Creating a Contained Availability Group and Enabling Database Creation via CAG Listener
A Contained Availability Group (CAG) is designed to simplify high availability and disaster recovery by encapsulating system databases (master, msdb) within the availability group itself. This means that logins, jobs, credentials, and other metadata are automatically replicated across replicas, eliminating the need for manual synchronization and reducing operational complexity. Starting with SQL Server 2025 CU1, you can create or restore databases directly through the CAG listener - without connecting to the physical instance - by enabling a session context key. Why Contained AGs Matter Self-contained HA unit: Each CAG has its own copy of master and msdb, making it independent of the physical SQL instance. Simplified failover: When the AG fails over, all associated metadata moves with it, ensuring applications continue to function without manual intervention. Improved automation: Supports scenarios where direct access to the SQL instance is restricted, enabling operations through the AG listener. Enhanced security: Reduces exposure by limiting instance-level access; operations can be scoped to the AG context. Streamlined management: Eliminates the need for login and job replication scripts across replicas. Step 1: Prepare the Database for Availability Group This example uses SQL Server on Linux; however, the steps are identical for SQL Server on Windows. In this walkthrough, an existing database named CAGDB is added to a Contained Availability Group (CAG). Before adding the database to the CAG, verify that it is configured for FULL recovery mode and perform a full database backup. ALTER DATABASE CAGDB SET RECOVERY FULL; GO BACKUP DATABASE CAGDB TO DISK = N'/var/opt/mssql/backups/CAGDB.bak' WITH INIT, COMPRESSION; GO Note: On Linux, ensure that the backup target directory exists and is owned by the mssql user. sudo mkdir -p /var/opt/mssql/backups sudo chown mssql:mssql /var/opt/mssql/backups Step 2: Create the Contained Availability Group On your Linux SQL Server nodes, run: CREATE AVAILABILITY GROUP [CAGDemo] WITH ( CLUSTER_TYPE = EXTERNAL, CONTAINED ) FOR DATABASE [CAGDB] REPLICA ON N'node1' WITH ( ENDPOINT_URL = N'tcp://node1:5022', AVAILABILITY_MODE = SYNCHRONOUS_COMMIT, FAILOVER_MODE = EXTERNAL, SEEDING_MODE = AUTOMATIC ), N'node2' WITH ( ENDPOINT_URL = N'tcp://node2:5022', AVAILABILITY_MODE = SYNCHRONOUS_COMMIT, FAILOVER_MODE = EXTERNAL, SEEDING_MODE = AUTOMATIC ); GO #Connect to secondary replicas and join the AG: ALTER AVAILABILITY GROUP [CAGDemo] JOIN WITH (CLUSTER_TYPE = EXTERNAL); ALTER AVAILABILITY GROUP [CAGDemo] GRANT CREATE ANY DATABASE; Step 3: Configure Listener and Connect Create a listener and connect using SSMS or sqlcmd: ALTER AVAILABILITY GROUP [CAGDemo] ADD LISTENER N'CAGDemoListener' ( WITH IP ( (N'*.*.*.*', N'255.255.255.0') ), PORT = 1453 ); GO Step 4: Connect to CAGDemoListener and attempt Database Creation (Failure) When connected through the listener: CREATE DATABASE TestCAGDB; Result:\ Msg 262, Level 14, State 1: CREATE DATABASE is not allowed in this context.\ This happens because database creation is blocked by default in a contained AG session. Step 5: Enable Database Creation in CAG Session or Instance master EXEC sp_set_session_context key = N'allow_cag_create_db', @value = 1; This enables database creation for your current session. Step 6: Retry Database Creation (Success) CREATE DATABASE TestCAGDB; Result: Database created successfully within the contained AG context. Users with dbcreator role in the CAG context can perform this action. Step 7: Backup the database. ALTER DATABASE TestCAGDB SET RECOVERY FULL; BACKUP DATABASE TestCAGDB TO DISK = N'/var/opt/mssql/data/backups/TestCAGDB.bak'; Step 8: Add database to the CAG ALTER AVAILABILITY GROUP [CAGDemo] ADD DATABASE [TestCAGDB]; Optional: To automate Steps 4 - 8, you can create a stored procedure (for example: [dbo].[sp_cag_create_db]) and execute it while connected through the Contained Availability Group (CAG) listener context. CREATE OR ALTER PROCEDURE [dbo].