ImportExportJobError, SQL72012, SQL72014, SQL72045.
When trying to Import .bacpac file via Azure Portal, it fails with below error: 'code': 'ImportExportJobError', 'message': 'The ImportExport operation with Request Id '' failed due to 'The ImportExport operation with Request Id '' failed due to 'Could not import package.\\nWarning SQL72012: The object [data_0] exists in the target, but it will not be dropped even though you selected the 'Generate drop statements for objects that are in the target database but that are not in the source' check box.\\nWarning SQL72012: The object [log] exists in the target, but it will not be dropped even though you selected the 'Generate drop statements for objects that are in the target database but that are not in the source' check box.\\nError SQL72014: Framework Mi'.'.' The DAC framework hit a hard error and failed due to conflicts with existing system objects in the target database. The generated error does not show much information, except a Warning without enough detail to pinpoint the root cause. ⚠️ What the warnings mean (SQL72012) The object [data_0] exists in the target, but it will not be dropped… The object [log] exists in the target, but it will not be dropped… Retrying the import from the portal doesn’t help—the job fails consistently with the same outcome. To understand the exact cause of error, you can use SQLPackage.exe tool and follow steps below: Download SqlPackage for Windows. To extract the file by right clicking on the file in Windows Explorer, and selecting 'Extract All...', and select the target directory. Open a new Terminal window and cd to the location where SqlPackage was extracted: Import: sqlpackage.exe /Action:Import /tsn:ServerName.database.windows.net /tdn:sqlimporttestDB /tu:sql-user /tp:password /sf:"C:\test\DB-file.bacpac" /d:True /df:C:\test\df.txt TSN: Target server name, where the database will be imported. Tdn: Target database name, the name of the new database that will be created. Tu: user Tp: password Sf: source file, where the bacpac file is located. d: diagnostic, this parameter will help us to obtain detailed information for the import/export process. Df: where the diagnostic file will be saved and the name of it, please change the folder location to the same used on the source file. Note: .bacpac file needs to be present locally on your machine for this command. In the diagnostic file generated, we got a clear error indicating that Script "CREATE USER [EntraUser1@contoso.com] FOR EXTERNAL PROVIDER" failed to execute and only connections established with Entra accounts can create other Entra users. Microsoft.Data.Tools.Diagnostics.Tracer Error: 0 : 2026-01-22T06:56:50 : Error encountered during import operation Exception: Microsoft.SqlServer.Dac.DacServicesException: Could not import package. Error SQL72014: Core Microsoft SqlClient Data Provider: Msg 33159, Level 16, State 1, Line 1 Principal 'EntraUser1@contoso.com' could not be created. Only connections established with Active Directory accounts can create other Active Directory users. Error SQL72045: Script execution error. The executed script: CREATE USER [EntraUser1@contoso.com] FOR EXTERNAL PROVIDER; You’ll also notice the database gets created, but none of the schema or tables are deployed—leaving you with an online but completely blank database. SSMS shows the same behavior, the database appears online after creation, but the import ultimately fails and the resulting database is empty. When explicitly executing this script in database, you'll face the exact same error: If the source database contains only Contained Entra users, you typically won’t see this issue. For contained users, the import job uses a different user-creation script—one that can be executed even when the import connection is established using SQL authentication. CREATE USER [EntraUser2@contoso.com] WITH SID = 'User-SID-Here' , TYPE = E; The issue occurs when the Exported database contains Entra Server logins and a corresponding User is created in the User Database. To mitigate this issue: You need to initiate the Import request using Microsoft Entra Account since SQL Authentication account cannot create a user from an External Provider which is Microsoft Entra in this case. Make the Entra Users 'Contained' in User Database before exporting and then use SQL Authentication account for importing the DB. The second option is especially useful if you prefer importing through the Azure portal but your Entra account has MFA enforced. In that case, using SQL authentication for the import workflow can be a practical path forward. REFERENCES: Import a BACPAC File to Create a Database in Azure SQL Database - Azure SQL Database & Azure SQL Managed Instance | Microsoft Learn SqlPackage Import - SQL Server | Microsoft Learn
