Introducing 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 SinghWriting a great session abstract for FabCon & SQLCon
Important Dates FabCon/SQLCon Europe in Barcelona, runs 2026 September 28 - Oct 1, 2026 Workshop Call for Content open Feb 17, 2026 to March 23, 2026 Breakout Session Call for Content open Feb 17, 2026 to April 17, 2026 When submitting a session to a conference, consider the following: Title: The title should answer the attendee's question what's in it for me? Why should I attend this session? Is it going to make me better at my job? Will it save my company money? Will it make my reports more organized or my database faster, more secure or modern? The title needs to make sense; it needs to inform. It doesn't need to be funny or contain a dad joke. It CAN, but that's secondary. It shouldn't just be the name of a product or even "Learn [product name]" because you can't teach me everything about it in 60 minutes or less. Abstract: The abstract should contain 3 things: It should define the problem you're trying to solve. It should introduce the solution. It should briefly describe what they'll learn about the solution. In the time allotted. The problem can be that the attendee doesn’t know how to create great visuals, performance tune, connect to Lakehouse, etc. If so, consider titles like “Creating Great Visuals Using...”, “Cutting Costs by Optimizing Your...”, or “Understanding Governance in…” The abstract can introduce a new feature or concept. If so, then the problem is "there's a new thing that you don't know about yet." The solution is "this feature does X, Y & Z." Then tell them that they'll learn everything about X or a little bit about X, Y & Z. If you include an acronym, make sure you spell it out first. Not everyone is going to know what it means, and you don't want only a room full of attendees that already know everything. Avoid using many buzz words in you title or abstract. Drop it into Copilot for a final check and use prompts to help improve your work. Use "make it more precise" if it's over the character count. Tey "make it more professional" if you think it's more casual than you intended. Final check: Before you hit submit, run your abstract by a friend. Does it make sense to the technical and/or non-technical? Do the grammar & spelling check out? With allowances for English not being your 1st language, the abstract should show that you can effectively communicate the topic to an audience. Does the level assigned match the abstract? Is it in the right track? Most calls for content provide definitions on what's a good fit for content in each topic. You can find the topic definitions for FabCon/SQLCon Europe here. Can you do ALL THIS in 60 minutes? Does it fit within the character count? Lastly, a few "don'ts" Don't include your name in the abstract if you know the review is done blind. Don't add it to every category or track. Be mindful. Don't email organizers to say you've submitted a session. They know. Don't demand feedback the very day you're declined. Well, never demand it, but waiting a week to politely ask never hurts. Respect the decision if they aren’t able to offer you feedback. Remember that 800 people might be asking the same question. Don't be entitled. No one *stole* your spot. It was never yours to begin with. Don't use AI to write your entire abstract. Reviewers typically know when it's not written by a human or there are tools that help them check. If you can't convey a concept on your own in 400 characters, how can we trust that you can speak on the concept for a full hour?SSMA Copilot for SAP ASE (Sybase)
Introduction SAP ASE (formerly Sybase) continues to power mission‑critical workloads across financial services, telecom, and large-scale enterprise applications. However, as modernization accelerates, more customers are actively seeking reliable and automated paths to migrate Sybase workloads to Microsoft SQL Server and Azure SQL Targets. While Sybase’s T-SQL dialect shares several similarities with Microsoft SQL Server, its procedural code contains deep complexities—extended syntax, non-standard constructs, legacy system tables, and database‑scoped behaviors that often break traditional rule-based converters. These nuances make stored procedures, triggers, and packages some of the hardest assets to migrate. To address these challenges, the SQL Migration team is expanding Copilot-based code conversion capabilities to SSMA SAP ASE, following the same intuitive user flow as the Oracle-to-SQL Copilot released earlier. This new AI-assisted experience dramatically reduces manual fix-up effort, boosts conversion accuracy, and empowers users to modernize complex Sybase assets with confidence. Why We Built This SSMA’s rule engine already auto-converts a significant portion of Sybase code—typically around 70% for standard workloads. But rule-based systems hit limitations when faced with: Proprietary Sybase syntax variations Conditional logic or cursors expressed in non-standard forms System-level commands not supported in SQL Server Ambiguous constructs requiring contextual interpretation These gaps often force users into tedious manual rewriting. By bringing agentic AI into the equation, Copilot attempts to fill the missing 30%—providing syntactically correct, context-aware, and fully explained code conversions. Instead of relying solely on static rules, Copilot understands intent, identifies root-causes of failures, and generates SQL Server-compatible alternatives with transparent reasoning. This combination of deterministic rule engine + adaptive AI unlocks a far more complete, scalable, and user-friendly migration experience. Authentication Methods SSMA for SAP ASE offers two simple ways to authenticate with Copilot, giving customers flexibility based on their security and infrastructure needs. Option 1: Bring Your Own Key (Azure OpenAI) Connect SSMA to your own Azure OpenAI resource using your deployment details and key. This option is ideal for organizations that already manage Azure OpenAI or require strict control over their AI environment. Option 2: Microsoft‑Managed Endpoint (Preview) A new, seamless experience where no API key is needed. Users simply sign in with Microsoft Entra ID, and SSMA handles authentication through a secure browser-based flow. For detailed setup steps and prerequisites for both authentication options, refer to the SSMA Copilot Learn documentation. What Copilot Offers When the “Fix with Copilot” button is triggered, SSMA opens a structured tri-pane experience designed for clarity and trust: 1. Errors to Fix Shows issues that the rule engine could not convert—whether due to unsupported syntax, parse failures, or ambiguous constructs. This helps users quickly understand where the rule engine struggled. 