[sp_cag_create_db] @database_name sysname, @createdb_sql NVARCHAR(MAX) = NULL AS BEGIN SET NOCOUNT ON DECLARE @fIsContainedAGSession int EXECUTE @fIsContainedAGSession = sys.sp_MSIsContainedAGSession if (@fIsContainedAGSession = 1) BEGIN DECLARE @SQL NVARCHAR(MAX); EXEC sp_set_session_context = N'allow_cag_create_db', @value = 1; IF @createdb_sql IS NULL SET @SQL = 'CREATE DATABASE ' + QUOTENAME(@database_name); ELSE SET @SQL = @createdb_sql; PRINT @SQL EXEC sp_executesql @SQL; SET @SQL = 'ALTER DATABASE ' + QUOTENAME(@database_name) + ' SET RECOVERY FULL'; PRINT @SQL EXEC sp_executesql @SQL; SET @SQL = 'BACKUP DATABASE ' + QUOTENAME(@database_name) + ' TO DISK = N''NUL'''; PRINT @SQL EXEC sp_executesql @SQL; DECLARE _Name sysname; set _Name = (SELECT name FROM sys.availability_groups ags INNER JOIN sys.dm_exec_sessions des ON ags.group_id = des.contained_availability_group_id WHERE @@SPID = des.session_id); SET @SQL = 'use master; ALTER AVAILABILITY GROUP ' + QUOTENAME(@AG_Name) + ' add DATABASE ' + QUOTENAME (@database_name) PRINT @SQL EXEC sp_executesql @SQL; EXEC sp_set_session_context key = N'allow_cag_create_db', @value = 0; END ELSE BEGIN RAISERROR('This can only be used with a contained availability group connection.', 16, 1); END END GO At a high level, this procedure simplifies database onboarding into a CAG by orchestrating the following actions as a single workflow: Creating (or restoring) the database Setting the recovery model to FULL Taking the initial backup required for availability group seeding Adding the database to the target Contained Availability Group Example: Create a database Execute the following command to create NewTestDB and add it to the target CAG. EXEC [dbo].sp_cag_create_db @database_name = [NewTestDB]; Example: Restore a database The stored procedure also supports an optional parameter, @createdb_sql, which allows you to provide a custom SQL statement to create or restore a database (for example, restoring from a backup). Once the database backup file exists and is accessible to SQL Server, you can use this parameter to perform the operation. Important: When @createdb_sql is used, the procedure executes that SQL statement directly. Ensure the SQL statement is from a secured and trusted source. DECLARE @restoreSql NVARCHAR(MAX); SET @restoreSql = N' RESTORE DATABASE AdventureWorks2022 FROM DISK = ''/var/opt/mssql/backups/AdventureWorks2022.bak'' WITH MOVE ''AdventureWorks2022'' TO ''/var/opt/mssql/data/AdventureWorks2022.mdf'', MOVE ''AdventureWorks2022_log'' TO ''/var/opt/mssql/data/AdventureWorks2022_log.ldf'', RECOVERY; '; EXEC dbo.sp_cag_create_db @database_name = N'AdventureWorks2022', @createdb_sql = @restoreSql; Conclusion Contained Availability Groups represent a major step forward in simplifying high availability for SQL Server. By encapsulating system databases within the AG context, they eliminate the complexity of synchronizing logins, jobs, and credentials across replicas. With the new capability in SQL Server 2025 CU1 to create or restore databases directly through the AG listener using sp_set_session_context, organizations can streamline automation and reduce operational overhead. References What Is a Contained Availability Group Deploy a Pacemaker Cluster for SQL Server on LinuxIntroducing Pacemaker HA Agent v2 for SQL Server on Linux (In Preview)
We are excited to introduce the next generation of High Availability (HA) Agent for SQL Server on Linux: Pacemaker HA Agent v2. This release is a major step forward, designed to reduce planned and unplanned failover times, compared to the previous agent, based on internal engineering improvements. Why Pacemaker Is Required for SQL Server HA on Linux For users new to Linux, it’s important to understand how high availability works on this platform. On Windows, SQL Server AlwaysOn Availability Groups rely on Windows Server Failover Clustering (WSFC) to: Monitor node health Detect failures Orchestrate automatic failovers SQL Server AlwaysOn Availability Groups on Linux rely on an external cluster orchestrator for health monitoring and failover coordination, with Pacemaker HA Agent being one of the cluster orchestrators, responsible for: Monitoring node and application health Coordinating failover decisions Helping mitigate split‑brain scenarios through improved write‑lease evaluation Managing resources such as Availability Groups and listeners The Pacemaker HA Agent is the integration layer that allows Pacemaker to understand SQL Server health and manage