Microsoft Cluster Center

Clustering Basics

 

Clusters Defined
A cluster is a group of independent computers working together as a single system to ensure that mission-critical applications and resources are as highly-available as possible.  The group is managed as a single system, shares a common namespace, and is specifically designed to tolerate component failures, and to support the addition or removal of components in a way that's transparent to users.  Clustered systems have several advantages: fault-tolerance, high-availability, scalability, simplified management and support for rolling upgrades, to name a few.

There are two different types of cluster models in the industry: the shared device model and the shared nothing model.

In the shared device model, applications running within a cluster can access any hardware resource connected to any node  in the cluster.  As a result, access to the data must be synchronized.  In many such implementations, a special component called a Distributed Lock Manager (DLM) is used for this purpose.  A DLM is a service that manages access to cluster hardware resources.  When multiple applications access the same resource, the DLM resolves any conflicts that might arise.  Along with this sophistication and complexity, a DLM adds significant overhead to the cluster.  Most of this is additional traffic between nodes; however, a performance hit is also realized due to the loss of serialized access to hardware resources.

By default, Microsoft Cluster Server and the Windows Cluster Service use the shared nothing model.  Because this model does not use a DLM, it does not have the overhead incurred by using such a service.  In the shared nothing model, only one node can own and access a single hardware resource at any given time.  When failure occurs, a surviving node can take ownership of the failed node's resources and make them available to users.

While both Microsoft Cluster Server and the Windows Cluster Service support the shared nothing model, they can use the shared device model, but only if the clustered application supplies its own DLM.

Why Cluster?
Generally speaking, hardware failure is not the predominant cause of downtime.  The leading causes of downtime are typically related to events that are external to the system, such as misconfiguration, power outages, security breaches, and so forth.  Clustering cannot help you solve those types of problems.  In addition, a cluster cannot protect you from software incompatibilities, corrupt databases, viruses, catastrophes or mistakes.  Clustering is best implemented when a substantial proportion of your server downtime is caused by hardware failure.  If your organization’s leading cause of downtime is the result of failures in administration, software, or infrastructure, an investment in clustering technology may not reduce your downtime.

You first need to assess the reasons for server downtime in your organization, look at the problems that clustering solves, and then make a business decision as to whether clustering is an appropriate solution.  The primary focus of clustering is solving problems that arise from hardware failure, such as a blown CPU, bad memory, or the loss of an entire server. In addition, clustering allows you to continue providing resources during planned outages that may cause downtime for users. A cluster system can allow resources to be manually moved—or failed over—to one server while the other is brought down to perform a rolling upgrade, a configuration change, or other maintenance.

A rolling upgrade is the process of applying a service pack or other hardware or software update to each node in the cluster while the other node continues providing service. Rolling upgrades are typically a series of stages:

• Groups are moved from the node to be upgraded to another node.
• The node to be upgraded is taken offline.
• Perform the installation on or upgrade to the offline node.
• Bring the upgraded node online.
• Move the groups back to the upgraded node.

Then, repeat this process on each node in the cluster until the entire cluster is upgraded. Rolling upgrades are very attractive from a server management standpoint because services are only unavailable during the time it takes to move resources from one node to the other. By design, clusters help increase uptime. Increased uptime really means reduced downtime. Clustering can help reduce both planned and unplanned downtime. When any mission critical system fails, the consequences can include lost revenue, interruption of services to customers, and knowledge workers unproductively sitting idle. In organizations of all sizes, failures incur costs in many areas. Hidden costs often include damage to your reputation among customers, suppliers, and end-users; and the perception that your organization isn’t able to satisfy customer needs. Understanding the limitations of clustering is just as important as understanding the benefits. While clustering protects against the failure of a node in the cluster, it does not provide any protection against other problems, such as network failures, database corruption, loss of shared storage, or disasters.

Before implementing a cluster in your environment, you should evaluate whether this solution really solves enough of your problems to justify its cost. Clustering adds complexity to your environment and administration. Therefore, it is important that you understand and evaluate this technology in relation to your overall goals and the needs of your network.

Fault Tolerance Defined
Fault tolerance is the ability of a system to continue functioning when part of it fails (e.g., experiences a fault). This term is used to describe disk subsystems (e.g., RAID), symmetric multiple processors (SMP), redundant power supplies (with separate power sources), uninterruptible power supplies, redundant network adapters, etc.  Fault tolerance is designed to alleviate the problems caused by component failures, power outages, or other like occurrences.

Disk subsystems that use RAID, which stands for Redundant Array of Inexpensive Disks (or Redundant Array of Independent Disks, or Redundant Array of Inexpensive Devices, depending on who you ask) are considered fault tolerant.  RAID refers to the grouping of individual hard disks in a way that provides continued operation in the event of a disk failure.  There is both hardware RAID (e.g., a RAID controller is used) and software RAID (e.g., the functionality is provided by an operating system or application).  There are many forms (levels) of RAID:

• RAID-0: Stripe set without parity.  Stripe sets work well with databases due to the usually random I/O nature of database transactions.  In RAID-0, data is divided into blocks and spread (in a fixed order) across all of the disks in an array. RAID-0 improves read/write performance by spreading operations across multiple disks, so that operations can be performed independently and simultaneously.  While RAID-0 provides the highest performance, it does not provide any fault tolerance.  If a drive in a RAID-0 array fails, all of the data within the stripe set becomes inaccessible.
• RAID-1:  Mirroring.  Disk mirroring provides a redundant, identical copy of a disk. Data written to the primary disk is also written to a mirror disk. RAID-1 provides fault tolerance and generally improves read performance, but it may also degrade write performance.  Because dual-write operations can degrade system performance, many mirror set implementations use duplexing, where each mirror drive has its own disk controller. While the mirror approach provides good fault tolerance, it is relatively expensive to implement.  In addition, only half of the available disk space can be used for storage.  The other half is needed for mirroring.
• RAID-5:  Stripe set with parity.  RAID-5 provides redundancy of all data on the array, allowing a single disk to fail and be replaced, in most cases, without system downtime.  RAID-5 offers lower performance than RAID-0 or RAID-1 but higher reliability and faster recovery.  RAID-5 uses the equivalent of one disk for storing the parity strips, but distributes the parity strips across all the drives in the array. The data and parity information are arranged on the disk array so that they are always on different disks.

There are other implementations of RAID, such as RAID-0+1 (aka RAID-10), RAID-2, RAID-3, etc., but these are typically proprietary implementations unique to the hardware manufacturer that support them.

High-Availability Defined
By definition, the goal of a highly available system is to provide continuous use of critical data and applications that keep businesses up and running, regardless of planned or unplanned interruption.  High-Availability refers to a system uptime that approaches 100%.  For example, an availability level of 99.999%, calculated on a round-the-clock basis, would mean that an organization would experience at least five minutes of unscheduled downtime per year.  A level of 99.99% translates to 52 minutes of downtime.  A level of 99.9% translates to 8.7 hours, and a level of 99% equals about 3.7 days of downtime per year.

The need for high-availability is not limited to 365x24x7 environments.  Many applications must be available during normal business hours or for a critical time periods throughout the day.  A system failure during these critical periods is unacceptable for many organizations.

Alternatives to Microsoft Cluster Server and Windows 2000 Cluster Services
Alternatives include Vinca's Co-StandbyServer, Vinca's Octopus, and Network Specialists' Double-Take.  In addition, there are the shared storage clustering solutions provided by Digital's Clusters for Windows NT, NCR's LifeKeeper or Veritas FirstWatch.  Finally, there is the fault tolerance and site disaster tolerance of Marathon's Endurance 4000.