Understanding Failover Clustering: 6 Important Aspects

Last Modified: February 21st, 2023

Failover Clustering - Featured Image | Hevo Data

Companies that rely on online transactions can not allow server crashes as it will hamper their data records and affect their business adversely.  Therefore, such companies seek methods to develop a foolproof mechanism that can keep their data safe even in the case of server crashes. Failover CLustring is one such mechanism.

Failover Clustering is a mechanism that works on a set of computer servers that collaborate to ensure either High Availability (HA) or Continuous Availability (CA) for server applications. This mechanism ensures that even if one server goes down, another cluster node can undertake its workload without causing any interruptions.

This article will introduce Failover Clustering and list its key features. It will further discuss the importance of this mechanism and define its various types. The article will also explain the 2 key processes involved in the working of this clustering. Read along to learn the applications and limitations of Failover Clustering!

Table of Contents

What is Failover Clustering?

Failover Clustering - Definition | Hevo Data
Image Source – serverwatch.com/

Failover Clustering is a mechanism that provides scalability and availability to your server workloads. Many popular server applications like Microsoft Exchange Server, Microsoft SQL Server, Hyper-V, etc. rely on Failover Clustering for their data’s safekeeping. Failover Clusters are available both in physical and virtual forms and you choose the type of cluster according to your server application’s needs. 

The key objective of Failover Clustering is to offer CA (Continuous Availability) or HA (Higher Availability)  services for your online running applications. The clusters that guarantee CA are also known as  FT (Fault Tolerant) clusters because they empower users to work on applications without witnessing any timeouts due to a server crash. HA clusters on the other hand can suffer from a brief service interruption. However, they will support your system to recover automatically without suffering from any data loss.

Key Features of Failover Clustering

The following features make Failover Clustering a must-have mechanism:

  • Scalability: Since Failover Clustering operates on a group of clusters that work together to prevent server failure, you can easily scale this mechanism by adding new clusters to the group. 
  • Stability: The Clustered Servers are known as nodes and are connected via physical cables. Now, even if one or more nodes fail due to external circumstances, the remaining nodes can provide service in place of the filed nodes using the Failover Clustering mechanism.
  • Real-time Monitoring: The Cluster nodes are kept under constant monitoring to keep track of their functioning. Whenever a cluster fails to perform, it is either restarted or shifted to another node. 
  • Cluster Shared Volume (CSV): This Failover Clustering functionality offers a consistent and distributed namespace that nodes can utilize to work with shared storage. This feature is critical in ensuring minimum disruptions for your server applications.

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What is the Importance of Fail-Over Clustering?

The Failover Clustering mechanism empowers you to perform patching & maintenance work on the passive nodes without shutting down your database. This way you can prevent downtime issues and can also repair failed servers without causing any delay. Moreover, in cases of a hardware error, this mechanism ensures that the database is stopped to safeguard the active nodes.

You can also experience automated data recovery in case of failure using Failover Clustering. This will lessen your dependency on the IT team and will allow your servers to recover in less time. Furthermore, this mechanism provides you with high SQL Cluster availability coupled with minimum downtime. Failover Clustering’s automatic failover feature also ensures that your database is always up and working even in face of failure occurring on the hardware level. Using this technique can simplify server management and recovery for your online mechanism.

What are the Types of Failover Clusters?

In the recent decade, there have been major developments in the field of Failover Clustering and many companies provide their own version of clustering solutions. Some of the most popular clustering types are:  

VMWare Failover Clusters

The VMWare Failover Clustering is a popular mechanism to manage failures of virtual servers. It offers several tools for VM clusters and provides a continuous availability model that accurately replicates a VMware virtual machine. Moreover, VMware’s vSphere HA offers high-availability services for your VMs by resting a pool of VMs and their hosts. Since the tool does not depend on any external component, it has a low risk of failure. 

