Windows Authentication for Cloud-Native Identities: Modernizing Azure SQL Managed Instance (Preview)
Organizations moving to the cloud often face a critical challenge: maintaining seamless authentication for legacy applications without compromising security or user experience. Today, we’re excited to announce support for Windows Authentication for Microsoft Entra principals on Azure SQL Managed Instance, enabling cloud-native identities to authenticate using familiar Windows credentials. Why This Matters Traditionally, Windows Authentication relied on on-premises Active Directory, making it difficult for businesses adopting a cloud-only strategy to preserve existing authentication models. With this new capability: Hybrid Identity Support: Users synchronized between on-premises AD DS and Microsoft Entra ID can continue using a single set of credentials for both environments. Cloud-Only Identity (Preview): Identities that exist only in Microsoft Entra ID can now leverage Kerberos-based Windows Authentication for workloads like Azure SQL Managed Instance—without requiring domain controllers. This means organizations can modernize infrastructure while maintaining compatibility with legacy apps, reducing friction during migration. Key Benefits Seamless Migration: Move legacy applications to Azure SQL Managed Instance without rewriting authentication logic. Passwordless Security: Combine Windows Authentication with modern credentials like Windows Hello for Business or FIDO2 keys, enabling MFA and reducing password-related risks. Cloud-Native Integration: Microsoft Entra Kerberos acts as a cloud-based Key Distribution Center (KDC), issuing Kerberos tickets for cloud resources such as Azure SQL Managed Instance and Azure Files Breaking Barriers to Cloud Migration Many enterprises hesitate to migrate legacy apps because they depend on Windows Authentication. By extending this capability to cloud-native identities, we remove a major barrier—allowing customers to modernize at their own pace while leveraging familiar authentication models. Learn More https://learn.microsoft.com/en-us/azure/azure-sql/managed-instance/winauth-azuread-overview?view=azuresql Microsoft Entra Kerberos OverviewLesson Learned #526: How to Identify the REST API Version Used by Your PowerShell Commands?
A few days ago, I wanted to understand which REST API version was being used behind each PowerShell command I was running to create Azure SQL Database servers. To investigate, I picked a simple command: Get-AzSqlServer -ResourceGroupName "ResourceGroupName" -ServerName "servername". Remember that Get-AzSqlServer cmdlet is a PowerShell wrapper over the Azure REST API for the Microsoft.Sql/servers resource. Internally, it makes a call to the ARM endpoint documented here, passing the required api-version. The actual version used depends on the installed Az.Sql module and may vary from one environment to another. I found that setting the variable $DebugPreference = "Continue" in my PowerShell Script , PowerShell prints detailed internal debug output, including the exact REST API call sent to Azure Resource Manager (ARM). Checking the output I've found the section called: Absolute Uri: https://management.azure.com/subscriptions/xxx-xxxx--613ccd2df306/resourceGroups/ResourceGroupName/providers/Microsoft.Sql/servers/servername?api-version=2023-02-01-preview So, it seems that running this command we could see this info. Even though you don’t explicitly define the api-version when using cmdlets like Get-AzSqlServer, the Azure platform requires it under the hood. The version used determines, which properties are available or supported, what operations behave differently across versions, whether the call will succeed once older versions are retired, etc.. For example, by using Azure CLI from the Portal, I was able to see the most recent API versions. It’s also important to note that, if your organization has .NET code managing Azure SQL Database environments, the underlying REST API calls might still be using an outdated preview version.Step-by-Step Guide: Route Azure SQL Audit Logs to Multiple Log Analytics Workspaces
Scenario: Many organizations need to route audit logs from Azure SQL Database to more than one Log Analytics workspace. For example, your security team may use Microsoft Sentinel in one workspace, while your application team analyzes logs in another. Azure now makes this possible—here’s how to set it up, and what to watch out for. Why Send Audit Logs to Multiple Workspaces? Separation of Duties: Security and application teams can access the logs they need, independently. Integration with Different Tools: Sentinel may use one workspace for SIEM, while app teams use another for analytics. Compliance and Regional Needs: Some organizations must store logs in different regions or workspaces for regulatory reasons. Step-by-Step Guide Enable Auditing to Log Analytics Workspace Go to your Azure SQL Server in the Azure Portal. Under Security, select Auditing. Set the audit destination to your primary Log Analytics workspace, Click Save. Tip: Enabling auditing here automatically creates a diagnostic setting for the selected workspace. Add