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Kerberos double hop delegation on SQL Linked Server fails on AG listener after RC4 disablement
Environment 3 Node- SQL Server 2022 with Availability Group Windows Server 2022 - Linked Server configured with Kerberos delegation (double-hop scenario) - RC4 encryption recently disabled via GPO The Problem After disabling RC4 in the domain (not sure of this root cause), Kerberos delegation through a Linked Server stopped working — but only when connecting via the **AG listener name**. Connecting via the **node name** works fine. I try to migrate my service account to gMSA and I've recreate all SPN and all delegation for the new account, but the issue is the same: Authentication works if the linked server us the node name, if it use the Listener AG name the connection fail with ------------------------------ Login failed for user 'NT AUTHORITY\ANONYMOUS LOGON'. (Microsoft SQL Server, Error: 18456) Connection Id 6d654295-0538-4837-b900-ff65c9e86ee9 at 2026-04-29 11:59:25Z I Confirmed via Kerberos event logging (Event ID 4769 on DC)** On a healthy request (node name), ticket encryption type is `0x12` (AES256). - Confirmed SPN registration with `setspn -L` - Verified Kerberos events on the DC (4768/4769) - Confirmed forwardable flag (`0x40000000`) is present in ticket options — delegation is active - Confirmed pre-auth and session encryption are both `0x12` (AES256) for the working path set `msDS-SupportedEncryptionTypes = AES128+AES256` on the SQL service account and resetting its password rotete kdc key Are there any additional steps needed on the Linked Server or constrained delegation configuration side after the service account change? Any guidance appreciated. Thanks.
How does GitHub Copilot in SSMS 22 handle database context collection before generating a response?
Hello, I am trying to better understand the internal workflow of GitHub Copilot in SSMS 22, especially for database-specific questions. From the product descriptions, it seems that Copilot can use the context of the currently connected database, such as schema, tables, columns, and possibly other metadata, when answering questions or generating T-SQL. However, I could not find clear official documentation about the actual sequence of operations. My main questions are: Before generating a response, does Copilot first collect database context/metadata from the active connection and then send that context to the LLM as grounding information? Or does it first use the LLM to interpret the user’s request, decide what information is needed, and then retrieve database metadata before generating the final answer? In some explanations, I have seen the phrase "Core SQL Copilot Infrastructure", but I cannot find any official documentation for that term. Is this an official component name? If so, what does it specifically refer to in the SSMS Copilot architecture? When Copilot answers schema-related or data-related questions, what information is retrieved automatically from the connected database, and is any SQL executed as part of that process? Is there any official architectural documentation that explains: context collection, prompt grounding, LLM invocation order, and whether query execution can occur before the final response is generated? I am asking because I want to understand the feature from both an architecture and data governance/security perspective. Any clarification from the product team or documentation links would be greatly appreciated. Thank you.Unable to install SQL Server 2022 Express (installer glitch + SSMS error)
Hi, I recently purchased a new Lenovo laptop, and I am trying to install Microsoft SQL Server 2022 Express along with SSMS. SSMS installed successfully, but SQL Server installation fails, and sometimes the installer UI glitches or does not load properly. Because of this, I am getting connection errors in SSMS like "server not found" and "error 40". I am not very familiar with technical troubleshooting. Can someone guide me step-by-step in a simple way to install SQL Server correctly? Thank you.