"Invalid Managed Identity" error in vulnerability assessments for SQL Managed Instance
On a recent case, a customer received the error "Invalid Managed Identity" when trying to scan a database. The error suggests that there is an issue with the managed identity or the RBAC permissions required, but the same error occurs when there is a connectivity issue between SQL Managed Instance and the storage account selected. Checking RBAC permissions The RBAC permissions can be manually checked in Azure Portal, or you can use the below script in Azure CLI, providing the resource details. #SQL Managed Instance Details $serverResourceGroup = '' $serverName = '' #Storage Account Details $storageAccountResourceGroup = '' $storageAccount = '' ############################################################################################################################## $sqlIdentity = ((az sql mi show -g $serverResourceGroup -n $serverName | ConvertFrom-Json).Identity).principalId $storageId = (az storage account show -g $storageAccountResourceGroup -n $storageAccount | ConvertFrom-Json).id $permissions = $NULL $permissions = az role assignment list --all --assignee $sqlIdentity | ConvertFrom-Json | Where-Object {$_.scope -eq $storageId -and $_.roleDefinitionName -eq 'Storage Blob Data Contributor'} if ($permissions -eq $NULL) {Write-Host "RBAC permissions do not exist"} else {Write-Host "RBAC Permissions exist"} It will return a simple message to confirm if the permissions exist. Connectivity issues If the permissions do exist, then it may be due to connectivity issues between SQL Managed Instance and the storage account. Listed below are ways to check this. Storage account networking configuration The storage account can be configured to allow the following access: Public - All Public - Selected networks Private If the access is set to Selected Networks, make sure the SQL Managed Instance subnet is in the list. If the access is private only, then the SQL Managed Instance would need to be able to resolve the Private IP in DNS. NSG/Firewall rules and routing Check that there are no rules blocking connections between each resource and that the routing is configured correctly. DNS settings If the DNS settings are custom or a private endpoint is being used, the DNS configuration for the SQL Managed Instance virtual network may need to be configured, for example, adding a private DNS zone. Network Peering If the connectivity is through a private endpoint in a different virtual network, check that there is communication between them, such as network peering. Disclaimer Please note that products and options presented in this article are subject to change. This article reflects the documentation in January 2026. I hope this article was helpful for you, please feel free to share your feedback in the comments section.Geo‑Replication Redo Lag in Azure SQL Database
Monitoring and Troubleshooting Using Public DMVs Azure SQL Database provides built‑in high availability and geo‑replication capabilities to ensure database resilience and business continuity. While replication is fully managed by the platform, customers may occasionally observe a delay between the primary and geo‑replicated secondary database, especially during periods of heavy write activity. This article provides a public, supported approach to monitoring and understanding geo‑replication delay caused by redo lag, using official Dynamic Management Views (DMVs) and T‑SQL only, without relying on internal tools. Scenario Overview Customers may report that changes committed on the primary database are not immediately visible on the geo‑replicated secondary, sometimes for several minutes. Typical symptoms include: Reporting queries on the geo‑secondary showing stale data Increased redo catch‑up time on the secondary No performance degradation observed on the primary Replication eventually catches up without manual intervention This behavior is commonly associated with redo lag, where the secondary has already received the log records but requires additional time to replay them into data pages. Understanding Geo‑Replication Redo Lag In Azure SQL Database geo‑replication: Transactions are sent from the primary to the secondary Log records are hardened on the secondary The secondary applies these records asynchronously to its data files (redo) If the secondary experiences temporary pressure (for example, due to schema changes or intensive operations), redo may fall behind, causing the secondary to lag—even though data durability remains intact. Step 1: Check Geo‑Replication Status and Lag The primary DMV for monitoring geo‑replication is: 📘 sys.dm_geo_replication_link_status Public documentation: https://learn.microsoft.com/en-us/sql/relational-databases/system-dynamic-management-views/sys-dm-geo-replication-link-status-azure-sql-database Sample T‑SQL Query -- Run on primary DB SELECT link_guid , partner_server , last_replication , replication_lag_sec FROM sys.dm_geo_replication_link_status; Key Columns Explained Column Description replication_state_desc Current replication state replication_lag_sec Estimated lag (in seconds) last_replication Last successful replication timestamp (UTC) partner_server Geo‑replica logical server Interpretation Healthy replication: replication_lag_sec = 0 and state is healthy Transient delay: Lag increases temporarily but later returns to zero Sustained delay: Lag remains elevated for an extended period and should be investigated further Step 2: Monitor Local Replica Redo Health To understand whether lag is related to redo activity on the secondary, you can query: 📘 sys.dm_database_replica_states Public documentation: https://learn.microsoft.com/en-us/sql/relational-databases/system-dynamic-management-views/sys-dm-database-replica-states-azure-sql-database Sample T‑SQL Query -- Run on primary DB SELECT database_id, synchronization_state_desc, synchronization_health_desc, redo_queue_size, redo_rate, last_commit_time from sys.dm_database_replica_states Key Insights redo_queue_size Indicates how much log data is pending replay on the secondary redo_rate Shows how quickly redo is being applied last_commit_time Helps estimate data freshness on the secondary (UTC) Interpretation Scenario Observation Normal operation redo_queue_size = 0 Write burst redo_queue_size increases temporarily Recovery in progress redo_rate remains positive Healthy state synchronization_health_desc = HEALTHY Short‑lived spikes are expected platform behavior and usually resolve automatically. Practical Monitoring Considerations Reporting Workloads If applications read from the geo‑secondary for reporting: Expect near‑real‑time, not guaranteed real‑time visibility Design reports to tolerate small delays Route latency‑sensitive reads to the primary if required Transaction Patterns Redo lag is more likely during: Large batch updates Index maintenance operations Schema modification commands Bursty write workloads Keeping transactions short and efficient reduces replication pressure. Best Practices Use UTC timestamps consistently when correlating events Monitor replication_lag_sec and redo_queue_size together Implement retry logic in applications for transient conditions Avoid assuming read replicas are always perfectly synchronized Do not take manual actions during short‑lived redo spikes unless the lag persists Summary Redo lag in Azure SQL Database geo‑replication is a normal and self‑healing behavior during certain workload patterns. By using supported public DMVs and T‑SQL, customers can: Monitor replication health safely Understand replica freshness Make informed application routing decisions Avoid unnecessary intervention Azure SQL Database automatically stabilizes replication once redo pressure subsides, ensuring durability and availability without manual management. References Azure SQL Database High Availability https://learn.microsoft.com/azure/azure-sql/database/high-availability-overview sys.dm_geo_replication_link_status https://learn.microsoft.com/en-us/sql/relational-databases/system-dynamic-management-views/sys-dm-geo-replication-link-status-azure-sql-database sys.dm_database_replica_states https://learn.microsoft.com/en-us/sql/relational-databases/system-dynamic-management-views/sys-dm-database-replica-states-azure-sql-databaseReal‑World Cloud & Azure SQL Database Examples Using Kepner‑Tregoe
The Kepner‑Tregoe (KT) methodology is especially effective in modern cloud environments like Azure SQL Database, where incidents are often multi‑dimensional, time‑bound, and affected by asynchronous and self‑healing behaviors. Below are practical examples illustrating how KT can be applied in real Azure SQL scenarios. Example 1: Azure SQL Geo‑Replication Lag Observed on Read‑Only Replica Scenario An application team reports that changes committed on the primary Azure SQL Database are not visible on the geo‑replica used for reporting for up to 30–40 minutes. The primary database performance remains healthy. Applying KT – Problem Analysis What is happening? Read‑only geo‑replica is temporarily behind the primary. What is not happening? No primary outage, no data corruption, no failover. Where does it occur? Only on the geo‑secondary, during specific time windows. When does it occur? Repeatedly around the same time each hour. What is the extent? Lag spikes, then returns to zero. KT Insight By separating data visibility delay from primary health, teams avoid misdiagnosing