Diagnostic Settings for Additional Workspaces In azure portal search for Diagnostic settings. Search for your subscription and master database of SQL Server to create diagnostics setting at server level Click + Add diagnostic setting. Name your setting (e.g., “AuditToAppWorkspace”). Under Log, select audit, select SQLSecurityAuditEvents (uncheck “DevOpsAudit” if not needed). Choose an additional Log Analytics workspace as the destination. Click Save. create new setting Note: You can repeat this step to send audit logs to as many workspaces as needed. Example Use Case A customer uses: Workspace A for Microsoft Sentinel (security monitoring) Workspace B for application analytics By configuring multiple diagnostic settings, both teams receive the audit data they need—no manual exports required. Summary Configuring multiple diagnostic settings allows you to send Azure SQL Database audit logs to several Log Analytics workspaces. This is essential for organizations with different teams or compliance needs. Remember: Enable auditing first Add diagnostic settings for each workspace Monitor for cost and avoid duplicate logs References: https://learn.microsoft.com/en-us/azure/azure-sql/database/auditing https://learn.microsoft.com/en-us/azure/azure-monitor/essentials/diagnostic-settings
ABORT_QUERY_EXECUTION query hint - public preview
We are pleased to announce the public preview of a new query hint, ABORT_QUERY_EXECUTION. The hint is intended to be used as a Query Store hint to let administrators block future execution of known problematic queries, for example non-essential queries causing high resource consumption and affecting application workloads. The hint is now available in Azure SQL Database for all databases without restrictions. The hint will later be available in Azure SQL Managed Instance with the always-up-to-date update policy, as well as in a future version of SQL Server. For more information, see Block future execution of problematic queries in documentation. Update 2025-10-06: The ABORT_QUERY_EXECUTION hint is now generally available. Frequently Asked Questions Is this supported by Microsoft Support during public preview? Yes, just like other query hints. How do I use this? Use Query Store catalog views or the Query Store UI in SSMS to find the query ID of the query you want to block and execute sys.sp_query_store_set_hints specifying that query ID as a parameter. For example: EXEC sys.sp_query_store_set_hints @query_id = 17, @query_hints = N'OPTION (USE HINT (''ABORT_QUERY_EXECUTION''))'; What happens when a query with this hint is executed? This hint is intended to be used as a Query Store hint but can be specified directly as well. In either case, the query fails immediately with error 8778, severity 16: Query execution has been aborted because the ABORT_QUERY_EXECUTION hint was specified. How do I unblock a query? Remove the hint by executing sys.sp_query_store_clear_hints with the query ID value of the query you want to unblock passed via the @query_id parameter. Can I block a query that is not in Query Store? No. At least one execution of the query must be recorded in Query Store. That query execution does not have to be successful. This means that a query that started executing but was canceled or timed out can be blocked too. When I add the hint, does it abort any currently executing queries? No. The hint only aborts future query executions. You can use KILL to abort currently executing queries. What permissions are required to use this? As with all other Query Store hints, the ALTER permission on the database is required to set and clear the hint. Can I block all queries matching a query hash? Not directly. As with all other Query Store hints, you must use a query ID to set and clear a hint. However, you can create automation that will periodically find all new query IDs matching a given query hash and block them. Can I find all blocked queries in Query Store? Yes, by executing the following query: SELECT qsh.query_id, q.query_hash, qt.query_sql_text FROM sys.query_store_query_hints AS qsh INNER JOIN sys.query_store_query AS q ON qsh.query_id = q.query_id INNER JOIN sys.query_store_query_text AS qt ON q.query_text_id = qt.query_text_id WHERE UPPER(qsh.query_hint_text) LIKE '%ABORT[_]QUERY[_]EXECUTION%' Where do I send feedback about this hint? The preferred feedback channel is via https://aka.ms/sqlfeedback. Feedback sent that way is public and can be voted and commented on by other SQL community members. You can also leave comments on this blog post or email us at intelligentqp@microsoft.com.Stream data in near real time from SQL to Azure Event Hubs - Public preview
