Building an Azure architecture that’s ready for every signature
At Exclaimer, we help organizations manage email signatures at scale, so every message can carry a consistent, compliant, on-brand signature without IT teams manually updating thousands of mailboxes. This is more difficult than it may seem, especially when you're doing it for more than 80,000 customers, around 9.6 million seats, and more than 21 billion emails a year. Every signature must show up in the right place, with the right details, for the right sender, recipient, device, and business rule. Behind that are constantly changing employee records, customer-specific policies, email chains, recipient lists, regional disclaimers, and brand requirements. Because our platform sits directly in the email flow, availability is critical. And because many of our customers operate in regulated industries, they also need confidence that data stays in-region and configured signatures are applied consistently. To support that level of scale and reliability, we’ve spent the last several years evolving our architecture on Microsoft Azure. Today, Azure Kubernetes Service (AKS), Azure SQL Database, Azure Database for PostgreSQL, Azure Cosmos DB, Azure Data Explorer, and Azure Databricks help us run a global platform that’s more responsive, more resilient, and more cost-efficient. Reading the signs that our architecture needed to change In the beginning, our cloud product ran more like a multi-server, on-premises product hosted on Azure Virtual Machines (VMs). The platform was split into a smaller number of core services, and the team relied heavily on VM-based infrastructure to keep those services running. As Exclaimer grew, our architecture had to keep pace with higher volumes, more regions, and more complex customer requirements. Regional demand shifted throughout the day, but scaling infrastructure up and down still relied on scripts, pre-baked VMs, and operational coordination. That created more risk during maintenance and failover. We run parallel data centers in regional pairs so we can move traffic away from one site when needed. But when traffic moves, the receiving environment has to be ready to handle the full load. In the VM world, that meant someone or something had to remember to scale up standby resources at the right moment. At the same time, our product was becoming more service-oriented. We were moving away from a smaller set of larger services toward well over 100 microservices. Every new service created more conversations about VM sizing, images, patching, and operational overhead. It was time for a model that could scale faster, run more efficiently, and reduce the amount of infrastructure work required to ship and operate the product. Signing on to AKS for faster, more efficient scaling By moving many workloads to Linux containers on AKS, we gained a smaller footprint, faster startup times, and a more consistent way to package and deploy services. AKS also gave us a managed Kubernetes foundation for running those containers at global scale, with autoscaling capabilities that better matched our traffic patterns. With Horizontal Pod Autoscaler, services can react to load in seconds rather than minutes. With Cluster Autoscaler, we can add or remove node capacity based on what the platform actually needs. That means we can pack workloads onto nodes more efficiently, scale down during quiet periods, and scale up quickly when demand returns. The operational difference is just as important. During an incident, maintenance event, or regional failover, our teams have fewer manual steps to think about. If traffic shifts, the platform can scale with it. That takes away one more thing for engineers to worry about when they should be focused on keeping the customer experience steady. The move to containers and a more streamlined CI/CD workflow also improved our deployment cadence by making it easier to build, test, and deploy changes across the platform. In 2021, we deployed 285 changes, features, and fixes to production over the course of the entire year. Today, we deploy that many every few days. Cost has improved, too. Since 2024, when the bulk of our migration to containerized services took place, we’ve reduced our average cost per user by about 39 percent, even as the product has grown more complex and we’ve added more capabilities for customers. We achieved that through a combination of containerized architecture, AKS autoscaling, and expanded reservations across compute and storage technologies. Choosing the right database for the right kind of data We started with a strong Microsoft SQL Server foundation, and Azure SQL Database remains core to our platform today. It stores critical customer configuration data and continues to give us the reliability, replication, resizing flexibility, and regional scale we need. But not every workload belongs in the same database. Customer configuration, relational service data, key-value storage, usage events, and business intelligence (BI) all have different access patterns. That principle led us to Azure Database for PostgreSQL flexible server for one of our most important migrations. We had used Azure Table storage for a core service that needed to retrieve customer data quickly. It was cost-effective and stable for a long time, but as the product evolved, the data became more relational, and we found ourselves adding complexity in application code that a relational database could handle more naturally. Azure Database for PostgreSQL gave us that relational model with low management overhead, fast read replicas, reserved instances for predictable workloads, and a path to future scale. After the migration, average request time for a critical service dropped from 18.6 milliseconds to 1.79 milliseconds. That’s a 90 percent improvement across a service that handles around 9 billion requests each month. Azure Cosmos DB plays a different role, supporting key-value and document storage where we need scale, availability, low