the issue as a platform outage. Public DMVs (such as sys.dm_geo_replication_link_status and sys.dm_database_replica_states) confirm this as a transient redo lag scenario, not a service availability issue. Example 2: Error 3947 – Transaction Aborted Due to HA Replica Redo Lag Scenario Applications intermittently hit error 3947 (“The transaction was aborted because the secondary failed to catch up redo”), while primary latency remains stable. Applying KT – Situation Appraisal What needs immediate action? Ensure application retry logic is functioning. What can wait? Deep analysis—since workload resumes normally after retries. What should not be escalated prematurely? Platform failover or data integrity concerns. KT Insight KT helps distinguish protective platform behavior from defects. Error 3947 is a deliberate safeguard in synchronous HA models to maintain consistency—not an outage or bug. Example 3: Performance Degradation During Business‑Critical Reporting Scenario Customer reports slow reporting queries on a readable secondary during peak hours, coinciding with replication lag spikes. Applying KT – Decision Analysis Possible actions: Route reporting queries back to primary during spike window Scale up replica resources Move batch processing off peak hours KT Decision Framework Musts: No data inconsistency, minimal user impact Wants: Low cost, fast mitigation, minimal architecture change Decision Temporarily route latency‑sensitive reads to the primary while continuing investigation. This decision is defensible, documented, and reversible. Example 4: Preventing Recurrence with Potential Problem Analysis Scenario Recurring redo lag spikes happen daily at the same minute past the hour. Applying KT – Potential Problem Analysis What could go wrong? Hourly batch job may generate large log bursts How likely is it? High (pattern repeats daily) What is the impact? Temporary stale reads on replicas Preventive actions: Break batch jobs into smaller units Shift non‑critical workloads outside reporting hours Monitor redo queue size proactively KT Insight Rather than responding reactively each day, teams use KT to anticipate and reduce the likelihood and impact of recurrence. Example 5: Coordinated Incident Management Across Regions Scenario An Azure SQL issue spans EMEA, APAC, and US support teams, with intermittent symptoms and high stakeholder visibility. Applying KT – Situation Appraisal KT helps teams: Prioritize which signals are critical vs. noise Decide when to involve engineering vs. continue monitoring Communicate clearly with customers using facts, not assumptions This prevents “analysis paralysis” or conflicting interpretations across time zones. Why KT Works Well in Cloud and Azure SQL Environments Cloud platforms contain self‑healing, asynchronous behaviors that can be misinterpreted Multiple metrics may conflict without structured reasoning KT brings discipline, shared language, and defensible conclusions It complements tooling (DMVs, metrics, alerts)—it doesn’t replace them Closing Thought In cloud operations, how you think is as important as what you observe. Kepner‑Tregoe provides a timeless, structured way to reason about complex Azure SQL Database behaviors—helping teams respond faster, communicate better, and avoid unnecessary escalations.Lesson Learned #521: Query Performance Regression with Multiple Execution Plans in Azure SQL
Some days ago, we were working on a service request where our customer asked why a query had degraded in performance. One possible issue could be that more than one execution plan is being used for a specific query. So I would like to share the steps we followed using QDS with DMVs. First, we executed this query to identify any queries that had more than one plan_id, which is often a sign that the optimizer has compiled multiple strategies to run the same query: SELECT q.query_id, qt.query_sql_text, q.query_hash, COUNT(DISTINCT p.plan_id) AS num_plans, STRING_AGG(CAST(p.plan_id AS VARCHAR), ', ') AS plan_ids FROM sys.query_store_query_text qt JOIN sys.query_store_query q ON qt.query_text_id = q.query_text_id JOIN sys.query_store_plan p ON q.query_id = p.query_id GROUP BY q.query_id, qt.query_sql_text, q.query_hash HAVING COUNT(DISTINCT p.plan_id) > 1 ORDER BY num_plans DESC; We got a list of queries and after some analysis, we found the one the customer was referring to. The query in question was a simple aggregate with a parameter: (@N int)SELECT count(Name),name FROM Notes where ID<@n group by Name As we found that they query has two plans, we executed the following TSQL to obtain the details of the executions. SELECT rs.execution_type_desc, rs.avg_duration / 1000 AS avg_duration_ms, rs.avg_cpu_time / 1000 AS avg_cpu_ms, rs.last_duration / 1000 AS last_duration_ms, rs.count_executions, rs.first_execution_time, rs.last_execution_time, p.plan_id, p.is_forced_plan, TRY_CONVERT(XML, p.query_plan) AS execution_plan_xml FROM sys.query_store_runtime_stats rs JOIN sys.query_store_plan p ON rs.plan_id = p.plan_id WHERE p.query_id = 2 ORDER BY rs.last_execution_time DESC; We got the following results: We could see the execution plan number 2 was executed less time but taking more time in average. Checking the execution plan XML we were able to identify an automatic update statistics was executed causing a new execution plan. Trying to give insights about possible causes, we wrote the following TSQL giving us when the statistics were updated directly from the execution plan XML. ;WITH XMLNAMESPACES (DEFAULT 'http://schemas.microsoft.com/sqlserver/2004/07/showplan') SELECT p.plan_id, stat.value('@Statistics', 'VARCHAR(200)') AS stats_name, stat.value('@LastUpdate', 'DATETIME') AS stats_last_updated, stat.value('@SamplingPercent', 'FLOAT') AS stats_sampling_percent FROM sys.query_store_plan AS p CROSS APPLY ( SELECT CAST(p.query_plan AS XML) AS xml_plan ) AS x OUTER APPLY x.xml_plan.nodes(' /ShowPlanXML/BatchSequence/Batch/Statements/StmtSimple/QueryPlan/OptimizerStatsUsage/StatisticsInfo' ) AS t(stat) WHERE p.query_id = 2; Well, we found another way to query directly the execution plan and include other information from Query Data Store. Enjoy!Principle 'XYZ' could not be found or this principal type is not supported - Azure SQL DB and MI
In this blog article, we will be discussing the possible scenarios to get the error "Principle 'XYZ' could not be found or this principal type is not supported" while adding an AAD user or group to your Azure SQL database or Azure SQL managed instance.Lesson Learned #517:Connection Timeouts to Azure SQL Database Using Private Endpoint with HikariCP
Recently, we have been working on a support case where our customer reported the following error message: ERROR com.zaxxer.hikari.pool.HikariPool - HikariPool-1 - Exception during pool initialization. com.microsoft.sqlserver.jdbc.SQLServerException: The TCP/IP connection to the host myserverX.database.windows.net, port 1433 has failed. Error: 'Connection timed out: no further information. Verify the connection properties. Make sure that an instance of SQL Server is running on the host and accepting TCP/IP connections at the port. Make sure that TCP connections to the port are not blocked by a firewall.' I would like to share the lessons learned during the troubleshooting and resolution process Initially, what caught our attention were the first two messages: Exception during pool initialization and Connection Timeout out. This indicates that Hikari was unable to create the connection pool during the initialization process (one of the first steps in connection pooling) due to a connection timeout. Therefore, we began working on connectivity options and started investigating, asking if our customer is using public endpoint or private endpoint, they confirmed the private endpoint usage. The following factors could be identified as possible causes: Private Endpoint Misconfiguration: The Private Endpoint was not correctly associated with the Azure SQL Database. DNS Resolution Issues: The database hostname was not resolving to the Private Endpoint's private IP address. Network Security Group (NSG) Restrictions: The NSG attached to the subnet hosting the Private Endpoint was blocking inbound traffic on port 1433. Firewall Settings on Azure SQL Database: Firewall rules were not allowing connections from the source network. Redirect Mode Configuration: Additional ports required for redirect mode were blocked or misconfigured. Our troubleshooting steps started running using nslookup myserverX.database.windows.net to ensure that the database hostname resolves to the Private Endpoint's private IP address. If the IP is public instead of private, we verify the DNS configuration or use Azure DNS. Our second step was to validate the Java Application host can reach Azure SQL Database on port 1433 or the redirect port (if our customer use redirect connection policy) using the command telnet myserverX.database.windows.net 1433 or the Linux command nc -vz myserverX.database.windows.net 1433 and we identified the connections fails. Check this Azure SQL Database and Azure Synapse Analytics connectivity architecture and Azure Private Link - Azure SQL Database & Azure Synapse Analytics | Microsoft Learn for more details. Following we verify the Network Security Group attached to the subnet if allows outbound traffic to the port 1433 and we found that the NSG rule doesn't exist for private endpoint. Once the rule was added the Java Application was able to connect.