Availability Groups safely. Evolution of the SQL Server Pacemaker HA Agent With SQL Server 2025 CU3 and later, Pacemaker HA Agent v2 is available in preview for Red Hat Enterprise Linux and Ubuntu through the mssql-server-ha package. Pacemaker HA agent v2 uses a service‑based architecture. The agent runs as a dedicated system service named mssql-pcsag, which is responsible for handling SQL Server–specific high availability operations and communication with Pacemaker. You can manage mssql-pcsag service by using standard system service controls to start, restart, status and stop this service by using the operating system's service manager (for example, systemctl). # Start the mssql-pcsag service sudo systemctl start mssql-pcsag # Restart the mssql-pcsag service sudo systemctl restart mssql-pcsag # Check the status of the mssql-pcsag service sudo systemctl status mssql-pcsag # Stop the mssql-pcsag service sudo systemctl stop mssql-pcsag Limitations of Pacemaker HA Agent v1 While the original agent enabled SQL Server HA on Linux, customers running production workloads encountered several challenges: Failover delays of 30 seconds to 2 minutes during planned or unplanned events Limited health detection, missing conditions such as I/O stalls and memory pressure Rigid failover behavior, unlike the flexible policies available on Windows (WSFC) Incomplete write‑lease handling, requiring custom logic No support for TLS1.3 for Pacemaker and SQL Server communications How Pacemaker HA Agent v2 Addresses These Gaps Pacemaker HA Agent v2 is a ground‑up improvement, designed to improve the reliability characteristics of SQL Server HA on Linux. 1. Faster & Smarter Failover Decisions The new agent introduces a service‑based health monitoring architecture, moving beyond basic polling. This allows SQL Server to report detailed diagnostic signals - improving detection speed and helping reduce failover delays in supported configurations. 2. Flexible Automatic Failover Policies inspired by the WSFC health model Pacemaker HA Agent v2 supports failure‑condition levels (1–5) and health‑check timeout model aligned with those available in AlwaysOn Availability Groups on Windows. This provides: Fine‑grained control over failover sensitivity, allowing administrators to tune when failover should occur. Improved detection of internal SQL Server conditions, such as memory pressure, internal deadlocks, orphaned spinlocks, and other engine‑level failures. Failover decisions are now driven by detailed diagnostics from sp_server_diagnostics, enabling faster and more accurate response to unhealthy states and providing enhanced resiliency capabilities for SQL Server AG on Linux. You can configure the failure condition level and health check timeout using the following commands: -- Setting failure condition level ALTER AVAILABILITY GROUP pacemakerag SET (FAILURE_CONDITION_LEVEL = 2); -- Setting health check timeout ALTER AVAILABILITY GROUP pacemakerag SET (HEALTH_CHECK_TIMEOUT = 60000); After applying the configuration, validate the setting using the sys.availability_groups DMV: 3. Robust Write Lease Validity Handling To prevent split‑brain scenarios, SQL Server on Linux uses an external write‑lease mechanism. In v1, lease information was not fully integrated into failover decisions. In v2, the agent actively evaluates the write-lease validity, before initiating transitions. This supports controlled role changes and improved data consistency behavior during failover events, depending on cluster configuration. 4. TLS 1.3 Support Pacemaker HA agent v2 includes design updates to support TLS 1.3–based communication for health checks and failover operations, when TLS 1.3 is enabled. Supported Versions & Distributions Pacemaker HA Agent v2 supports: SQL Server 2025 CU3 or later RHEL 9 or later Ubuntu 22.04 or higher. Preview upgrade & migration guidance for non-production environments New or existing non-prod deployments running SQL Server 2025 (17.x) can migrate from Pacemaker HA Agent v1 to v2 using following approach: Drop the existing AG resource sudo pcs resource delete <NameForAGResource> This temporarily pauses AG synchronization but does not delete the Availability Group (AG). After the resource is recreated, Pacemaker resumes management and AG synchronization automatically. Create a new AG resource using the v2 agent (ocf:mssql:agv2) sudo pcs resource create <NameForAGResource> ocf:mssql:agv2 ag_name=<AGName> meta failure-timeout=30s promotable notify=true Validate cluster health sudo pcs status Resume normal operations References Create and Configure an Availability Group for SQL Server on Linux - SQL Server | Microsoft Learn Thank You, Engineering: David Liao Attinder Pal SinghAnnouncing GA of SQL Server 2025 on RHEL 10 and Ubuntu 24.04, with additional enhancements for Linux deployments