Windows Server Failover Cluster (WSFC)

The WFSC mechanism allows you to generate Hyper-V failover servers. This technique gained high popularity among Windows users between 2016 and 2019. WSFC supports cluster monitoring and automatically provides the required failover mechanism. To manage a situation of server failure, WFSC either shifts the clusters to separate node or try restarting them.  Furthermore, its Cluster Shared Volume (CSV) technology provides a distributed namespace to utilize shared memory among multiple nodes.

SQL Server Failover Clusters

This Microsoft product, launched in SQL Server 2017, contains powerful HA solutions that leverage WSFC technology. Under this, SQL Server components are considered WSFC cluster resources. They are further integrated with other resources dependent on WSFC. This way, WSFC has the control to identify and communicate the commands to restart an SQL Server instance or to shift such instances to a different node.

Red Hat Linux Failover Clusters

The Red Hat Enterprise Linux (RHEL) has designed its technique to manage failovers. Under this Failover Clustering users can easily build HA failover clusters using the Add-Ons and Red Hat Global File System. Moreover, it provides ample support for single clusters that span multiple sites. Such multi-site clusters operate on a Storage Area Network (SAN) based data replication which benefits from Red Hat’s Failover Clustering.

What Key Processes are Involved in Failover Clustering?

Failover Clustering - Before and After Failover Clustering | Hevo Data
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The Failover Clustering consists of the following 2 key processes:

High Availability Failover Clusters

A High Availability (HA) Cluster contains a group of independent servers that work by sharing resources & data across the system. This implies every node in the Failover mechanism can access the shared storage. Such High Availability Clusters also deploy a monitoring connection that can track the “heartbeat” (health) of the other servers. 

Using the heartbeat mechanism in a simple two-node configuration, the first node can easily recognize the failure of another node. In this scenario, the first node marks itself as active and marks the other node as passive entities. Similarly, for every cluster, the node pairings constantly monitor the health of their pair node and ensure that at least one node is active in every cluster at all times.

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Continuous Availability Failover Clusters

In contrast to the High Availability model, the CA (Continuous Availability) mechanism works with clusters that have multiple systems sharing a single copy of the Operating System. This implies commands issued by anyone system are also implemented on the other systems automatically.

The CA Failover Clustering requires everyone in the company to use formatted computers. This is necessary to ensure that an updated copy of the OS exists on each computer.

What are the Applications of Failover Clustering?

Failover Clustering is a robust mechanism that can facilitate the following real-time applications:

  • Ensures Availability of Critical Applications: Online Transaction-based systems require 100 percent data availability at all times to ensure lossless transactions. Therefore, Failover Clustering is highly useful in applications in which online transactions are a key part. For instance, Ticket reservations, stock trading, ATMs, etc., all can benefit from Failover Clustering.
  • Disaster Recovery: Disaster Recovery is a key application for Failover Clustering. Microsoft also provides storage for saving your replicated data that can provide data recovery in case of a disaster. Furthermore, companies can use the Failover mechanism to replicate and store data at various locations so that even if a location is affected by any physical disaster, the remaining replicas are safe.
  • Database Replication: Database providers often provide you with Failover Clustering-based database replication features. For instance, MySQL Cluster offers a heartbeat mechanism that can detect failure occurring in other nodes instantly.

What are the Limitations of Failover Clustering?

Failover Clustering comes along with the following limitations;

  • The Failover Clustering setup for Windows is complex and requires you to manage multiple networks and network cards simultaneously. Therefore it is not easy for a beginner to deploy this mechanism.
  • There is a need to have a stronger integration between Windows Failover clustering & Hyper-V. Until such integration is developed, you will need to make changes in both of these tools to perform Failover Clustering smoothly.
  • This mechanism does not have any web portal that can allow you to modify its cluster settings. You need to manually log into a remote desktop using a VIP address and navigate to the Cluster Manager option.


The article introduced you to Failover Clustering and explained its key features. It also explained the importance and sub-processes involved in this mechanism. The article further elaborated on the types, main applications, and limitations of using Failover Clustering. 

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Former Research Analyst, Hevo Data

Abhinav is a data science enthusiast who loves data analysis and writing technical content. He has authored numerous articles covering a wide array of subjects in data integration and infrastructure.

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