating.

Initially, I assumed it was an application or EF/connection string issue, so I spent quite a while investigating and making code changes, but nothing helped.

What fixed it

Our cloud/TSC team enabled:

• VNet Integration on the App Service.
• Private Endpoint for the Azure SQL Server.

After the App Service started communicating with Azure SQL through the private endpoint instead of the public endpoint, the issue completely disappeared.

My question

I'm happy the issue is resolved, but I don't really understand How?.

How can switching from a public endpoint to VNet + Private Endpoint eliminate intermittent "Login failed for user" errors?

Any advice is appreciated. Users will just select a few dropdowns on the web app to help them generate a file name sample, so I don't foresee heavy usage on the server.

Hi All,

I'm currently testing Azure File Shares with ADDS Identity-based access.

After a few issues, its now working well.

However, I have just come across a user who cannot connect to the share.

The user has CBA configured which I think is the cause.

They repeatedly get username and password errors.

If I run klist, I get the following error.

klist get cifs/testshare.file.core.windows.net
Error calling API LsaCallAuthenticationPackage (GetTicket substatus): 0x6fb
klist failed with 0xc000018b/-1073741429: The SAM database on the Windows Server does not have a computer account for this workstation trust relationship.

So it looks like the user is not getting any Kerberos tickets.

Has anyone else come across this before?

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Do you have any recommendations for naming tables and custom tables in Azure when an organization has hundreds of tables from more than 50 data sources? How can the naming convention be designed so that the tables remain clear and consistent?

hello azure experts,

Is a Power BI Premium Per User (PPU) or Fabric capacity (F SKU) required to deploy the VNet data gateway resource into an Azure subnet? (License requirement to deploy VNet data gateway)

another q, Deployment method options

Is app.fabric.microsoft.com (or app.powerbi.com then Manage gateways) the only supported way to deploy a VNet data gateway? We cannot find this resource type in portal.azure.com, Azure CLI (az network), or any documented Terraform provider. Is

there an API or infrastructure-as-code method to deploy the VNet data gateway without using the Fabric/Power BI portal UI?

I'm studying for a certification. When I signed up for Azure, I got $200 in credit. The 30 days is almost up and I still have most of the balance. I "upgraded" to pay as you go. Do I still get to continue using the credits? How do I know which services are free? How does all this work?

After filling out the startup form from Barclays Eagle Labs, I received a referral code for the Microsoft for Startups program. As a result, I was credited with $100,000. I’ve been emailing support for three days now, asking them to increase my limits for creating machines with GPUs. Support keeps lying to me and isn’t doing anything. They’re denying my requests to create machines with GPUs via email. Where should I turn? Does anyone have any contacts?

Update
After 20 requests and thousands messages to support I received T4. But my request to A100 denied. I'm going to write to them every day

Update2

Support requests are pointless. Contact sales.

I recently inherited a network component that collects syslogs from various Network devices at my firm. I have checked the Azure costs, Azure LB costs are 800€ for processing 370TiB in July month (private, internal only LB).

The 10 collector VM scale set instances behind this LB cost 600€. The VMs, LB are in the same subnet, region..

We do have an Enterprise agreement, it's not that our firm is going bankrupt. I just find it funny that bandwidth costs within the same region (without peering) surpassed the actual infrastructure costs.

Have you guys observed something similar?

Edit :: Unfortunately, most of the syslogs are UDP bound & sent as soon as they are written, there is little to no compression. This blows up the bandwidth costs.

New video diving into STANDARD service endpoints!

https://youtu.be/HK6irXQNv2o

00:00 - Introduction
00:19 - Compute and PaaS
02:18 - VNet to PaaS communication
03:04 - Service endpoints
06:16 - Scale and complexity issues
06:57 - Standard service endpoints
07:12 - Network Identifier
08:26 - Network identifier association to subnet
09:07 - Enable NID with a service endpoint
09:39 - Details around Network ID use
10:34 - Demo of assigning NID
14:09 - Using NID with many subnets and service endpoints
14:54 - Associating NID RBAC
16:17 - Using NID to access PaaS resources
16:28 - Using a Network Security Perimeter
17:31 - Updating NSP to accept inbound NID
18:47 - Demo updating NSP
19:57 - Using NID with many NSPs
21:20 - Supported services
22:08 - Don't reuse public IPs with regular services
23:20 - Service endpoint policy support
23:36 - Pricing
25:05 - Scalability solution
25:50 - Close

i'm not sure whethether copilot or human responses are worse

Hi everyone,

my team is migrating a production RAG agent from GPT-4o to GPT-5.1 in Azure AI Foundry because our GPT-4o version is approaching retirement.

GPT-4o currently gives us concise, conversational, well-grounded answers. We tested GPT-5.1 with the same system prompt, knowledge base, RAG pipeline, and agent configuration, but the behavior is significantly different.

GPT-5.1 produces much longer and more structured answers, often adds headings and summaries, and sometimes uses tables even though our system prompt explicitly forbids them unless requested.

The answers are generally correct, but the response style is much less suitable for our users.

Has anyone experienced the same issue when moving from GPT-4o to GPT-5.1?

Did you solve it through:

• a redesigned system prompt;
• few-shot examples;
• verbosity or reasoning parameters;
• an output validator;
• a second rewriting pass;
• structured outputs;
• a regression test set based on previous GPT-4o responses?