If near-real time integration is something you are looking to implement and you were looking for a simpler way to get the data out of SQL, keep reading. SQL is making it easier to integrate and Change Event Streaming is a feature continuing this trend. Modern applications and analytics platforms increasingly rely on event-driven architectures and real-time data pipelines. As the businesses speed up, real time decisioning is becoming especially important. Traditionally, capturing changes from a relational database requires complex ETL jobs, periodic polling, or third-party tools. These approaches often consume significant cycles of the data source, introduce operational overhead, and pose challenges with scalability, especially if you need one data source to feed into multiple destinations. In this context, we are happy to release Change Event Streaming ("CES") feature into Public Preview for Azure SQL Database. This feature enables you to stream row-level changes - inserts, updates, and deletes - from your database directly to Azure Event Hubs in near real time. Change Event Streaming addresses the above challenges by: Reducing latency: Changes are streamed (pushed by SQL) as they happen. This is in contrast with traditional CDC (change data capture) or CT (change tracking) based approaches, where an external component needs to poll SQL at regular intervals. Traditional approaches allow you to increase polling frequency, but it gets difficult to find a sweet spot between minimal latency and minimal overhead due to too frequent polls. Simplifying architecture: No need for Change Data Capture (CDC), Change Tracking, custom polling or external connectors - SQL streams directly to configured destination. This means simpler security profile (fewer authentication points), fewer failure points, easier monitoring, lower skill bar to deploy and run the service. No need to worry about cleanup jobs, etc. SQL keeps track of which changes are successfully received by the destination, handles the retry logic and releases log truncation point. Finally, with CES you have fewer components to procure and get approved for production use. Decoupling: The integration is done on the database level. This eliminates the problem of dual writes - the changes are streamed at transaction boundaries, once your source of truth (the database) has saved the changes. You do not need to modify your app workloads to get the data streamed - you tap right onto the data layer - this is useful if your apps are dated and do not possess real-time integration capabilities. In case of some 3rd party apps, you may not even have an option to do anything other than database level integration, and CES makes it simpler. Also, the publishing database does not concern itself with the final destination for the data - Stream the data once to the common message bus, and you can consume it by multiple downstream systems, irrespective of their number or capacity - the (number of) consumers does not affect publishing load on the SQL side. Serving consumers is handled by the message bus, Azure Event Hubs, which is purpose built for high throughput data transfers. onceptually visualizing data flow from SQL Server, with an arrow towards Azure Event Hubs, from where a number of arrows point to different final destinations. Key Scenarios for CES Event-driven microservices: They need to exchange data, typically thru a common message bus. With CES, you can have automated data publishing from each of the microservices. This allows you to trigger business processes immediately when data changes. Real-time analytics: Stream operational data into platforms like Fabric Real Time Intelligence or Azure Stream Analytics for quick insights. Breaking down the monoliths: Typical monolithic systems with complex schemas, sitting on top of a single database can be broken down one piece at a time: create a new component (typically a microservice), set up the streaming from the relevant tables on the monolith database and tap into the stream by the new components. You can then test run the components, validate the results against the original monolith, and cutover when you build the confidence that the new component is stable. Cache and search index updates: Keep distributed caches and search indexes in sync without custom triggers. Data lake ingestion: Capture changes continuously into storage for incremental processing. Data availability: This is not a scenario per se, but the amount of data you can tap into for business process mining or intelligence in general goes up whenever you plug another database into the message bus. E.g. You plug in your eCommerce system to the message bus to integrate with Shipping providers, and consequently, the same data stream is immediately available for any other systems to tap into. How It Works CES uses transaction log-based capture to stream changes with minimal impact on your workload. Events are published in a structured JSON format following the CloudEvents standard, including operation type, primary key, and before/after values. You can configure CES to target Azure Event Hubs via AMQP or Kafka protocols. For details on configuration, message format, and FAQs, see the official documentation: Feature Overview CES: Frequently Asked Questions Get Started Public preview CES is available today in public preview for Azure SQL Database and as a preview feature in SQL Server 2025. Private preview CES is also available as a private preview for Azure SQL Managed Instance and Fabric SQL database: you can request to join the private preview by signing up here: https://aka.ms/sql-ces-signup We encourage you to try the feature out and start building real-time integrations on top of your existing data. We welcome your feedback—please share your experience through Azure Feedback portal or support channels. The comments below on this blog post will also be monitored, if you want to engage with us. Finally, CES team can be reached via email: sqlcesfeedback [at] microsoft [dot] com. Useful resources Free Azure SQL Database. Free Azure SQL Managed Instance.Azure SQL Database LTR Backup Immutability is now Generally Available