Additional Endpoints Required for AAD Authentication and CRL Checks for Azure SQL DB
You may have attempts to connect to Azure SQL Database with an Azure Active Directory (AAD) account that are failing with a timeout error, but SQL Authentication works as expected. Alternatively you could be encountering generic connection errors with the inner exception being ‘Revocation of the SSL certificate failed’. If the following workarounds are not sufficient, you may have to whitelist specific endpoints on your Firewalls or network infrastructure: Disabling the Revocation of the SSL Certificate Check: Revocation of the SSL certificate failed for AAD authentication - Microsoft Tech Community Allowing all SSL traffic from that server on their firewall An example of the ‘Revocation of the SSL certificate failed’ error in SQL Server Management Studio (SSMS): You can take a network trace in order to see where traffic is being blocked, or to grab the certificate that is being passed back. Having the certificate will allow you to examine the CRL endpoints listed in the certificate itself. Instead of taking a network trace, you may want to watch blocked traffic on your Firewall and whitelist trusted endpoints that appear in order to expedite troubleshooting. You can test connectivity to ports via PowerShell using, for example, “tnc login.windows.net -port 443”. If you have an ADFS setup, then to authenticate you will need to whitelist your ADFS endpoint on port 443. If you have multiple ADFS endpoints you will need to whitelist the one that your DNS server is resolving you to. This is a non-exhaustive list of endpoints that may be required depending on the authentication type. Additional endpoints may be required to communicate with Active Directory Federation Services (ADFS), or depending on your networking path and if you are using a public Certification Authority (CA), endpoints for whoever has issued your certificate for ADFS. Please note not all Firewalls can be configured to accept wildcards, and while the below list has as many explicitly defined URLs as possible, you may need to see what traffic is being blocked on the Firewall to get definite URLs for those not fully defined here. This is also how you can determine if something not on this list is being blocked and is required for your particular networking setup (perhaps the ADFS endpoint your machine is reaching out to is not the one you expect, etc). URL Port Description mscrl.microsoft.com HTTP/80 Used to download CRL lists. *.verisign.com HTTP/80 Used to download CRL lists. *.entrust.net HTTP/80 Used to download CRL lists for MFA. *.management.core.windows.net (Azure Storage) *.graph.windows.net (Azure AD Graph) HTTPS/443 Used for the various Azure services secure.aadcdn.microsoftonline-p.com HTTPS/443 Used for MFA. *.microsoftonline.com HTTPS/443 Used to configure your Azure AD directory and import/export data. login.microsoftonline.us HTTPS/443 Used by US Gov for AD Login. login.microsoftonline.com HTTPS/443 Used by Public cloud for AD login for MFA. login.windows.net HTTPS/443 Used by Public cloud for AD login for Password and Integrated. http://crl.microsoft.com HTTP/80 Used to verify certificates. http://crl3.digicert.com HTTP/80 Used to verify certificates. http://crl4.digicert.com HTTP/80 Used to verify certificates. http://ocsp.digicert.com HTTP/80 Used to verify certificates. http://www.d-trust.net HTTP/80 Used to verify certificates. http://root-c3-ca2-2009.ocsp.d-trust.net HTTP/80 Used to verify certificates. http://crl.microsoft.com HTTP/80 Used to verify certificates. http://oneocsp.microsoft.com HTTP/80 Used to verify certificates. http://ocsp.msocsp.com HTTP/80 Used to verify certificates. http://www.microsoft.com/pkiops HTTP/80 Used to verify certificates. cacerts.digicert.com HTTP/80 Used to verify certificates. ctldl.windowsupdate.com HTTP/80 Used to verify certificates. References Azure Active Directory certificate authorities | Microsoft Docs Azure TLS Certificate Changes | Microsoft Docs Azure AD Connect: Troubleshoot Azure AD connectivity issues | Microsoft Docs Revocation of the SSL certificate failed for AAD authentication - Microsoft Tech Community Microsoft 365 endpoints - Microsoft 365 Enterprise | Microsoft DocsLesson Learned #383: Loading multiple extended file using sys.fn_xe_file_target_read_file
In today's technologically advanced world, data plays a crucial role in driving decision-making processes and gaining valuable insights. One of the popular methods for capturing and analyzing data in Microsoft SQL Server is through Extended Events (XE). XE allows administrators to collect information about various events occurring within the SQL Server environment. However, managing and loading multiple extended event files can be a challenging task. In this article, we will explore an effective solution using the sys.fn_xe_file_target_read_file function to load multiple extended event files seamlessly.