latency, encryption at rest, and straightforward dev/test support. Optimized for unstructured data and high-performance reads and writes, it gives us a highly scalable foundation for workloads that don't fit a traditional relational model. We use it to store customer assets for signatures and video branding, high-volume metadata for internal message-processing operations, audit events that help customers track account changes, and tokens used to collect data from third-party systems on behalf of customers. It also gives us a clean way to keep data and services aligned. Azure Data Explorer solved another scaling challenge: usage and billing data. We need to be able to audit the number of messages we process for our customers so we can bill accurately, and at more than 20 billion emails a year, our previous SQL-based usage pipeline became difficult to manage. With Azure Data Explorer, we can ingest massive volumes of event data at low storage cost, connect to Azure Event Hubs, and avoid maintaining custom plumbing. That move reduced the cost of the system by around 70 percent. Azure Databricks rounds out the picture as our BI and data platform, giving our teams a shared foundation for transformations, analysis, and reporting across product and business data. Keeping every region ready for business Our customers are everywhere, so our platform has to be, too. Exclaimer runs in seven distinct geographic locations: Australia, Canada, Europe, Germany, the United Arab Emirates, the United Kingdom, and the United States. That global footprint helps us meet customer expectations around availability and data residency. Many organizations want their data to stay in-region, and Azure gives us the coverage we need to support that. Availability is especially important because our platform is part of a live communication flow. When someone sends an email, they expect it to keep moving. Our Azure architecture helps us support that expectation across the stack. AKS lets compute scale with regional demand. Azure SQL and Azure Database for PostgreSQL support critical relational workloads. Azure Cosmos DB gives us scalable, low-latency storage for document and key-value patterns. Azure Data Explorer handles very high-volume usage ingestion without the complexity of our former custom pipeline. Across the board, these managed Azure services reduce the amount of operational work our engineers have to carry. We can spend less time maintaining the basics and more time tuning performance, improving stability, and building the capabilities our customers need next. Building for the future on a stronger foundation The biggest sign that our architecture is working may be how little we have to reinvent when we build something new. As we develop upcoming product capabilities, we already have many of the foundational pieces in place: AKS for compute, Azure Cosmos DB for state, and Azure Service Bus for messaging. We also have Azure SQL for core data, Azure Database for PostgreSQL where relational service data needs room to scale, Azure Data Explorer for high-volume event analysis, and Azure Databricks for BI tooling. Together, these services make our platform faster, more efficient, and more resilient. Email signatures may look simple on the surface. Behind every one, there’s a set of decisions about performance, scale, data, availability, and trust. With Azure, we’ve built an architecture that helps us keep every signature moving, wherever our customers do business. About the authors Phil Vetter started in engineering at Exclaimer as a developer at the start of 2013, and now sits at the helm as VP of Engineering. Lee Jones started at Exclaimer in 2013 in the IT department, and now serves as Director of Platform Engineering, managing the infrastructure and resilience of Exclaimer Cloud.Generally Available: SQL Migration to SQL Server on Azure Virtual Machines in Azure Architecture
One Migration Experience, More Flexibility Modernizing SQL Server estates is rarely a single-step journey. Organizations often operate across on-premises, hybrid, and cloud environments while balancing application dependencies, operational requirements, and modernization goals. SQL Server migration enabled by Azure Arc simplifies this process by bringing migration activities into a single experience in the Azure portal. With the July 2026 release, we are announcing General Availability of SQL Server on Azure Virtual Machines as a migration target in Azure Arc, allowing customers to have a greater flexibility to choose Azure destination that best aligns with to your needs without introducing additional tools or migration processes. Whether migrating to the fully managed Azure SQL Managed Instance service or to SQL Server running on Azure VMs, the experience remains consistent and familiar. Unified Migration Workflow A key benefit of SQL Server migration enabled by Azure Arc is that the entire migration lifecycle is managed from a single tool in Azure portal. After a SQL Server instance is enabled by Azure Arc, customers can: Assess migration readiness Select a migration target Configure migration settings Monitor migration progress Validate results Perform final cutover All of these activities are performed directly from the Azure portal using a guided workflow designed to simplify migration planning and execution. The prerequisite remains unchanged: source SQL Server instances must be enabled by Azure Arc before migration can begin. The result is a flexible, scalable, and consistent migration experience that supports hybrid realities, reduces operational overhead, and helps customers modernize SQL Server estates at their own pace. Consistent Experience Across Azure SQL Targets Migration to SQL Server on Azure Virtual Machines follows the same operational model already available for Azure SQL Managed Instance migration scenarios. Customers use the same migration dashboard, monitoring experience, and guided workflow regardless of the destination. This consistency reduces learning curves, simplifies