Azure SQL Database is a fully managed, always‑up‑to‑date relational database service built for mission‑critical apps. It delivers built‑in high availability, automated backups, and elastic scale, with strong security and compliance capabilities. Today, I am very excited to announce the General Availability of immutability for Azure SQL DB LTR backups! Azure SQL Database now supports immutable long‑term retention (LTR) backups, stored in write‑once, read‑many (WORM) state for a fixed (customer configured) period. That means your LTR backups cannot be modified or deleted during the lock window—even by highly privileged identities—helping you preserve clean restore points after a cyberattack and strengthen your compliance posture. Why this matters: ransomware targets backups Modern ransomware playbooks don’t stop at encrypting production data—they also attempt to alter or delete backups to block recovery. With backup immutability, Azure SQL Database LTR backups are written to immutable storage and locked for the duration you specify, providing a resilient, tamper‑proof recovery layer so you can restore from a known‑good copy when it matters most. What we’re announcing General Availability of Backup Immutability for Long‑Term Retention (LTR) backups in Azure SQL Database. This GA applies to Azure SQL database LTR backups. What immutability does (and doesn’t) do Prevents changes and deletion of LTR backup artifacts for a defined, locked period (WORM). This protection applies even to highly privileged identities, reducing the risk from compromised admin accounts or insider misuse. Helps address regulatory WORM expectations, supporting customers who must retain non‑erasable, non‑rewritable records (for example, requirements under SEC Rule 17a‑4(f), FINRA Rule 4511(c), and CFTC Rule 1.31(c)–(d)). Always consult your legal/compliance team for your specific obligations. Complements a defense‑in‑depth strategy—it’s not a replacement for identity hygiene, network controls, threat detection, and recovery drills. See Microsoft’s broader ransomware guidance for Azure. How it works (at a glance) When you enable immutability on an LTR policy, Azure SQL Database stores those LTR backups on Azure immutable storage in a WORM state. During the lock window, the backup cannot be modified or deleted; after the lock expires, normal retention/deletion applies per your policy. Key benefits Ransomware‑resilient recovery: Preserve clean restore points that attackers can’t tamper with during the lock period. Compliance‑ready retention: Use WORM‑style retention to help meet industry and regulatory expectations for non‑erasable, non‑rewritable storage. Operational simplicity: Manage immutability alongside your existing Azure SQL Database long‑term retention policies. Get started Choose databases that require immutable LTR backups. Enable immutability on the LTR backup policy and set the retention/lock period aligned to your regulatory and risk requirements. Validate recovery by restoring from an immutable LTR backup. Documentation: Learn more about backup immutability for LTR backups in Azure SQL Database in Microsoft Learn. Tell us what you think We’d love your feedback on scenarios, guidance, and tooling that would make immutable backups even easier to adopt. Share your experiences and suggestions in the Azure SQL community forums and let us know how immutability is helping your organization raise its cyber‑resilience.Convert geo-replicated databases to Hyperscale
Update: On 22 October 2025 we announced the General Availability for this improvement. We’re excited to introduce the next improvement in Hyperscale conversion: a new feature that allows customers to convert Azure SQL databases to Hyperscale by keeping active geo-replication or failover group configurations intact. This builds on our earlier improvements and directly addresses one of the most requested capabilities from customers. With this improvement, customers can now modernize your database architecture with Hyperscale while maintaining business continuity. Overview We have heard feedback from customers about possible improvements we could make while converting their databases to Hyperscale. Customers complained about the complex steps they needed to perform to convert a database to Hyperscale when the database is geo-replicated by active geo-replication or failover groups. Previously, converting to Hyperscale required tearing down geo-replication links and recreating them after the conversion. Now, that’s no longer necessary. This improvement allows customers to preserve their cross-region disaster recovery or read scale-out configurations and still allows conversion