We are excited to announce the General Availability (GA) of SQL Server 2025 on Red Hat Enterprise Linux (RHEL) 10 and Ubuntu 24.04, starting with the CU1 release. This milestone empowers enterprises to deploy SQL Server 2025 on the latest Linux distributions, ensuring robust compatibility, enhanced security, and optimal performance for mission-critical workloads. The GA reinforces our commitment to delivering a modern, secure, and AI-ready database platform across diverse Linux environments. CU1 Release Highlights Key Features: Production-Ready Support: GA support for RHEL 10 and Ubuntu 24.04, enabling production deployments on the newest Linux platforms. Important: Update your SQL Server repository To ensure you are installing the production-ready GA version of SQL Server 2025, it is essential to update your repository from mssql-server-preview.repo to mssql-server-2025.repo. Continuing to use the preview repository may result in installing pre-release builds that are not intended for production workloads. You can proceed with the installation steps as described in the official documentation: RHEL: Install SQL Server on Linux Ubuntu: Install SQL Server on Linux Enable database creation or restoration in Contained Availability Group sessions You can now use the session context key 'allow_cag_create_db' set via the existing stored procedure sp_set_session_contex to enable database creation and restoration directly within a contained availability group (CAG) session through the CAG listener. Only users with the dbcreator role can create databases in a CAG session, and only users with the db_owner or sysadmin role can restore databases. Example: EXEC sp_set_session_context @key = N'allow_cag_create_db', @value = 1; This command enables the feature for your session. To disable it, set @value = 0. Enhanced Observability: SQL Server 2025 on Linux introduces new Dynamic Management Views (DMVs) that provides comprehensive, system-level insights. These DMVs collect and expose metrics from the underlying operating system, allowing administrators to monitor and diagnose not only SQL Server’s performance, but also the impact of other processes running on the same host. This holistic visibility helps distinguish between issues caused by SQL Server and those originating from other workloads or infrastructure bottlenecks, enabling more effective troubleshooting and optimization for mission-critical deployments. sys.dm_os_linux_cpu_stats: Enables users to identify CPU saturation, investigate I/O waits, analyze system responsiveness, and correlate SQL Server performance with broader OS activity, helping to separate database-specific bottlenecks from infrastructure-wide challenges. sys.dm_os_linux_disk_stats: Facilitates detection of log flush slowness, assessment of checkpoint or read-heavy workloads, and identification of external I/O pressure from noisy neighbors on shared hosts, helping teams optimize storage tiers and queue settings. sys.dm_os_linux_net_stats: Provides real-time visibility into network interface statistics, enabling proactive monitoring and troubleshooting of connectivity and throughput issues. Collectively, these DMVs equip database professionals with actionable, OS-level metrics to maintain stability, optimize performance, and ensure reliability in mission-critical Linux deployments. References What’s New in SQL Server 2025 Contained Availability Group You can share your feedback using any of the following methods: Submit your ideas on Azure Ideas (Use the SQL Server on Linux Group on the left side of the page) Alternatively, you can open issues: Issues · microsoft/mssql-docker (github.com) on GitHub. We hope you give SQL Server 2025 CU1 on RHEL10 or Ubuntu 24.04 a try - and we look forward to hearing what you think!