operational processes, and enables teams to select the most appropriate Azure SQL platform without changing migration methodology. Online Migration Using Backup and Log Shipping Migration to SQL Server on Azure Virtual Machines uses backup and restore with log shipping to support online migration scenarios while minimizing downtime. The process begins with a full database backup that is restored to the target SQL Server instance running on an Azure Virtual Machine. Transaction log backups that are uploaded continuously by your workflows to Azure Blob Storage are continuously applied to the target database, keeping it closely synchronized with the source environment. Azure Blob Storage serves as the intermediary staging location between source and target systems. To support efficient data movement and restore operations, both the Azure Blob Storage account and the target SQL Server on Azure Virtual Machines must reside in the same Azure region. Within the Azure Arc migration experience, customers select the Azure Blob Storage container that stores the backup files. Azure Arc automatically restores the full backup and continuously applies transaction log backups as they become available. Customers are responsible for configuring and maintaining the continuous upload of transaction log backups to Azure Blob Storage. Customer-Controlled Cutover When the customer is ready to complete migration, upon customer initiated cutover, Azure Arc performs the final synchronization by applying the last uploaded backup and bringing the target database online. This approach gives organizations full control over the migration timeline and cutover window, allowing downtime to be planned according to business requirements while reducing operational complexity. Learn More To learn more about SQL Server migration enabled by Azure Arc, see: Migration Overview For information about migrating to SQL Server in Azure VM, see: Migrate to SQL Server in Azure VMAzure SQL is Retiring the “No Minimum TLS” (MinTLS None) Configuration
As part of the retirement of lower TLS versions 1.0 and 1.1 and the enforcement of 1.2 as the new default minimum TLS version, we will be removing the No Minimum TLS (MinTLS = “None” or "0") option and updating these configurations to TLS 1.2. No Minimum TLS allowed Azure SQL Database and Azure SQL Managed Instance resources to accept client connections using any TLS protocol version and unencrypted connections. Over the past year, Azure has retired TLS 1.0 and 1.1 for all Azure databases, due to known security vulnerabilities in these older protocols. As of August 31, 2025, creating servers configured with versions 1.0 and 1.1 was disallowed and migration to 1.2 began. With legacy TLS versions being retired, TLS 1.2 will become the secure default minimum TLS version for new Azure SQL DB and MI configurations and for all client-server connections. As a result, the MinTLS = None configuration option will default to 1.2, and existing servers configured with No Minimum TLS will need to connect using 1.2 or higher. Update (July 16, 2026): This blog post has been updated to clarify the expected configuration behavior associated with the minimum TLS 1.0 retirement. The content below reflects the latest guidance. What is changing? Creating new Azure SQL Database and Managed Instance servers with MinTLS = None previously allowed any TLS version and unencrypted connections. After July 31, 2026, we will change the default behavior of the minimum TLS value "None", for the creation of new SQL DB and MI resources using PowerShell, Azure CLI, and any other REST based interface. This configuration option has been removed from the Portal as part of the retirement of TLS versions 1.0 and 1.1. Attempts to CREATE or UPDATE an Azure SQL server with MinTLS = None will default to connecting with TLS 1.2. If the server parameter value for the minimum TLS is left blank, it will default to minimum TLS version 1.2. Attempts to connect with TLS 1.0, 1.1 or unencrypted connections will fail with “Error: 47072/171 on Gateway.” Effective date (retirement milestone) MinTLS = None (0) MinTLS left blank (defaults to supported minimum) Before 8/31/25 Any + Unencrypted Any + Unencrypted After 8/31/25 1.2 + Unencrypted 1.2 After July 31, 2026 1.2 TLS error: 47072/171 (for unencrypted connections) 1.2 In summary, after July 31, 2026, Azure SQL Database and Azure SQL Managed Instance will require all client connections to use TLS 1.2 or higher and unencrypted connections will be denied. The minimum TLS version setting will no longer accept the value "None" for new or existing servers and servers currently configured with this value will be upgraded to explicitly enforce TLS 1.2. Who is impacted? For most Azure SQL customers, there is no action required. Most clients already use TLS 1.2 or higher. After July 31, 2026, if your Azure SQL Database or Managed Instance is still configured with No Minimum TLS and using 1.0, 1.1 or unencrypted connections, it will automatically update to TLS 1.2 to reflect the current minimum protocol enforcement in client-server connectivity. We do recommend you verify your client applications – especially any older or third-party client drivers – to ensure they can communicate with TLS 1.2 or above. In some rare cases, very old applications, such as an outdated JDBC driver or older .NET framework version, may need an update or need to enable TLS 1.2. Conclusion This retirement is part of Azure’s broader security strategy to ensure encrypted connections are secure by modern encryption standards. TLS version 1.2 is more secure than older versions and is now the industry standard (required by regulations like PCI DSS and HIPAA). This change eliminates the use of unencrypted connections which ensure all database connections meet current security standards. If you’ve already migrated to TLS 1.2 (as most customers have), you will most likely not notice any change, except that the No Minimum TLS option will disappear from configurations.
