365 Tenant To Tenant Migration
I have a tenant who is not set up to be GCC compliant. We have created another tenant that is now GCC compliant and need to move the tenants from the original tenant to the newly created GCC compliant tenancy. I am not sure how we can go about doing this with the destination and origination having the same domain name. I have created the users with the onmicrosoft accounts, instead of the .org users, but we still have the issue of migration. How do we move these users? What is the expected down time for their domain if we use a dummy domain? I am very concerned this is going to result in a massive loss of data.Teams Delivers a Slack Migration Tool
Microsoft announced the availability of a Slack to Teams migration tool in the Microsoft 365 admin center. The new tool exists to assist the 79 million monthly active users of Slack who might want to move to Teams and don’t know how to get there. ISVs have been helping people move off Slack to Teams for years, so other migration options exist. https://office365itpros.com/2026/01/07/slack-to-teams-migration/
GoDaddy to Microsoft 365 Migration Issues
Hi there, I wonder if I could get some help with an issue I've got. Currently I am attempting to migrate one user mailbox from the current GoDaddy tenant to our new Microsoft tenant, to initially test out the migration. I've followed the Migration tool in the Exchange admin center but am receiving the following error: Error: MigrationRecipientNotFoundException: A recipient wasn't found for "***@***.onmicrosoft.com". Create a recipient of the appropriate type for this migration and try again. I've got the user created in the Microsoft 365 admin center and a mailbox is set up for them. Both on GoDaddy and Microsoft it is UserMailbox recipient type. I'm using the IMAP Migration settings as outlined from the GoDaddy IMAP settings, and have since checked with GoDaddy and they give these settings: IMAP Server: imap.secureserver.net Authentication: Basic Encryption: SSL Accept untrusted certificates: Yes Port: 993 GoDaddy have also said that Basic authentication is supported by them and I have checked the Entra configuration to ensure that Basic is not blocked. I have even had the user I'm attempting to migrate log in to the temporary onmicrosoft account to make sure there are no log in issues there. I have posted this on the Answers forum as well and was pointed in this direction for further help. Any thoughts or help on this would be amazing. Thanks in advance, Oli
Issue when ingesting Defender XDR table in Sentinel
Hello, We are migrating our on-premises SIEM solution to Microsoft Sentinel since we have E5 licences for all our users. The integration between Defender XDR and Sentinel convinced us to make the move. We have a limited budget for Sentinel, and we found out that the Auxiliary/Data Lake feature is sufficient for verbose log sources such as network logs. We would like to retain Defender XDR data for more than 30 days (the default retention period). We implemented the solution described in this blog post: https://jeffreyappel.nl/how-to-store-defender-xdr-data-for-years-in-sentinel-data-lake-without-expensive-ingestion-cost/ However, we are facing an issue with 2 tables: DeviceImageLoadEvents and DeviceFileCertificateInfo. The table forwarded by Defender to Sentinel are empty like this row: We created a support ticket but so far, we haven't received any solution. If anyone has experienced this issue, we would appreciate your feedback. LucasAzure SQL Database Data Sync Retirement: Migration Scenarios and Recommended Alternatives
Azure SQL Database Data Sync has long been used to keep data consistent across multiple Azure SQL databases. However, as the service moves toward retirement, many customers are now asking an important question: How do we replace Azure SQL Data Sync with a supported, future‑proof solution—without significant data loss or downtime? In this article, we’ll walk through: What Data Sync retirement means in practice Typical migration challenges A real-world customer scenario Recommended alternatives A step‑by‑step migration approach from DEV to PROD Useful references and documentation Why Azure SQL Data Sync Retirement Matters Azure SQL Data Sync relies on: Triggers Metadata tables Hub-and-spoke topology While functional, this architecture introduces complexity, performance overhead, and operational risks, especially as data volumes and workloads grow. Microsoft’s long-term direction favors scalable, resilient, and observable data integration services, such as Azure Data Factory (ADF) and event-driven replication patterns. If you are currently using Data Sync, planning a migration early is strongly recommended. Official guidance: https://learn.microsoft.com/azure/azure-sql/database/sql-data-sync-data-sql-server-sql-database Sample Customer Scenario Let’s consider a real scenario commonly seen in the field: 4 Azure SQL Databases Subscription: Contoso-DEV Current topology: Azure SQL Data Sync Target state: Consolidate all data into one Azure SQL Database Environment flow: DEV → UAT → PROD Database tiers: Standard (S0 / S1) Size: Below 250 GB per database Key requirements: Minimal data loss Quick replication Azure-native and supported replacement Clear operational model Migration Design Considerations Before selecting a tool, several factors must be evaluated: ✅ Latency tolerance (near real-time vs scheduled sync) ✅ Write patterns (conflicts, bidirectional vs unidirectional) ✅ Schema compatibility ✅ Operational overhead ✅ Long-term supportability For most consolidation scenarios, unidirectional replication (many → one) provides the best balance of simplicity and reliability. Diagram 1: Current State – Azure SQL Data Sync (Before Retirement) This diagram represents the existing topology, where multiple databases are synchronized using Azure SQL Data Sync into a single consolidated database. Characteristics Trigger‑based synchronization Additional metadata tables Limited observability Service approaching retirement Diagram 2: Target State – Azure Data Factory Based Consolidation This diagram shows the recommended replacement architecture using Azure Data Factory. Advantages No triggers or sync metadata tables Parallel ingestion Built‑in retry, monitoring, and alerting Fully supported and future‑proof Diagram 3: Incremental Replication Logic (ADF) This diagram explains how minimal data loss is achieved using incremental replication. Key Points No continuous connection required Typical RPO: 1–5 minutes Safe restart after failures Diagram 4: DEV → PROD Migration Flow This diagram highlights the recommended rollout approach starting with POC in DEV. Best Practices Build once, reuse across environments Parameterize connection strings Enable monitoring before PROD cutover Recommended Alternatives to Azure SQL Data Sync ✅ Option 1: Azure Data Factory (ADF) – Primary Recommendation Azure Data Factory provides a fully supported and scalable replacement for Data Sync when consolidating databases. Architecture Overview One pipeline per source database Initial full load Incremental replication using: Change Tracking, or CDC (if applicable), or Watermark columns (ModifiedDate / identity) Why ADF? Microsoft’s strategic data integration platform Built-in monitoring and retry logic Parallel ingestion Schema mapping and transformation support 📌 Best fit when: You need consolidation Near real‑time (minutes) is acceptable You want a future‑proof design 📘 References: https://learn.microsoft.com/azure/data-factory/copy-activity-overview https://learn.microsoft.com/azure/data-factory/incremental-copy-overview https://learn.microsoft.com/azure/data-factory/connector-azure-sql-database ⚠️ Option 2: SQL Transactional Replication (Limited Use) Transactional replication can still work in narrow scenarios, but: Adds operational complexity Limited flexibility for schema changes Not recommended for new designs 📘 Reference: https://learn.microsoft.com/azure/azure-sql/database/replication-to-sql-database 🧭 Option 3: Azure SQL Managed Instance Link (Future‑Facing) If your long-term roadmap includes Azure SQL Managed Instance, the MI Link feature enables near real-time replication. However: Not applicable if your target remains Azure SQL Database Requires infrastructure change 📘 Reference: https://learn.microsoft.com/azure/azure-sql/managed-instance/link-feature Recommended Migration Approach (DEV → PROD) Phase 1 – Assessment Review schema overlaps and key conflicts Identify identity and primary key strategies Confirm availability of: Change Tracking ModifiedDate / watermark columns 📘 Change Tracking: https://learn.microsoft.com/sql/relational-databases/track-changes/about-change-tracking-sql-server Phase 2 – Initial Seeding (DEV) Use ADF Copy Activity for full loads Ingest each source DB into: Dedicated schemas, or Logical partitions Validate: Row counts Referential integrity Performance impact Phase 3 – Incremental Replication Enable incremental pipelines Recommended frequency: every 1–5 minutes Use parallelism for scalability Simulate Data Sync behavior without triggers Phase 4 – Cutover Optional short write freeze Final delta sync Application validation Promote pipelines to PROD Data Loss and Performance Expectations Metric Expected Outcome RPO Minutes (configurable) Downtime Near‑zero Performance impact Predictable and controllable Observability Built‑in via ADF monitoring Final Recommendation Summary ✅ Azure Data Factory with initial full load + incremental replication ✅ Azure-native, strategic, and supported ✅ Ideal for Data Sync retirement scenarios ✅ Scales from DEV to PROD with minimal redesign Azure SQL Data Sync retirement is an opportunity—not a setback. With services like Azure Data Factory, customers can move toward: Better observability Cleaner architectures Easier production operations Long-term platform alignment If you are still relying on Azure SQL Data Sync, now is the right time to assess, plan, and migrate. Helpful Resources Azure SQL Data Sync overview https://learn.microsoft.com/azure/azure-sql/database/sql-data-sync-data-sql-server-sql-database Azure Data Factory incremental copy https://learn.microsoft.com/azure/data-factory/incremental-copy-overview Azure SQL change tracking https://learn.microsoft.com/sql/relational-databases/track-changes/about-change-tracking-sql-serverAzure SQL Database Data Sync Retirement: Migration Scenarios and Recommended Alternatives
