Understanding Failover Clusters and their performance issues
In part 1 of this two-part blog about utilizing Failover Clusters in your network to improve performance and availability, we'll uncover how they work, why they are popular for large-scale organizations, and discuss several of the most common issues with them.
In part 2, we'll discover the best troubleshooting strategies to address Failover Cluster performance issues, and we'll review a helpful checklist that streamlines the process for fixing these issues. We'll also explore how to deploy a comprehensive but easy to use monitoring solution that helps you reduce downtime and bottlenecks.
Let's get to it!
What is a Failover Cluster?
A Failover Cluster is a collaborative assembly of independent servers that aims to maintain the uninterrupted availability of applications and services. Collectively, the Failover Clusters enhance the reliability and scalability of applications and services. Each server in the cluster is called a node and each node is completely interdependent of another. These nodes work in unison to deliver either continuous or high availability through failover mechanisms. Failover Clusters can encompass both physical servers and virtual machines. A Failover Cluster typically comprises a minimum of two nodes to facilitate seamless transaction and data transfer, along with software to handle data processing across the interconnected nodes.
In the event of a server failure, another node within the cluster seamlessly assumes the workload, minimizing or eliminating any downtime—a process commonly referred to as failover.
Top providers in the industry for Failover Clusters include Windows Failover Clustering, SQL Server Failover Clustering, Exchange Server Failover Clustering, Red Hat Linux Failover Clusters, Real Application Clusters (RAC), Oracle Database Clusterware, and Oracle GoldenGate.
Why are Failover Clusters the ultimate choice of large-scale organizations?
A key benefit of Failover Clusters is high availability and optimal performance. An organization, such as a banking enterprise or an e-commerce enterprise, can more efficiently run an application or a website to store data. For example, let's think about an application running in a Microsoft SQL database. When there is an unexpected database outage or a networking issue, or a potential data volume issue, it can cause both the database server and application server to exceed their resource limits. This will ultimately result in bottlenecks, which lead to loading issues, server downtime, or system failure.
The Failover Cluster theory was developed to ease this problem. In our example, if the SQL database is hosted in a Windows Failover Cluster with multiple nodes, the failover process will happen between the active node and the passive node. When there is a downtime or failure, the passive node will get kickstarted, and the entire operation will continue without serious performance issues. These clusters might experience a short or minor no-service interruption during failover, but typically recover swiftly with minimal downtime and little to no data loss. Thus, it will not affect the process, and the organization can ensure maximum availability. Windows Failover Clusters, associated with Windows Server Failover Clusters, are essential for maintaining the continuous availability of critical applications and systems running in a Windows OS, which require extremely high availability levels, close to 100%.
In this blog, we will discuss performance related issues encountered when managing Failover Clusters, specifically Windows Failover Clusters.
Issues with Windows Failover Clusters
Along with the advantages, the Failover Clusters come with their own set of challenges.
If the cluster comprises three nodes, whenever a node gets compromised, you will not know when or which of the other nodes takes its place. Similarly, when the other fails due to an unidentifiable error, the other will be triggered. The process goes on and on until the entire cluster is compromised. What happens if all the nodes get compromised? Cluster failure. The whole cluster performance is impacted.
If you have more than one resource group in the Windows cluster, the resource group that is facing issues will go offline. It can be identified only if you manually check the status of the cluster now and then. In the long run, this process might prove exhausting.
On the other side, the users will experience the impact of application downtime, possibly leading to a negative user experience and posing a significant challenge for the organization. Recovering from downtime can be challenging. The actions taken will directly influence the customer experience, and customer trust and loyalty can be jeopardized.
Some common Failover Cluster performance issues include:
- Configuration errors:
Improperly configured cluster settings, such as network configurations, quorum settings, or resource dependencies, can result in failover failures and cluster instability. - Resource inadequacy:
Resource insufficiency, including CPU, memory, or storage, can hamper failover operations, leading to setbacks in workload transition, impacting the overall performance. - Connectivity:
When the network connectivity within the cluster nodes is weak or fluctuating, the entire failover process experiences downtime. - Quorum configurations:
As we know, quorum configurations are highly critical for maintaining the stability of the cluster. If there is a misconfiguration, it will result in downtime. Other issues that occur during setting up the cluster or while troubleshooting will impact the balance of the cluster. - Storage:
Lapses and shortcomings in shared storage systems, including SAN or NAS devices, will influence the accessibility of data and overall functioning of the failover. This can ultimately lead to interruptions in service availability and potential financial and public image harm for the organization. It is pivotal for these systems to be regularly monitored and maintained to prevent such failures and ensure uninterrupted access to critical data. - Inadequate monitoring:
Insufficient monitoring can lead to delays in identifying cluster issues, potentially causing longer service disruptions and impacting user experience and satisfaction. Forecast analysis, which requires the monitored data, becomes handy to allocate and balance resources.
These are the primary performance problems found in Windows Failover Clusters.
Check out part 2 of this blog to learn more about the strategies and best practices for resolving Failover Cluster performance issues. We'll also discover how to reduce downtimes and performance bottlenecks in your network, and how to improve availability.
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