to Hyperscale which helps in minimizing downtime and operational complexity. This feature is especially valuable for applications that rely on failover group endpoints for connectivity. Before this improvement, if application needs to be available during conversion, then connection string needed modifications as a part of conversion because the failover group and its endpoints had to be removed. With this new improvement, the conversion process is optimized for minimal disruption, with telemetry showing majority of cutover times under one minute. Even with a geo-replication configuration in place, you can still choose between automatic and manual cutover modes, offering flexibility in scheduling the transition. Progress tracking is now more granular, giving customers better visibility into each stage of the conversion, including the conversion of the geo-secondary to Hyperscale. Customer feedback Throughout the preview phase, we have received overwhelmingly positive feedback from several customers about this improvement. Viktoriia Kuznetcova, Senior Automation Test Engineer from Nintex says: We needed a low-downtime way to move our databases from the Premium tier to Azure SQL Database Hyperscale, and this new feature delivered perfectly; allowing us to complete the migration in our test environments safely and smoothly, even while the service remained under continuous load, without any issues and without needing to break the failover group. We're looking forward to the public release so we can use it in production, where Hyperscale’s ability to scale storage both up and down will help us manage peak loads without overpaying for unused capacity. Get started The good news is that there are no changes needed to the conversion process. The workflow automatically detects that a geo-secondary is present and converts it to Hyperscale. There are no new parameters, and the method remains the same as the existing conversion process which works for non-geo-replicated databases. All you need is to make sure that: You have only one geo-secondary replica because Hyperscale doesn't support more than one geo-secondary replica. If a chained geo-replication configuration exists, it must be removed before starting the conversion to Hyperscale. Creating a geo-replica of a geo-replica (also known as "geo-replica chaining") isn't supported in Hyperscale. Once the above requirements are satisfied, you can use any of the following methods to initiate the conversion process. Conversion to Hyperscale must be initiated starting from the primary geo-replica. The following table provides sample commands to convert a database named WideWorldImporters on a logical server called contososerver to an 8-vcore Hyperscale database with manual cutover option. Method Command T-SQL ALTER DATABASE WideWorldImporters MODIFY (EDITION = 'Hyperscale', SERVICE_OBJECTIVE = 'HS_Gen5_8') WITH MANUAL_CUTOVER; PowerShell Set-AzSqlDatabase -ResourceGroupName "ResourceGroup01" -ServerName "contososerver" -DatabaseName "WideWorldImporters" -Edition "Hyperscale" -RequestedServiceObjectiveName "HS_Gen5_8" -ManualCutover Azure CLI az sql db update --resource-group ResourceGroup01 --server contososerver --name WideWorldImporters --edition Hyperscale --service-objective HS_Gen5_8 --manual-cutover Here are some notable details of this improvement: The geo-secondary database is automatically converted to Hyperscale with the same service level objective as the primary. All database configurations such as maintenance window, zone-resiliency, backup redundancy etc. remain the same as earlier (i.e., both geo-primary and geo-secondary would inherit from their own earlier configuration). A planned failover isn't possible while the conversion to Hyperscale is in progress. A forced failover is possible. However, depending on the state of the conversion when the forced failover occurs, the new geo-primary after failover might use either the Hyperscale service tier, or its original service tier. If the geo-secondary database is in an elastic pool before conversion, it is taken out of the pool and might need to be added back to a Hyperscale elastic pool separately after the conversion. This feature has been fully deployed across all Azure regions. In case you see error (Update to service objective '<SLO name>' with source DB geo-replicated is not supported for entity '<Database Name>') while converting primary to Hyperscale, we would like to hear from you. Do send us an email to the email ID give in next section. If you don’t want to use this capability, make sure to remove any geo-replication configuration before converting your databases to Hyperscale. Conclusion This update marks a significant step forward in the Hyperscale conversion process, offering simple steps, less downtime and keeping the geo-secondary available during the conversion process. We encourage you to try this capability and provide your valuable feedback and help us refine this feature. You can contact us by commenting on this blog post and we’ll be happy to get back to you. Alternatively, you can also email us at sqlhsfeedback AT microsoft DOT com. We are eager to hear from you all!