Why Azure SQL Data Sync Retirement Matters Azure SQL Data Sync relies on: Triggers Metadata tables Hub-and-spoke topology While functional, this architecture introduces complexity, performance overhead, and operational risks, especially as data volumes and workloads grow. Microsoft’s long-term direction favors scalable, resilient, and observable data integration services, such as Azure Data Factory (ADF) and event-driven replication patterns. If you are currently using Data Sync, planning a migration early is strongly recommended. Official guidance: https://learn.microsoft.com/azure/azure-sql/database/sql-data-sync-data-sql-server-sql-database Sample Customer Scenario Let’s consider a real scenario commonly seen in the field: 4 Azure SQL Databases Subscription: Contoso-DEV Current topology: Azure SQL Data Sync Target state: Consolidate all data into one Azure SQL Database Environment flow: DEV → UAT → PROD Database tiers: Standard (S0 / S1) Size: Below 250 GB per database Key requirements: Minimal data loss Quick replication Azure-native and supported replacement Clear operational model Migration Design Considerations Before selecting a tool, several factors must be evaluated: ✅ Latency tolerance (near real-time vs scheduled sync) ✅ Write patterns (conflicts, bidirectional vs unidirectional) ✅ Schema compatibility ✅ Operational overhead ✅ Long-term supportability For most consolidation scenarios, unidirectional replication (many → one) provides the best balance of simplicity and reliability. Diagram 1: Current State – Azure SQL Data Sync (Before Retirement) This diagram represents the existing topology, where multiple databases are synchronized using Azure SQL Data Sync into a single consolidated database. Characteristics Trigger‑based synchronization Additional metadata tables Limited observability Service approaching retirement Diagram 2: Target State – Azure Data Factory Based Consolidation This diagram shows the recommended replacement architecture using Azure Data Factory. Advantages No triggers or sync metadata tables Parallel ingestion Built‑in retry, monitoring, and alerting Fully supported and future‑proof Diagram 3: Incremental Replication Logic (ADF) This diagram explains how minimal data loss is achieved using incremental replication. Key Points No continuous connection required Typical RPO: 1–5 minutes Safe restart after failures Diagram 4: DEV → PROD Migration Flow This diagram highlights the recommended rollout approach starting with POC in DEV. Best Practices Build once, reuse across environments Parameterize connection strings Enable monitoring before PROD cutover Recommended Alternatives to Azure SQL Data Sync ✅ Option 1: Azure Data Factory (ADF) – Primary Recommendation Azure Data Factory provides a fully supported and scalable replacement for Data Sync when consolidating databases. Architecture Overview One pipeline per source database Initial full load Incremental replication using: Change Tracking, or CDC (if applicable), or Watermark columns (ModifiedDate / identity) Why ADF? Microsoft’s strategic data integration platform Built-in monitoring and retry logic Parallel ingestion Schema mapping and transformation support 📌 Best fit when: You need consolidation Near real‑time (minutes) is acceptable You want a future‑proof design 📘 References: https://learn.microsoft.com/azure/data-factory/copy-activity-overview https://learn.microsoft.com/azure/data-factory/incremental-copy-overview https://learn.microsoft.com/azure/data-factory/connector-azure-sql-database ⚠️ Option 2: SQL Transactional Replication (Limited Use) Transactional replication can still work in narrow scenarios, but: Adds operational complexity Limited flexibility for schema changes Not recommended for new designs 📘 Reference: https://learn.microsoft.com/azure/azure-sql/database/replication-to-sql-database 🧭 Option 3: Azure SQL Managed Instance Link (Future‑Facing) If your long-term roadmap includes Azure SQL Managed Instance, the MI Link feature enables near real-time replication. However: Not applicable if your target remains Azure SQL Database Requires infrastructure change 📘 Reference: https://learn.microsoft.com/azure/azure-sql/managed-instance/link-feature Recommended Migration Approach (DEV → PROD) Phase 1 – Assessment Review schema overlaps and key conflicts Identify identity and primary key strategies Confirm availability of: Change Tracking ModifiedDate / watermark columns 📘 Change Tracking: https://learn.microsoft.com/sql/relational-databases/track-changes/about-change-tracking-sql-server Phase 2 – Initial Seeding (DEV) Use ADF Copy Activity for full loads Ingest each source DB into: Dedicated schemas, or Logical partitions Validate: Row counts Referential integrity Performance impact Phase 3 – Incremental Replication Enable incremental pipelines Recommended frequency: every 1–5 minutes Use parallelism for scalability Simulate Data Sync behavior without triggers Phase 4 – Cutover Optional short write freeze Final delta sync Application validation Promote pipelines to PROD Data Loss and Performance Expectations Metric Expected Outcome RPO Minutes (configurable) Downtime Near‑zero Performance impact Predictable and controllable Observability Built‑in via ADF monitoring Final Recommendation Summary ✅ Azure Data Factory with initial full load + incremental replication ✅ Azure-native, strategic, and supported ✅ Ideal for Data Sync retirement scenarios ✅ Scales from DEV to PROD with minimal redesign Azure SQL Data Sync retirement is an opportunity—not a setback. With services like Azure Data Factory, customers can move toward: Better observability Cleaner architectures Easier production operations Long-term platform alignment If you are still relying on Azure SQL Data Sync, now is the right time to assess, plan, and migrate. Helpful Resources Azure SQL Data Sync overview https://learn.microsoft.com/azure/azure-sql/database/sql-data-sync-data-sql-server-sql-database Azure Data Factory incremental copy https://learn.microsoft.com/azure/data-factory/incremental-copy-overview Azure SQL change tracking https://learn.microsoft.com/sql/relational-databases/track-changes/about-change-tracking-sql-server