Azure SQL Firewall / Locks
Hi there, I have 2 environments. I'm more of admin on Azure environment (recently made as subscription admin) after which Dev issue - Azure SQL I'm having difficulty to remove IP from Azure SQL Firewall. (Earlier i was able to) today my manager granted me subscription admin and as SQL Security Manager and it still not able to remove grayed out IPs.Lessons Learned #545:Understanding client_ip = 0.0.0.0 in Azure SQL Auditing
During my analysis, I reproduced the same behavior in a test environment using a client connection to Azure SQL Database through a Microsoft.Sql Virtual Network Service Endpoint . After enabling Azure SQL Auditing and reviewing the original Azure SQL Database Audit file (.xel), the connection was also recorded with client_ip = 0.0.0.0. This confirms that 0.0.0.0 can represent a valid client connection using a Service Endpoint and should not automatically be interpreted as internal Azure platform. When the original client IP is not exposed, one of the best ways to identify the originating application is to configure a meaningful Application Name property in the SQL connection string:Application Name=Customer-Production; Therefore, when reviewing Azure SQL audit records with client_ip = 0.0.0.0, check the original .xel audit file and use the application_name, host_name, authenticated principal, database name, and timestamp to correlate the activity with the correct application.Generally Available: SQL Migration to SQL Server on Azure Virtual Machines in Azure Architecture
One Migration Experience, More Flexibility Modernizing SQL Server estates is rarely a single-step journey. Organizations often operate across on-premises, hybrid, and cloud environments while balancing application dependencies, operational requirements, and modernization goals. SQL Server migration enabled by Azure Arc simplifies this process by bringing migration activities into a single experience in the Azure portal. With the July 2026 release, we are announcing General Availability of SQL Server on Azure Virtual Machines as a migration target in Azure Arc, allowing customers to have a greater flexibility to choose Azure destination that best aligns with to your needs without introducing additional tools or migration processes. Whether migrating to the fully managed Azure SQL Managed Instance service or to SQL Server running on Azure VMs, the experience remains consistent and familiar. Unified Migration Workflow A key benefit of SQL Server migration enabled by Azure Arc is that the entire migration lifecycle is managed from a single tool in Azure portal. After a SQL Server instance is enabled by Azure Arc, customers can: Assess migration readiness Select a migration target Configure migration settings Monitor migration progress Validate results Perform final cutover All of these activities are performed directly from the Azure portal using a guided workflow designed to simplify migration planning and execution. The prerequisite remains unchanged: source SQL Server instances must be enabled by Azure Arc before migration can begin. The result is a flexible, scalable, and consistent migration experience that supports hybrid realities, reduces operational overhead, and helps customers modernize SQL Server estates at their own pace. Consistent Experience Across Azure SQL Targets Migration to SQL Server on Azure Virtual Machines follows the same operational model already available for Azure SQL Managed Instance migration scenarios. Customers use the same migration dashboard, monitoring experience, and guided workflow regardless of the destination. This consistency reduces learning curves, simplifies operational processes, and enables teams to select the most appropriate Azure SQL platform without changing migration methodology. Online Migration Using Backup and Log Shipping Migration to SQL Server on Azure Virtual Machines uses backup and restore with log shipping to support online migration scenarios while minimizing downtime. The process begins with a full database backup that is restored to the target SQL Server instance running on an Azure Virtual Machine. Transaction log backups that are uploaded continuously by your workflows to Azure Blob Storage are continuously applied to the target database, keeping it closely synchronized with the source environment. Azure Blob Storage serves as the intermediary staging location between source and target systems. To support efficient data movement and restore operations, both the Azure Blob Storage account and the target SQL Server on Azure Virtual Machines must reside in the same Azure region. Within the Azure Arc migration experience, customers select the Azure Blob Storage container that stores the backup files. Azure Arc automatically restores the full backup and continuously applies transaction log backups as they become available. Customers are responsible for configuring and maintaining the continuous upload of transaction log backups to Azure Blob Storage. Customer-Controlled Cutover When the customer is ready to complete migration, upon customer initiated cutover, Azure Arc performs the final synchronization by applying the last uploaded backup and bringing the target database online. This approach gives organizations full control over the migration timeline and cutover window, allowing downtime to be planned according to business requirements while reducing operational complexity. Learn More To learn more about SQL Server migration enabled by Azure Arc, see: Migration Overview For information about migrating to SQL Server in Azure VM, see: Migrate to SQL Server in Azure VMLessons Learned #544: How to Detect INT Identity Exhaustion Before Inserts Fail.