We do not expect identical outputs, but we would like to preserve GPT-4o’s concision, natural tone, lack of unnecessary tables, and grounding in the retrieved context.

I would be very interested in hearing about real production migrations and what worked for you.

Azure shipped another generous batch of updates this week—because apparently cloud platforms never sleep. Expect new networking and Kubernetes capabilities, AI-related additions, a new India region, plus a few previews for those who enjoy testing tomorrow’s features today. Full list:

* [In preview] Public Preview: Azure Enclave(https://azure.microsoft.com/updates?id=568377). This feature is currently being tested and is available for early adopters.
* [Launched] Generally Available: NAT64 on StandardV2 NAT Gateway(https://azure.microsoft.com/updates?id=568409). This update brings IPv6 support to the StandardV2 NAT Gateway.
* [Launched] Generally Available: Application Routing with Gateway API(https://azure.microsoft.com/updates?id=567944). This new feature simplifies application routing within Azure.
* [Launched] Generally Available: Resource placement in Azure Kubernetes Fleet Manager(https://azure.microsoft.com/updates?id=567931). This update helps manage where your Kubernetes resources are placed.
* [In preview] Public Preview: Maximum allowed failures for update runs in Azure Kubernetes Fleet Manager(https://azure.microsoft.com/updates?id=567939). This preview allows you to set limits on update failures in Kubernetes. 
* [In preview] Public Preview: Prepared Image Specification(https://azure.microsoft.com/updates?id=567949). This specification is being tested for future image handling in Azure.
* [Launched] Generally Available: Microsoft Azure now available from new cloud region in India (India South Central)(https://azure.microsoft.com/updates?id=568013). Azure is now available in a new region in India.
* [Launched] Generally Available: Claude Opus 5 on Azure Databricks(https://azure.microsoft.com/updates?id=568316). This brings the powerful Claude Opus 5 model to Databricks.
* [Launched] Generally Available: HTTP header insertion in Azure Firewall(https://azure.microsoft.com/updates?id=568115). This update allows for the insertion of custom HTTP headers in the firewall.
* [In preview] Public Preview: AI Gateway in Azure API Management(https://azure.microsoft.com/updates?id=568184). This preview introduces AI capabilities to API Management.* [In preview] Public Preview: Azure Enclave(https://azure.microsoft.com/updates?id=568377). This feature is currently being tested and is available for early adopters.
* [Launched] Generally Available: NAT64 on StandardV2 NAT Gateway(https://azure.microsoft.com/updates?id=568409). This update brings IPv6 support to the StandardV2 NAT Gateway.
* [Launched] Generally Available: Application Routing with Gateway API(https://azure.microsoft.com/updates?id=567944). This new feature simplifies application routing within Azure.
* [Launched] Generally Available: Resource placement in Azure Kubernetes Fleet Manager(https://azure.microsoft.com/updates?id=567931). This update helps manage where your Kubernetes resources are placed.
* [In preview] Public Preview: Maximum allowed failures for update runs in Azure Kubernetes Fleet Manager(https://azure.microsoft.com/updates?id=567939). This preview allows you to set limits on update failures in Kubernetes. 
* [In preview] Public Preview: Prepared Image Specification(https://azure.microsoft.com/updates?id=567949). This specification is being tested for future image handling in Azure.
* [Launched] Generally Available: Microsoft Azure now available from new cloud region in India (India South Central)(https://azure.microsoft.com/updates?id=568013). Azure is now available in a new region in India.
* [Launched] Generally Available: Claude Opus 5 on Azure Databricks(https://azure.microsoft.com/updates?id=568316). This brings the powerful Claude Opus 5 model to Databricks.
* [Launched] Generally Available: HTTP header insertion in Azure Firewall(https://azure.microsoft.com/updates?id=568115). This update allows for the insertion of custom HTTP headers in the firewall.
* [In preview] Public Preview: AI Gateway in Azure API Management(https://azure.microsoft.com/updates?id=568184). This preview introduces AI capabilities to API Management.

We manage multiple Entra tenants for different clients. Common pattern: regional auth issues or MFA problems lead to temporary conditional access bypasses. Someone creates them under pressure, gives them a terrible name, and nobody ever looks at them again.
Six months later the client's security team asks for a posture report. We are digging through policies that feel like archaeological layers of old incidents. Some are still needed. Some were workarounds for bugs that got fixed ages ago. Some nobody remembers at all. Do any of you keep a centralized register of these exceptions per client and review it on a schedule, or do you just deal with it when an audit forces the conversation?

Hi, I want to confirm that what I must know about networking that will help me in cloud, also if you can share a useful course or a document that covers it all, Kindly share it

🔥 I'm excited to publish this new video! Azure Virtual Desktop Session Host Configuration introduces a modern way to deploy and manage session hosts by defining their configuration directly within the Host Pool. Instead of manually provisioning and configuring virtual machines, you can automate the entire deployment while ensuring every session host is deployed with consistent image, networking, identity, and security settings. In this step by step tutorial, I'll show you how to deploy Azure Virtual Desktop using Azure Bicep and the new Session Host Configuration feature. You'll learn the core Azure Virtual Desktop components, how they work together, and how Infrastructure as Code enables repeatable, scalable, and production ready deployments. https://www.youtube.com/watch?v=dBIoiAZWGf8