SQL Server 2019 Intelligent Performance -Worker Migration
SQL Server task scheduling basics A few basic terms: Scheduler – each scheduler is mapped to an individual logical processor (DMV sys.dm_os_schedulers) Worker – each worker is mapped to a thread 1 (DMV sys.dm_os_workers) Task – each task is mapped to a series of programming instructions that form a unit of work. The task is then bound to a worker in order to execute the instructions on a CPU. (DMV sys.dm_os_tasks) Please reference SQL Server Thread and Task Architecture Guide for comprehensive explanation. 1 Unless the SQL Server instance is set to fiber mode, which is generally not recommended. The following graph is a high-level life cycle workflow of a task from the moment that it is bound to a worker to the time that it is unbound from its worker after task completion. Mechanism to balance CPU usage in previous versions of SQL Server SQL Server internally tracks the current task count as load factor for each scheduler and always assigns a newly created task to the least loaded scheduler for balanced CPU usage. This mechanism works well for typical short-running query tasks. For long-running tasks, this mechanism may not always sustain evenly distributed CPU usage across schedulers. It is possible for more than one long-running task to be assigned to the same scheduler when other schedulers have higher task loads (which are all short-running tasks) at the moment the long-running task is assigned to a scheduler. Workers are bound to the same scheduler for the life of the worker, and a task is bound to a worker for its entire execution duration. This means when other schedulers become idle or have fewer tasks, long-running tasks cannot be re-assigned to these schedulers because they are bound to their originally assigned scheduler. This can lead to an unbalanced workload with multiple competing runnable workers on a single scheduler unable to utilize available CPU cycles on other idle schedulers. With computer hardware evolution, SQL Server customers gradually switch to host machines with a higher number of CPUs. Imbalanced CPU usage in the SQL Server engine becomes a more visible problem these days. What is worker migration Worker migration (AKA “worker stealing”) allows an idle SOS scheduler to migrate a worker from the runnable queue of another scheduler on the same NUMA node and immediately resume the task of the migrated worker. This enhancement provides more balanced CPU usage and reduces the amount of time long-running tasks spend in the runnable queue. A long-running task that is enabled for worker migration is no longer bound to a fixed scheduler. Instead, it will frequently move across schedulers within the same NUMA node which naturally results in less loaded schedulers. Together with the existing load factor mechanism, worker migration provides SQL Server with an enriched solution for balanced CPU usage. Availability group parallel redo tasks with worker migration In SQL Server 2019, workers associated with availability group parallel redo tasks are enabled for worker migration to address a commonly observed scheduler contention issue among redo tasks on secondary replicas. Availability group parallel redo is the default redo mode starting with SQL Server 2016 RTM and later versions. For each database in an availability group secondary replica, a set of parallel redo worker tasks are created for this database in addition to its main redo task. The main redo task is dedicated to analyzing incoming log records and dispatching them to different parallel redo workers. Each parallel redo worker processes assigned log records and applies changes to data pages. Both the main redo task and parallel redo worker tasks are long-running tasks. After a database successfully starts its parallel redo worker tasks during database startup phase, these parallel redo worker tasks will stay alive until the database is shut down. The main redo task also keeps running as long as there are transaction logs to process and does not stay idle for more than 60 seconds. For a heavy transaction workload database on the availability group primary replica, the main redo task of the database on a secondary replica is generally CPU-intensive. Its parallel redo worker tasks may have high CPU demand depending on database configuration, table schema and transaction types. It is possible for one or more parallel redo worker tasks of a database to be assigned to the same scheduler as its