Recently, I worked on a support case involving an Azure SQL Database table where the customer had reached the maximum value supported by the INT data type. The table used an INT IDENTITY(1,1) column as its primary key. Over time, the generated identity value approached the maximum value supported by INT. Once the available range was exhausted, the application was no longer able to insert new rows. At that point, the column needed to be changed from INT to BIGINT. However, performing this type of migration on a very large table can be a complex and time-consuming operation. The situation is that an INT column uses 4 bytes and supports values from: -2,147,483,648 to: 2,147,483,647. To prevent similar problems in the future, I suggested using the following query to review the current status of all INT IDENTITY columns in the database. The query uses the sys.identity_columns catalog view: SELECT s.name AS SchemaName, t.name AS TableName, c.name AS ColumnName, CONVERT(bigint, c.last_value) AS CurrentIdentityValue, CONVERT(bigint, 2147483647) AS MaximumIntValue, CONVERT(bigint, 2147483647) - ISNULL(CONVERT(bigint, c.last_value), 0) AS RemainingValues, CAST( ISNULL(CONVERT(decimal(20,2), c.last_value), 0) / 2147483647 * 100 AS decimal(6,2) ) AS PercentUsed FROM sys.identity_columns AS c INNER JOIN sys.tables AS t ON c.object_id = t.object_id INNER JOIN sys.schemas AS s ON t.schema_id = s.schema_id WHERE TYPE_NAME(c.system_type_id) = 'int' ORDER BY PercentUsed DESC; I prefer using this query instead of relying on: SELECT COUNT(*) FROM dbo.TableName. The number of rows in a table does not necessarily match the current identity value. Rows might have been deleted, transactions might have been rolled back, and identity values might contain gaps. For this reason, the current identity value is a better indicator of the remaining capacity. Adding this query as a regular preventive check can help identify identity columns that are approaching their limits before they cause application failures. I would like to share with you an example creates a table with an identity seed close to the maximum value supported by INT: DROP TABLE IF EXISTS dbo.IdentityCapacityDemo2; CREATE TABLE dbo.IdentityCapacityDemo2 ( Id INT IDENTITY(2147483600,1) NOT NULL, CreatedDate datetime2(0) NOT NULL CONSTRAINT DF_IdentityCapacityDemo2_CreatedDate DEFAULT SYSUTCDATETIME(), CONSTRAINT PK_IdentityCapacityDemo2 PRIMARY KEY CLUSTERED (Id) ) Insert 20 rows using this command: insert into IdentityCapacityDemo2(CreatedDate) values(SYSUTCDATETIME()) Example of returns: I think runnning this preventive check can help detect identity exhaustion before it affects the application.Lessons Learned #543: Evaluating MultiSubnetFailover with Azure SQL Database
Last week, I worked on a support case in which the use of the MultiSubnetFailover connection-string feature was being considered for an application connecting to Azure SQL Database. The expectation was that enabling the following option could improve connection recovery during a database failover changing MultiSubnetFailover to True. This option is commonly associated with SQL Server high availability, and Azure SQL Database is also designed to remain available by moving databases between replicas when required. However, after reviewing the Azure SQL Database connectivity architecture and comparing the behavior with the property enabled and disabled, I did not observe a clear improvement. The property could be added to the connection string without generating an error, and the application was able to connect successfully with both configurations. What MultiSubnetFailover is designed for MultiSubnetFailover was introduced primarily for SQL Server high-availability configurations such as: Always On Availability Group listeners. SQL Server Failover Cluster Instance virtual network names. In a multi-subnet Availability Group, a listener name may resolve to multiple IP addresses located in different network subnets. Without MultiSubnetFailover=True, the application may try those addresses sequentially. If the first address is not currently active, the connection can be delayed while the attempt waits for a timeout. When the option is enabled, supported SQL client drivers can attempt connections to the listener addresses in parallel and use the first address that responds successfully. This can reduce connection time after an Availability Group failover because the SQL client is directly involved in selecting the reachable listener address. Why Azure SQL Database is different Azure SQL Database uses a different connectivity architecture. The application connects to a logical server endpoint: <server-name>.database.windows.net. The Azure SQL connectivity layer receives the connection and routes it to the infrastructure currently hosting the database. Depending on the configured connection policy, the Azure SQL gateway either proxies the connection or redirects the application to the appropriate database node. The important difference is that the SQL client does not receive a list containing the IP addresses of the Azure SQL Database primary and secondary replicas. The decision and the associated routing are managed by the Azure SQL Database platform. Although Azure SQL Database internally uses multiple replicas for high availability, this is not the same connectivity model as a SQL Server Availability Group listener that publishes multiple addresses through DNS. What about Failover Groups? Azure SQL Database Failover Groups provide a stable listener endpoint such as: <failover-group-name>.database.windows.net. Following a regional failover, the listener is updated so that it points to the logical server hosting the new primary databases. This process depends partly on DNS. The listener name remains the same, but its DNS target changes after the failover. This is still different from a SQL Server multi-subnet Availability Group listener. The Failover Group listener does not expose the addresses of the Azure SQL Database replicas to the SQL client. Therefore, MultiSubnetFailover=True cannot directly select the new primary replica. In this scenario, application recovery continues to