Migrate SQL 2016 to SQL 2022 - Detail Work Breadown Structre (WBS)
Hi, We’ve started a project to migrate from SQL Server 2016 to SQL Server 2022, and I’m currently preparing a detailed Work Breakdown Structure (WBS). Has anyone in this community gone through a similar migration and been willing to share their project WBS, either in .mpp or Excel format? Regards, Subhasish Roy
Best Practices for Connecting Internal SQL Server Financial Systems to Online Payment Platforms
I currently have an internal enterprise system used for purchasing, payments, and finance operations. The system runs on an on-premises database using Microsoft SQL Server and stores all financial transactions and internal workflow data. We now have a new requirement to enable online payment services for customers. These services will be exposed externally (likely in the cloud) and must interact with the same financial system so that transactions are reflected in our internal database. My main concerns are related to architecture, security, and data synchronization. Key points about the current setup: The core system and database are hosted internally (on-premises). The database contains sensitive finance and payment data. Internal processes depend on the current database structure and workflows. The new requirements: Develop an online payment service accessible over the internet. Ensure transactions from the online service update the internal system. Maintain data integrity and security. Avoid performance issues for the internal system. I’m evaluating a few possible approaches but I’m unsure which is best practice: Allow the cloud payment service to connect directly to the internal SQL Server database through secure networking. Maintain a replicated or read/write copy of the database in the cloud. Use SQL Server replication (transactional or snapshot) between on-prem and cloud. Introduce an API or middleware layer that handles all transactions and updates the internal database. Maintain separate databases and synchronize transactions asynchronously. My main questions: Is it recommended to expose the internal SQL Server database directly to cloud services? Should I use replication, a secondary database, or a service/API layer? What architecture pattern is commonly used for integrating on-prem financial systems with online payment platforms? How can we ensure consistency between internal transactions and online payments? Are there recommended SQL Server features or patterns for this scenario (replication, service broker, CDC, etc.)? Any advice on best practices, architecture patterns, or real-world implementations would be greatly appreciated.
Best architecture to integrate internal SQL Server system with cloud-based online payment services
I currently have an internal enterprise ERP system also need to be integrated with online payments, and finance operations. The system runs on an on-premises database using Microsoft SQL Server 2022 and stores all financial transactions and internal workflow data. We now have a new requirement to enable online payment services for customers. These services will be exposed externally (likely in the cloud) and must interact with the same financial system so that transactions are reflected in our internal database. My main concerns are related to architecture, security, and data synchronization. Key points about the current setup: The core system and database are hosted internally (on-premises). The database contains sensitive finance and payment data. Internal processes depend on the current database structure and workflows. The new requirements: Develop an online payment service accessible over the internet. Ensure transactions from the online service update the internal system. Maintain data integrity and security. Avoid performance issues for the internal system. I’m evaluating a few possible approaches but I’m unsure which is best practice: Allow the cloud payment service to connect directly to the internal SQL Server database through secure networking. Maintain a replicated or read/write copy of the database in the cloud. Use SQL Server replication (transactional or snapshot) between on-prem and cloud. Introduce an API or middleware layer that handles all transactions and updates the internal database. Maintain separate databases and synchronize transactions asynchronously. My main questions: Is it recommended to expose the internal SQL Server database directly to cloud services? Should I use replication, a secondary database, or a service/API layer? What architecture pattern is commonly used for integrating on-prem financial systems with online payment platforms? How can we ensure consistency between internal transactions and online payments? Are there recommended SQL Server features or patterns for this scenario (replication, service broker, CDC, etc.)? Any advice on best practices, architecture patterns, or real-world implementations would be greatly appreciated.
SQL Server issue but don't know what - please help!
