Introduction
What Is a Multi-Node Failover Cluster Instance?
SQL Server clustering refers to a setup where two or more physical servers (nodes) connect through a LAN, host SQL Server instances, and share access to common storage. The SQL Server clustering ensures high availabilityand protects against disasters when a server fails.
Always on Failover Cluster Instances (FCI)
SQL Server Always On Failover Cluster Instances (FCIs) use Windows Server Failover Clustering (WSFC) to deliver high availability at the server instance level. An FCI is a single SQL Server instance installed across multiple WSFC nodes, to ensure continuous access to the entire SQL Server installation.
What is “Always On Availability Group”?
The Always On availability groups feature delivers high availability and disaster recovery as an enterprise-grade alternative to database mirroring. It maximizes uptime for a defined set of user databases by grouping them into an availability group that fails over together. Each group includes one set of read-write primary databases and up to eight sets of corresponding secondary databases. You can configure secondary databases for read-only access, backup operations, or both. The system initiates failover at the level of an availability replica, not due to database-level issues such as missing data files, deleted databases, or transaction log corruption.
To help you get started, here’s what you can do next:
To explore what metrics this integration monitors, see Supported Metrics and Default Monitoring Configuration.
To configure the integration, see Working with Application.
Use Cases
Discovery
Device discovery provides a unified view of all components within a Windows MS SQL Failover / Always On Availability Group cluster, along with their interrelationships.
Monitoring
The device monitoring helps to collect the metric values with respect to time and sends alert to the intended customer team to act up on immediately in case of any threshold breach or unexpected metric behaviour observed based on configurations. In a way it helps the customer with smooth functioning of business with minimal or zero downtime in case of any infrastructure related issues occurring.
- Provides monitoring related to availability, capacity, performance and usage.
- Alerts are generated when defined metric thresholds are breached, notifying users of potential issues.
- Refer to the Supported Metrics and Default Monitoring Configuration for complete details.
Supported Versions |
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This application is validated on Windows Server 2019 and Microsoft SQL Server 2019 (RTM) - 15.0.2000.5 (X64) for both MSSQL failover instance & availability group clusters. Clustering software used is Microsoft Windows Server Failover Clustering (WSFC). |
Version History
Application Version | Bug fixes / Enhancements |
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6.0.0 | Added support for Veritas Mssql Cluster. |
5.2.2 |
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5.2.1 | Fix provided for the metrics mssql_cluster_group_listener_status and mssql_cluster_instance_FailoverStatus. |
5.2.0 | Script Optimisations, Support for Native Bridge Timeouts in UI, Fix for MSSQL Cluster single-node discovery and Disk Monitoring issues. |
5.1.0 |
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5.0.1 |
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5.0.0 | Added new native type MSSQL Server Database and its supported metrics. |
4.0.3 | Filtering sql service status on passive nodes for metric mssql_cluster_node_sqlservices_state. |
4.0.2 | Fixed MS SQL default SQL server instance monitoring issue. |
4.0.1 | Enhanced the app discovery script to fetch the SQL server instance IP address details. |
4.0.0 | Persona changes to support CLUSTER and STANDALONE MS SQL Cluster configurations. |
Click here to view the earlier version updates
Application Version | Bug fixes / Enhancements |
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3.0.2 | Implemented the fix to fetch ipaddress for default SQL server instances. |
3.0.1 | Added Fix for Powershell script Empty Arguments issue. |
3.0.0 |
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2.0.1 | Added support for NativeType Display order changes and resource grouping by type in UI. |
2.0.0 | mssql application enhancement & csv monitoring support changes. |
1.0.2 | Full Discovery Support. |
1.0.1 | Initial SDK2.0 app Discovery and Monitoring Implementations. |