depend on the service transition, DNS resolution, and retry behavior. The importance of retry logic One of the main lessons from this case was that retry logic is more relevant to Azure SQL Database resiliency than enabling MultiSubnetFailover. An application connecting to Azure SQL Database must expect occasional transient connectivity errors. These can occur during maintenance, scaling, failover, network interruptions, or temporary service conditions. An appropriate retry strategy should normally include: A limited number of retry attempts. A short delay before the first retry. Increasing delays between subsequent attempts. A maximum retry interval. Creation of a fresh SQL connection. For transactions, retry logic requires additional care. The application must determine whether the transaction was committed, rolled back, or left in an unknown state before repeating the complete operation.Azure SQL DB Fabric Mirroring with Private Endpoint
Introduction Overview steps for configuration of Mirroring between Azure SQL Database to Fabric Mirrored Database over Private Endpoint and Public Connectivity Disabled on source. Prerequisites #1 - The minimum requirement for the source Azure SQL Database tier is - it is Standard Tier with DTUs equal or greater than 100. Free, Basic Tier, or <100 DTUs are NOT supported. All vCore model tiers supported. #2 - System Assigned Managed Identity (SAMI) must be enabled on the Azure SQL logical server. #3 - Microsoft.PowerPlatform should be registered as a source provider at the subscription level. If this step is not completed, you'll face error in the next steps, while creating the 'Virtual Network Data Gateway', example below. #4 - The Virtual Network Subnet of the configured Private Endpoint should have the following selected. Select Microsoft.PowerPlatform/netaccesslinks for the Subnet Delegation tab. This is a required step, otherwise the subnet is grayed out to select while configuration of the Virtual Network Data Gateway at Fabric level. High Level Configuration Steps #1 - Go to Fabric Portal > Settings Click on Settings button on top right > Click on Manage Connections and Gateways Go to 'Virtual Network Data Gateway' tab > Click New In the new page, Select your Capacity, Subscription, Resource Group, VNET and Subnet of the source Azure SQL DB and create it. #2 - Go back to your workspace, and click new item > Search 'Mirrored Azure SQL Database' #3 - Here, in Data Gateway section, chose your new created gateway which we created in previous step, and fill the required source Azure SQL Database details and click connect. #4 - Select the tables to be mirrored in the next steps and you will be able to successfully mirror from Azure SQL Database to Mirrored Azure SQL Database without Public Connectivity and using Private Endpoint.3 Reasons Enterprise SQL Server Migrations Slow Down - and How to Avoid Them
Summary Many of Enterprises around the globe have relied on SQL Server for over 3 decades to run their mission critical business applications. Their SQL Server estates face pressure from downtime risk, cost volatility, end of support timelines and modernization demands. As these customers get ready to modernize their data to use the latest capabilities of A.I and cloud native application trends, they want to migrate and modernize their SQL Servers to use Azure SQL with a modernization strategy built on confidence of customer success. Enterprise migrations rarely fail because of migration tools. They slow down because organizations struggle to answer three questions: How much downtime can we tolerate? What will it cost after migration? Are we choosing the right target platform? The organizations that answer these questions early move faster and with less risk. For the DB Administrators, Data architects, application architect and cloud-cost decision makers there are important technical considerations before, during and after data modernization to avoid long term costs and operational concerns. The Microsoft SQL Team has helped many customers modernize their SQL. We discuss important guidelines that can help resolve the 3 major concerns that block or slow SQL Server migration and modernization in Enterprises. This is covered in the episode of DataExposed for which this companion blog goes into the details. What are important triggers that cause customers and partners to consider SQL modernization? There are many business triggers that force Enterprises to migrate their data to public cloud. As SQL Server 2012 to SQL Server 2016 are already in the end of support stage of their lifecycle, customers need to upgrade SQL Server in place or migrate to AzureSQL. Due to cyber security threats, customers are feeling more vulnerable to attackers. Moving their data into a secure environment is essential for protecting not just their data but their business. Customers are reporting the need to free up IT dollars to invest into other parts of the business that may need it more. These may be anything from datacenter contract expirations, need for Hardware refreshes to software license renewals. As the business grows or becomes cyclical, there is surge in demand. Capacity constraints become a barrier for such expansions. These are triggers that cause them to rethink their data modernization strategy. Data modernization and moving the data to a elastic, scalable, secure and resilient data platform such as Azure SQL, becomes essential. The Three Migration Blockers However, data modernization and migration is not without any risk. Based on our customers experience, here are three key reasons that we have commonly encountered that halt or slow down SQL modernization. 1. Downtime Risk Business stakeholders often require strict service level commitments before authorizing production cutovers. Even when migrations are technically feasible, organizations may delay projects if they believe downtime windows could impact revenue, customer experience, or regulatory obligations. Most customers are still offered offline migration paths which can take hours to days, even though zero-downtime migrations are possible which take seconds to minutes. 