Hi, I'm facing a SQL Server focused issue that I don't understand why it's occurring and would like your help to identify and resolve, please. I will provide an in-depth breakdown of the scenario. Two years ago, I created a Azure Data Factory (ADF) Pipeline to take data from Azure Synapse to Azure SQL Server, and two other Pipelines to take data from an On-Premises Sage server to the same Azure SQL Server. These Pipelines were working perfectly up until two days ago (11/03/26) when the Pipelines still always complete successfully but the duration have increased greatly. The below screenshot shows the log of these three Pipeline for the past week. Note how prior to the 12/03/26 the Synapse Pipeline took about 6 minutes to complete and the two Sage Pipelines took around 25 seconds. Also note how on the 12/03/26 the Synapse Pipeline took over 3 hours but the two Sage Pipelines continued with their normal 25 seconds. Notice today (13/03/26) the Synapse Pipeline was still slow but now the two Sage Pipelines are taking over an hour. I'll note here that the Pipelines still complete successfully (so the config must be correct as it has been for two years). Each Pipeline contains a single (for Sage) or several (for Synapse) 'Copy data' objects. The objects have their source configuration to simply extract from the source (so either Synapse or Sage) and then the sink configuration has a 'Pre-Copy script' which simply Truncates the target SQL Server table, before loading to the SQL Server table. The screenshot below is one example - each Pre-Copy script is populated the same but just with the tables being different. When I look at the log for the Pipelines, I see a common theme for each and that is the 'Pre-Copy script' (the Truncate) is consuming 99% of the time. The screenshot below shows this common theme. So at this point, I ask the question why, after two years of all working well and completing very quickly, are the Pipelines taking so long to complete? This also seems to be an intermittent problem as I have performed several manual executions which will take a long while, then revert back to the quick several minutes again (so good), then revert once more to taking a long while again. It is intermittent. See the screenshot below. Notice how the same Pipeline have different durations. It's intermittent. The reason why I think it is a SQL Server focused issue for the following reasons: 1) Synapse - Performing simple commands (Select Top) returns data within seconds. 2) SQL Server - Performing simple commands (Select Top) usually takes seconds but during the past two days is often taking half hour. 3) SQL Server - When amending a SQL View it would take a split second to complete. During the past two days, it goes over ten minutes and still doesn't complete (I was amending the View for testing purposes). 4) SQL Server - When looking at the Views node under a database, during the past two days, it intermittently doesn't show the View. Sometimes, it will work if I log out and then back into SQL Server. 5) Power BI - Refreshing a Power BI report, whether from the Power BI Service or Desktop, call SQL Server Views. These SQL Server Views read from several SQL Server tables. These report refreshes are failing due to an IDbCommand interface error. These Power BI report data refreshes simply read from a SQL Server table via a SQL View. They don't reference or consider at all the any ADF Pipelines. The Pipelines execute between 2am and 3am each morning. The Power BI report refresh their data around 12pm to 5pm. As SQL Server seems to be problematic at the point of the 'Pre-Copy script', which is one of the end to end process, and then problematic at the very other end where Power BI reports consumes SQL Views - leads me to believe the issue is with SQL Server. I am a report developer and not an ADF expert. I've built the ADF process on the side. I haven't changed any development/configuration/etc... between this all working and failing. Our I.T. department have advised they have made no changes to contribute to this issue. Please can someone advise on what's happening here and why this issue has arose when for two years all was fine? Thanks.
Cannot connect Azure OpenAI Embeddings model to SQL Server 2025
On SQL Server 2025, I am trying to vectorize a table. To set up the ability for SQL Server 2025 to communicate with Azure OpenAI embeddings model, I first created a master key for encryption. CREATE MASTER KEY ENCRYPTION BY PASSWORD = 'Secret'; GO Then I set up a database scoped credential. CREATE DATABASE SCOPED CREDENTIAL [MyAzureOpenAICredential] WITH IDENTITY = 'HTTPEndpointHeaders', SECRET = '{"api-key":"secret"}'; Then I created an external model. CREATE EXTERNAL MODEL AzureOpenAIEmbeddingsModel WITH ( LOCATION = 'https://{secret}-eastus2.cognitiveservices.azure.com/openai/deployments/text-embedding-3-small/embeddings?api-version=2023-05-15', API_FORMAT = 'Azure OpenAI', MODEL_TYPE = EMBEDDINGS, MODEL = 'text-embedding-3-small', CREDENTIAL = [MyAzureOpenAICredential] ); However, when I run this simple script: DECLARE @text NVARCHAR(MAX) = N'SQL Server 2025 enables AI-powered applications'; DECLARE @embedding VECTOR(1536) = AI_GENERATE_EMBEDDINGS(@text USE MODEL AzureOpenAIEmbeddingsModel); I get this error. The database scoped credential 'MyAzureOpenAICredential' cannot be used to invoke an external rest endpoint. I have read through https://learn.microsoft.com/en-us/training/modules/build-ai-solutions-sql-server/4-integrate-ai-models pertaining to this task. As well as SQL Server 2025 docs for creating a model. I have also read SQL Server 2025 docs for creating https://learn.microsoft.com/en-us/sql/t-sql/statements/create-database-scoped-credential-transact-sql?view=sql-server-ver17. I have not found any answers.Polybase - Enforce TCP/IP Protocol
Hello, We know Polybase service in SQL server by default makes use of shared memory protocol to connect SQL server (local). I would like to know if there is any way we can change or force the connections to make use of TCP / IP protocol. Any help would be appreciated.