Removing barriers to migrating databases to Azure with Striim’s Unlimited Database Migration program
Alok Pareek, co-founder and Executive Vice President of Product and Engineering at Striim Shireesh Thota, Corporate Vice President of Databases at Microsoft Every modernization strategy starts with data. It’s what enables advanced analytics and AI agents today, and prepares enterprises for what’s to come in the future. But before services like Microsoft Fabric, Azure AI Foundry, or Copilot can create that value, the underlying data needs to move into Microsoft’s cloud platforms. It’s within that first step, database migration, where the real complexity often lies. To simplify the process, Microsoft has expanded its investment in the Striim partnership. Striim continuously replicates data from existing databases into Azure in real time, enabling online migrations with zero downtime. Through this partnership, we have collaborated to enable modernization and migration into Azure at no additional cost to our customers. We’ve designed this Unlimited Database Migration program to accelerate adoption by making migrations easier to start, easier to scale, and easier to complete, all without disrupting business operations. Since launch, this joint program has already driven significant growth in customer adoption, indicating the demand for faster, more seamless modernization. And with Microsoft’s continued investment in this partnership, enterprises now have a proven, repeatable path to modernize their databases and prepare their data for the AI era. Watch or listen to our recent podcast episode (Apple Podcasts, Spotify, YouTube) to learn more. Striim’s Unlimited Migration Program Striim’s Unlimited Database Migration Program was designed to make modernization as straightforward as possible for Microsoft customers. Through this initiative, enterprises gain unlimited Striim licenses to migrate as many databases as they need at no additional cost. Highlights and benefits of the program include: Zero-downtime, zero-data-loss migrations. Supported sources include SQL Server, MongoDB, Oracle, MySQL, PostgreSQL, and Sybase. Supported targets include Azure Database for MySQL, Azure Database for PostgreSQL, Azure Cosmos DB, and Azure SQL. Mission-critical, heterogeneous workloads supported. Applies for SQL, Oracle, NoSQL, OSS. Drives faster AI adoption. Once migrated, data is ready for analytics & AI. Access is streamlined through Microsoft’s Cloud Factory Accelerator team, which manages program enrollment and coordinates the distribution of licenses. Once onboarded, customers receive installation walkthroughs, an enablement kit, and direct support from Striim architects. Cutover support, hands-on labs, and escalation paths are all built in to help migrations run smoothly from start to finish. Enterprises can start migrations quickly, scale across business units, and keep projects moving without slowing down for procurement hurdles. Now, migrations can begin when the business is ready, not when budgets or contracts catch up. How Striim Powers Online Migrations Within Striim’s database migrations, schema changes and metadata evolution are automatically detected and applied, preserving data accuracy and referential integrity. As the migration progresses, Striim automatically coordinates both the initial bulk load of historical data and the ongoing synchronization of live transactions. This ongoing synchronization keeps source and target systems in sync for as long as needed to actively test the target applications with real data before doing the cutoff, thereby minimizing risk. However, the foundation of Striim’s approach is log-based Change Data Capture (CDC), which streams database changes in real time from source to target with sub-second latency. This helps migrations avoid just moving the static snapshot of a database. Rather, they continuously replicate every update as it happens, so both environments remain aligned with minimal impact on operational systems throughout the process. While the snapshot (initial load) is being applied to the target system, Striim captures all the changes that occur. Once the initial load process is complete, Striim applies the changes using CDC, and from this point on, the source and target systems are in sync. This eliminates the need for shutting down the source system during the initial load process and enables customers to complete their migrations without any downtime of the source database. Striim is also designed to work across hybrid and multi-cloud architectures. It can seamlessly move workloads from on-premises databases, SaaS applications, or other clouds into Microsoft databases. By maintaining exactly-once delivery and ensuring downstream systems stay in sync, Striim can reduce risk and accelerates the path to modernization. Striim is available in the Azure Marketplace, giving customers a native, supported way to integrate it directly into their Azure environment. This means migrations can be deployed quickly, governed centrally, and scaled as business needs evolve, all while still aligning with Azure’s security and compliance standards. From Migration to Value With workloads fully landed in Azure, enterprises can immediately take advantage of the broader Microsoft data ecosystem. Fabric, Azure AI Foundry, and Copilot become available as extensions of the database foundation, allowing teams to analyze, visualize, and enrich data without delay. Enterprises can begin adopting Microsoft AI services with data that is current, trusted, and