2. Cost uncertainty Many modernization projects are approved based on expected cost savings. However, if infrastructure sizing, licensing assumptions, storage consumption, or disaster recovery requirements are not evaluated properly, the actual operational cost can exceed initial expectations. Cost uncertainty often slows executive approval processes and extends migration timelines. 3. Compatibility and Feature Fit When migrating SQL Server, Azure SQL has several deployment offerings from IaaS to PaaS. These include SQL Server on Azure VM, Azure SQL Managed Instance, Azure SQL DB Hyperscale and Azure SQL in Microsoft Fabric. Many customers maybe using SQL Server features like Cross-database queries, CLR, SSIS, SQL Agent, and linked servers. They make a safe decision to lift and shift migrate to SQL Server on Azure VMs IaaS instead of modernizing to a PaaS service like Azure SQL Managed Instance. However, in the process, they lose the opportunity to use the PaaS capabilities, manageability and AI/Fabric capabilities in Azure by making this choice. Enterprise Architects, Application Architects, Database developers and DB Administrators have to make the right choice taking both development as well as operational costs and compatibility when they make their SQL modernization decisions. Here are best practices some of the biggest and successful SQL migrations have used to make the migration and modernization journey with confidence. While we cannot disclose specific customer names, these guidelines are based on helping many large to small Enterprise customers. Azure SQL Managed Instance as the Resiliency Anchor Azure SQL Managed Instance is often the platform that helps organizations overcome all three concerns simultaneously because it combines near-full SQL Server compatibility with platform-as-a-service benefits. Azure SQL Managed Instance (Azure SQL MI) Next-gen General Purpose is now generally available, bringing a built-in performance and scale upgrade for General Purpose workloads, including up to 500 databases per instance, up to 32 TB storage, lower latency, and higher IOPS. The release also adds more flexible cost-performance tuning with independent vCore, IOPS, and memory scaling, plus faster management operations to adapt to changing workload demand. For enterprise SQL Server modernization, this positions Azure SQL MI as a stronger path for high-compatibility migrations that need better price-performance without moving to a full replatform. Let us dive deeper into how this helps address the downtime risk concerns by enables three levels of resiliency and high availability features. Local Redundancy Azure SQL Managed Instance provides first layer of Local Redundancy — built into every Azure SQL MI instance at no extra cost. Azure SQL Managed Instance uses local redundancy by default to keep workloads available during node, VM, rack, maintenance, and other local failures within a single datacenter, with Service Fabric orchestrating failover. In General Purpose (including Next-gen GP), this is implemented as stateless compute plus remote stateful storage; during failover, the engine process moves to another compute node and reattaches data, which can cause temporary performance impact due to cold cache. In Business Critical, local redundancy uses multiple synchronized replicas with local SSD storage (Always On-like architecture), enabling fast failover and read scale-out on secondaries.Next-gen General Purpose is an architectural upgrade to the existing General Purpose service tier that uses an upgraded remote storage layer that stores instance data and log files on Elastic SAN instead of page blobs and maintains it locally. Local redundancy protects against local infrastructure issues. This gives you a 99.99% SLA but not full datacenter/zone disasters, so zone redundancy (where supported) or disaster recovery (DR) options like failover groups/geo-restore are needed for broader resilience. Zone Redundancy The second layer is Zone Redundancy, which is accomplished placing data replicas across availability zones. Your Azure SQL MI resources are distributed across multiple availability zones within a region. This protects against the failure of an entire datacenter because each Azure availability zone is a separate physical location with independent power, cooling and networking. It relies on synchronous replication using zone-redundant storage for General Purpose. For Business critical, it uses Always On Availability group replicas across zones for Business Critical. Always On availability group technology replicates data changes from the primary instance to standby replicas in other availability zones. In the event of an outage, there's an automatic failover that seamlessly transitions one of the standby replicas to be prima. These replicas are always in sync — which means zero data loss. Failover typically happens in under 30 seconds, and your SLA jumps to 99.995%. Failover Groups The third layer is Failover Groups. This is your cross-region disaster recovery solution. It asynchronously replicates all user databases to a secondary Azure SQL MI instance in a different Azure region. Because it is asynchronous replication, there is potential for momentary data loss in the case of a datacenter outage. But it still protects the data against the worst case failure — a full regional outage. If the replica is a standby replica, there is no license required and it is used only for disaster recovery. Using these options, business stakeholders can get their assurance that they have Enterprise grade availability and resiliency platform of AzureSQL for running their mission critical workloads. You can read more about these HA and Resiliency options in Microsoft Learn. Cost Governance for Enterprise Buyers The total cost of data modernization and migration is not a one-time estimate but an ongoing one. In this case, Azure SQL MI provides Enterprise DB Administrators many levers through pricing model choice, right-sizing, elasticity, serverless options and dev/test free tiers. Let us explore how these can be combined for smart cost estimations. Lets also look at the best offering for the cost-conscious