2. Explanation Provides a detailed, human-readable breakdown of: Why the conversion failed What the Copilot-generated fix means How the logic differs from Sybase to SQL Server This section builds trust, making AI-generated code fully interpretable. 3. Code Review Window Displays a side-by-side diff: Left: SSMA-generated output Right: Copilot-converted SQL code Changes are highlighted so users can validate improvements, understand transformations, and decide whether to apply the Copilot output. From an implementation and architecture point of view, this is similar to SSMA Oracle to SQL Code Conversion Copilot. To know more about how the AI model has been trained, refer to this blog. Sample Use Case (as illustrated in the GIF) In the example shown in the blog GIF, a Sybase stored procedure fails conversion because: It uses set switch on drop_system_tables with override, no_info—a Sybase-only command unsupported in SQL Server. The procedure definition contains create or replace procedure, which is not valid T‑SQL syntax. The rule engine cannot parse the affected block, causing SSMA to output the original Sybase procedure as a commented fallback. When Copilot is invoked: It identifies the unsupported keywords Suggests correct SQL Server equivalents (e.g., translating create or replace into IF EXISTS ... DROP + CREATE PROCEDURE) Generates a complete, runnable T‑SQL procedure Explains why each fix was made This allows users to resolve previously conversion‑blocking issues instantly. To learn more, Copilot in SSMA Real‑World Impact With SSMA’s SAP ASE Copilot, teams can migrate Sybase workloads with significantly less manual effort. Developers, DBAs, and architects gain: Faster conversion cycles Higher code accuracy Clear explanations that improve learning and long-term maintainability Independence from long, multi-step manual rewrite processes This Copilot experience transforms complex procedural conversions into guided, high-confidence workflows—making modernization more accessible for organizations of all sizes.Join us at SQLCon 2026
SQLCon 2026, the premier Microsoft SQL Community Conference, is co-located with the Microsoft Fabric Community Conference (FabCon) from March 16-20, 2026! Register today! This year, your Azure Data Community worlds collide, bringing the SQL and Fabric communities together for a brand-new experience. If you're passionate about SQL Server, Azure SQL, SQL in Fabric, SQL Tools, migration and modernization, database security, or building AI-powered apps with SQL, SQLCon 2026 is the place for you. We're bringing you an amazing keynote in the State Farm Arena, 50+ breakout sessions, and 4 expert-led workshops designed to help you optimize, innovate, and connect just on SQL alone! Join us in Atlanta where we're going to renew the SQL Community spirit - rebuild & reconnect with your networks, friendships, and career-building opportunities. SQLCon is just one part of our renewed commitment to connect at conferences, user groups, online, and at regional events. In a few words, we miss you. Why are SQLCon + FabCon better together? One registration, double the value: Register for either conference and get full access to both - mix and match sessions, keynotes, and community events to fit your interests. Shared spaces, shared energy: Enjoy the same expo hall, registration desk, conference app, and community lounge. Network with peers across the data platform spectrum. Unforgettable experiences: Join us for both keynotes at the State Farm Arena and celebrate at the legendary attendee party at the Georgia Aquarium. Register today and save $200 with code SQLCMTY200. Register Now! Let's build the future of data together. See you at SQLCon + FabCon!Announcing 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!
Announcing SQLCon 2026: Better Together with FabCon!
We’re thrilled to unveil SQLCon 2026, the premier Microsoft SQL Community Conference, co-located with the Microsoft Fabric Community Conference (FabCon) from March 16–20, 2026! This year, we’re bringing the best of both worlds under one roof—uniting the vibrant SQL and Fabric communities for a truly next-level experience. Whether you’re passionate about SQL Server, Azure SQL, SQL in Fabric, SQL Tools, migration and modernization, database security, or building AI-powered apps with SQL, SQLCon 2026 has you covered. Dive into 50+ breakout sessions and 4 expert-led workshops designed to help you optimize, innovate, and connect. Why are SQLCon + FabCon better together? One registration, double the value: Register for either conference and get full access to both—mix and match sessions, keynotes, and community events to fit your interests. Shared spaces, shared energy: Enjoy the same expo hall, registration desk, conference app, and community lounge. Network with peers across the data platform spectrum. Unforgettable experiences: Join us for both keynotes at the State Farm Arena and celebrate at the legendary attendee party at the Georgia Aquarium. Our goal is to reignite the SQL Community spirit—restoring the robust networks, friendships, and career-building opportunities that make this ecosystem so special. SQLCon is just the beginning of a renewed commitment to connect at conferences, user groups, online, and at regional events. Early Access Pricing Extended! Register by November 14th and save $200 with code SQLCMTY200. Register Now! Want to share your expertise? The Call for Content is open until November 20th for both conferences! Let’s build the future of data—together. See you at SQLCon + FabCon!