main redo task. If more than one long-running redo task competes for CPU cycles on the same scheduler, scheduler contention may occur. When this happens, the overall transaction log redo throughput of the impacted database can drop 20-30%. When several availability group databases have heavy redo workloads during the same period, this scheduler contention pattern is more common because of the increased chance for one or more database main redo tasks to be allocated to the same scheduler with parallel redo worker tasks. Worker migration avoids this performance degradation and maintains more consistent redo throughput for a database. For multiple database concurrent redo workloads, the overall redo throughput has about 10-15% improvement compared to the situation when there is scheduler contention between some main redo tasks and parallel redo worker tasks. To monitor worker migration occurrence, a new column “worker_migration_count” is added into the existing DMV sys.dm_os_workers. It is a cumulative indicator of the number of migrations that have happened to a worker since the last SQL Server service startup. Also, for parallel redo worker task records (command=”PARALLEL REDO TASK” or “PARALLEL REDO HELP TASK”) from the output of sys.dm_exec_requests, their scheduler_id values are expected to change frequently when the corresponding database has ongoing redo workloads. T-SQL query samples: -- Query worker_migration_count column in DMV sys.dm_os_workers SELECT worker_address, worker_migration_count FROM sys.dm_os_workers ORDER BY worker_migration_count DESC -- Query parallel redo tasks in DMV sys.dm_exec_requests -- (scheduler_id values may change for some rows when re-running this query) SELECT scheduler_id, session_id, task_address, command FROM sys.dm_exec_requests WHERE command = 'PARALLEL REDO TASK' OR command = 'PARALLEL REDO HELP TASK' ORDER BY session_id Next Steps In the future, other SQL Server system long-running tasks may be evaluated for enabling worker migration to avoid scheduler contention. One such example would be the availability group main redo task, which can also be impacted by scheduler contention. When the main redo tasks of two databases are assigned to the same scheduler, or a main redo task shares the same scheduler with a long-running and CPU intensive query task, redo performance can drop 30% or more. Dong Cao Principal Software EngineerHPE SGLX - The new Azure VM extension for SQL Server on Linux
Overview Mission critical SQL Server instances have the need to utilize high availability and disaster recovery features to ensure business continuity. SQL Server on Linux supports HPE Serviceguard as one of the supported clustering solutions. To know more, please refer to HPE Serviceguard for Linux. We have an official documentation that provides detailed steps on how you can configure SQL Server Always On availability groups with HPE Serviceguard for Linux. The purpose of this blog is to inform you about the HPE Serviceguard Extension available in Azure marketplace. This extension allows users to easily create Azure linux-based VMs with SQL Server and HPE Serviceguard pre-installed. As a result, customers can quickly configure SQL Server high availability (HA) solutions. The Serviceguard - Azure VM marketplace extension is available in all Azure regions for use. Let's get started! Create an Azure virtual machine using Azure portal: Log in to Azure portal – portal.azure.com Create Resource group in Azure under the subscription or choose existing resource group of choice. Choose SQL Server on Linux based marketplace image (RHEL or SUSE) and configure the VM on the basis of disks, virtual network, etc. On the Advanced tab of VM creation, click on “Select an extension to install.” Search for HPE Serviceguard for Linux Click on load more and select the extension. Under ‘Select Serviceguard Add-on to install’ , Select Microsoft SQL server on Linux if it’s non-quorum server node machine and select ‘Centralized Serviceguard Management and Arbitration’ if you need Serviceguard quorum server and SGMGR+ (UI) to be configured,. Enter Serviceguard administrative user “sgmgr” password and confirm the same. Proceed to create the VM upon entering the SGLX extension details. After you have configured the other two VMs using the steps as outlined above, you can follow this documentation starting from "Create HPE Service guard cluster" section to configure SQL Server Always On availability groups for SQL Server on Linux