Enterprises - Azure SQL DB Hyperscale. With Azure SQL DB Hyperscale, you get the SQL Server engine, T-SQL compatibility, High Availability, Disaster recovery, security, backups, and management all bundled into the service price. No separate cost for SQL Server license. Hyperscale separates compute and storage that can scale independently and does not force you to overprovision. You have to only pay what you use which is ideal for seasonal workloads, Dev/Test, SaaS applications, predictable daytime trends, and up to 60% savings when you use Elastic pools. Azure Hybrid benefit (AHB)- Azure Hybrid Benefit lets you bring your existing SQL Server investments to Azure and reduce compute costs, accelerating your ROI from cloud migration while preserving all the benefits of Azure SQL Azure SQL DB Free offer – is the strongest product offering. Enterprises can use all features of Azure SQL at no cost for up to 10 Azure SQL DB free-tier. 100,000 vCore-seconds of serverless compute per month, 32GB data storage, 32 GB backup storage, serverless auto-scaling and auto-pause if you hit the limit per month. Run your POCs at no cost and evaluate before you move to Azure SQLDB, especially SMB& some enterprise Azure SQL Managed Instance also offers 1 free Azure SQL MI instance per Azure subscription giving you 720vCore hours per month, 64GB storage, up to 500 databases, automated backups and 12 months free. And if data migration is not possible due to data compliance or data proximity purposes, Azure Arc Pay-As-You-Go (PAYG) gives you cloud-style SQL licensing for servers running anywhere—on-premises, at the edge, or in other clouds. Instead of making large up-front licensing investments, you only pay for SQL Server while it's running, while still gaining access to Azure Arc management, security, monitoring, and modernization capabilities. For seasonal, variable, or growth-oriented workloads, PAYG can improve cash flow and reduce licensing complexity. Reserved instances allow Enterprise customers to commit to using Azure SQL resource for a period of one or three years to receive a significant discount. This option combined with AHB can save you even more up to 80%. We have a comprehensive licensing guide for on-premises SQL Server for your reference. Azure SQL enables a variety of cloud cost-models for a wide range of enterprise workload needs to help Enterprise cloud cost decision makers and DB Administrators make the right choice for their workloads. Target selection guidance While Azure SQL has multiple deployment options to migrate your on-premises work loads, it is critical to make the right choice long term. Customers can install SQL Server on-premises, they can use Azure SQL deployment options, and also run SQL Server in other clouds like Amazon Web Services and Google Cloud. If there is an Enterprise workload that is not ready to modernize, you have the ability to lift and shift into SQL Server in Azure VM. It is a low cost migration option, because the application does not need any modification and it gives DB Administrators full control over the SQL server and underlying Windows or Linux OS. This can be a first step to modernization for some customers who are risk-averse. For those Enterprise customers who are willing to modernize their workloads and SQL Server instances, Azure SQL DB Hyperscale is the best option. Azure SQL Database Hyperscale helps organizations modernize their most demanding database workloads with virtually unlimited growth, high performance, and cloud-scale economics. Customers can scale storage and compute independently, support large multi-terabyte databases, accelerate application performance with read-scale replicas, and eliminate the operational complexity of managing infrastructure, backups, patching, and high availability. They can build cloud-native applications or cloud-enable existing applications. However, if Enterprise customers want good compatibility with their on-premises SQL Server but continue down the modernization path - their best option is Azure SQL Managed Instance. They can modernize the instance and not impact the application as there is no application change required. Applications will continue to work and the DB Administrators do not need to worry about managing infrastructure and all the overhead that comes with managing, self-managing your SQL Server virtual machines. For SQL Server customers, PostgreSQL may look like an attractive low cost option. However, it requires re-platforming that could add significant hidden cost due to retraining all their DBAs and their developers to do performance optimization, performance best practices and operational maintenance. Lastly, our same SQL engine is also available to customers as a SaaS-ified version, Fabric SQL database as well. All these options use the exact same SQL engine which makes it easier for Database developers and DB Administrators continue to use the same expertise, tools and process. Making the right choice of Azure SQL deployment is not just on the fastest way to modernize but the right long term approach. Conclusion and Next steps Enterprise SQL Server migrations rarely stall because of migration technology. More often, they are delayed by concerns around downtime, cost predictability, and platform selection. Organizations that address these questions early can accelerate modernization while reducing operational risk. Azure SQL provides multiple modernization paths—from SQL Server on Azure Virtual Machines to Azure SQL Managed Instance and Azure SQL Database—allowing organizations to balance compatibility, operational simplicity, resiliency, and cost efficiency based on their business requirements. As modernization initiatives accelerate, the most successful projects are those that treat migration not as a one-time infrastructure event, but as a long-term platform strategy. Whether its the newest and the fastest way for us to migrate customers, we have all the comprehensive Copilot enabled AI-assisted migration tooling, technical training and support you need. Look for more blogs, whitepapers, guides and training based on best practices used real-world data modernization projects.