governed. Instead of treating migration as an isolated project, customers gain an integrated pathway to analytics and AI, creating value as soon as databases go live in Azure. How Enterprises Are Using the Program Today Across industries, we’re already seeing how this program changes the way enterprises approach modernization. Financial Services Moving from Oracle to Azure SQL, one global bank used Striim to keep systems in sync throughout the migration. With transactions flowing in real time, they stood up a modern fraud detection pipeline on Azure that identifies risks as they happen. Logistics For a logistics provider, shifting package-tracking data from MongoDB to Azure Cosmos DB meant customers could monitor shipments in real time. Striim’s continuous replication kept data consistent throughout the cutover, so the company didn’t have to trade accuracy for speed. Healthcare A provider modernizing electronic medical records from Sybase to Azure SQL relied on Striim to ensure clinicians never lost access. With data now in Azure, they can meet compliance requirements while building analytics that improve patient care. Technology InfoCert, a leading provider of digital trust services specializing in secure digital identity solutions, opted to migrate its critical Legalmail Enterprise application from Oracle to Azure Database for PostgreSQL. Using Striim and Microsoft, they successfully migrated 2 TB of data across 12 databases and completed the project within a six-month timeframe, lowering licensing costs, enhancing scalability, and improving security. What unites these stories is a common thread: once data is in Azure, it becomes part of a foundation that’s ready for analytics and AI. Accelerate Your Path to Azure Now, instead of database migration being the bottleneck for modernization, it’s the starting point for what comes next. With the Unlimited Database Migration Program, Microsoft and Striim have created a path that removes friction and clears the way for innovation. Most customers can simply reach out to their Microsoft account team or seller to begin the process. Your Microsoft representative will validate that your migration scenario is supported by Striim, and Striim will allocate the licenses, provide installation guidance, and deliver ongoing support. If you’re unsure who your Microsoft contact is, you can connect directly with Striim, and we’ll coordinate with Microsoft on your behalf. There’s no lengthy procurement cycle or complex setup to navigate. With Microsoft and Striim jointly coordinating the program, enterprises can begin migrations as soon as they’re ready, with confidence that support is in place from start to finish. Simplify your migration and move forward with confidence. Talk to your Microsoft representative or book a call with Striim team today to take advantage of the Unlimited Database Migration Program and start realizing the value of Azure sooner. Or if you’re attending Microsoft Ignite, visit Striim at booth 6244 to learn more, ask questions, and see how Striim and Microsoft can help accelerate your modernization journey together.
Announcing Public Preview: Auditing for Fabric SQL Database
We’re excited to announce the public preview of Auditing for Fabric SQL Database—a powerful feature designed to help organizations strengthen security, ensure compliance, and gain deep operational insights into their data environments. Why Auditing Matters Auditing is a cornerstone of data governance. With Fabric SQL Database auditing, you can now easily track and log database activities—answering critical questions like who accessed what data, when, and how. This supports compliance requirements (such as HIPAA and SOX), enables robust threat detection, and provides a foundation for forensic investigations. Key Highlights Flexible Configuration: Choose from default “audit everything,” preconfigured scenarios (like permission changes, login attempts, data reads/writes, schema changes), or define custom action groups and predicate filters for advanced needs. Seamless Access: Audit logs are stored in One Lake, making them easily accessible via T-SQL or One Lake Explorer. Role-Based Access Control: Configuration and log access are governed by both Fabric workspace roles and SQL-level permissions, ensuring only authorized users can view or manage audit data. Retention Settings: Customize how long audit logs are retained to meet your organization’s policy. How It Works Audit logs are written to a secure, read-only folder in One Lake and can be queried using the sys. fn_get_audit_file_v2 T-SQL function. Workspace and artifact IDs are used as identifiers, ensuring logs remain consistent even if databases move across logical servers. Access controls at both the workspace and SQL database level ensure only the right people can configure or view audit logs. Example Use Cases Compliance Monitoring: Validate a full audit trail for regulatory requirements. Security Investigations: Track specific events like permission changes or failed login attempts. Operational Insights: Focus on specific operations (e.g., DML only) or test retention policies. Role-Based Access: Verify audit visibility across different user roles. Getting Started You can configure auditing directly from the Manage SQL Auditing blade in the Fabric Portal. Choose your preferred scenario, set retention, and (optionally) define custom filters—all through a simple, intuitive interface. Learn more about auditing for Fabric SQL database here Data exposed session with demo here
