Home > Articles > Operating Systems, Server > Solaris

Cluster and Complex Design Issues

This sample chapter from the Sun BluePrints book Designing Solutions with Sun Cluster 3.0 examines how failures occur in complex systems and shows methods that contain, isolate, report, and repair failures. Special considerations for clustered systems are discussed, including the impact of caches, timeouts, and the various failure modes, such as split brain, amnesia, and multiple instances.
See all of the Sun Blueprints articles here.
Like this article? We recommend

This chapter addresses the following topics:

  • The need for a business to have a highly available, clustered system

  • System failures that influence business decisions

  • Factors to consider when designing a clustered system

  • Failure modes specific to clusters, synchronization, and arbitration

To understand why you are designing a clustered system, you must first understand the business need for such a system. Your understanding of the complex system failures that can occur in such systems will influence the decision to use a clustered system and will also help you design a system to handle such failures. You must also consider issues such as data synchronization, arbitration, caching, timing, and clustered system failures—split brain, multiple instances, and amnesia—as you design your clustered system.

Once you are familiar with all the building blocks, issues and features that enable you to design an entire clustered system, you can analyze the solutions that the Sun_ Cluster 3.0 software offers to see how it meets your enterprise business need and backup, restore, and recovery requirements.

The sections in this chapter are:

  • Business Reasons for Clustered Systems
  • Failures in Complex Systems
  • Data Synchronization
  • Arbitration Schemes
  • Data Caches
  • Timeouts
  • Failures in Clustered Systems
  • Summary

Business Reasons for Clustered Systems

Businesses build clusters of computers to improve performance or availability. Some products and technologies can improve both. However, much clustering activity driving the computer industry today is focused on improving service availability.

Downtime is a critical problem for an increasing number of computer users. Computers have not become less reliable, but users now insist on greater degrees of availability. As more businesses depend on computing as the backbone of their operation, around-the-clock availability of services becomes more critical.

Downtime can translate into lost money for businesses, potentially large amounts of money. Large enterprise customers are not the only ones to feel this pinch. The demands for mission-critical computing have reached the workgroup, and even the desktop. No one today can afford downtime. Even the downtime required to perform maintenance on systems is under pressure. Computer users want the systems to remain operational while the system administrators perform system maintenance tasks.

Businesses implement clusters for availability when the potential cost of downtime is greater than the incremental cost of the cluster. The potential cost of downtime can be difficult to predict accurately. To help predict this cost, you can use risk assessment.

Risk Assessment

Risk assessment is the process of determining what results when an event occurs. For many businesses, the business processes themselves are as complex as the computer systems they rely on. This significantly complicates the systems architect's risk assessment. It may be easier to make some sort of generic risk assessment in which the business risk can be indicted as cost. Nevertheless, justifying the costs of a clustered system is often difficult unless one can show that the costs of implementing and supporting a cluster can reduce the costs of downtime. Since the former can be measured in real dollars and the latter is based on a multivariate situation with many probability functions, many people find it easier to relate to some percentage of "uptime."

Clusters attempt to decrease the probability that a fault will cause a service outage, but they cannot prevent it. They do, however, limit the maximum service outage time by providing a host on which to recover from the fault. Computations justifying the costs of a cluster must not assume zero possibility of a system outage. Prospect theory is useful to communicate this to end users in such a situation. To say the system has "a 99 percent chance of no loss" is preferable to "a 1 percent chance of loss." However, for design purposes, the systems architect must consider carefully the case where there is 1 percent chance of loss. You must always consider the 1 percent chance of loss in your design analysis. After you access the risks of downtime, you can do a more realistic cost estimate.

Cost Estimation

Ultimately, everything done by businesses can be attributed to cost. Given infinite funds and time ("time is money)" perfect systems can be built and operated. Unfortunately, most real systems have both funding and time constraints.

Nonrecurring expenses include hardware and software acquisition costs, operator training, software development, and so forth. Normally, these costs are not expected to recur. The nonrecurring hardware costs of purchasing a cluster are obviously greater than an equivalent, single system. Software costs vary somewhat. There is the cost of the cluster software and any agents required. An additional cost may be incurred as a result of the software licensing agreement for any other software. In some cases, a software vendor may require the purchase of a software license for each node in the cluster. Other software vendors may have more flexible licensing, such as per-user licenses.

Recurring costs include ongoing maintenance contracts, consumable goods, power, network connection fees, environmental conditioning, support personnel, and floor space costs.

Almost all system designs must be justified in economic terms. Simply put, is the profit generated by the system greater than its cost? For systems that do not consider downtime, economic justification tends to be a fairly straightforward calculation.

Plifetime = Rlifetime - Cdowntime - Cnonrecuring - ΣCrecurring

where:

Plifetime is the profit over the lifetime of the system.
Rlifetime is the revenue generated by the system over its lifetime.
Cdowntime is the cost of any downtime.
Cnonrecurring is the cost of nonrecurring expenses.
Crecurring is the cost of any recurring expenses.

During system design these costs tend to be difficult to predict accurately. However, they tend to be readily measurable on well-designed systems.

The cost of downtime is often described in terms of the profit of uptime.

Cdowntime(t) = X Puptime / tup

where:

Cdowntime is the cost of downtime.
tdown is the duration of the outage.
Puptime is the profit made during tup.
tup is the time the system had been up.

For most purposes, this equation suffices. What is not accounted for in this equation is the opportunity cost. If a web site has competitors and is down, a customer is likely to go to one of the competing web sites. This defection represents an opportunity loss that is difficult to quantify.

The pitfall in using such an equation is that the Puptime is likely to be a function of time. For example, a factory that operates using one shift makes a profit only during the shift hours. During the hours that the factory is not operating, the Puptime is zero, and consequently the Cdowntime is zero.

Cdowntime(t) = tdown X Puptime(t) / tup

where:

Puptime(t) Pnominal, when t is during the work hours
= 0, all other times

Another way to show the real cost of system downtime is to weight the cost according to the impact on the business. For example, a system that supports a call center might choose impacted user minutes (IUM), instead of a dollar value, to represent the cost of downtime. If 1000 users are affected by an outage for 5 minutes, the IUM value is 1,000 users times 5 minutes, or 5,000 IUMs. This approach has the advantage of being an easily measured metric. The number of logged-in users and the duration of any outage are readily measurable quantities. A service level agreement (SLA) that specifies the service level as IUMs can be negotiated. IUMs can then be translated into a dollar value by the accountants.

Another advantage of using IUMs is that the service provided to the users is measured, rather than the availability of the system components. SLAs can also be negotiated on the basis of service availability, but it becomes difficult to account for the transfer of the service to a secondary site. IUMs can be readily transferred to secondary sites because the measurement is not based in any way on the system components.

InformIT Promotional Mailings & Special Offers

I would like to receive exclusive offers and hear about products from InformIT and its family of brands. I can unsubscribe at any time.

Overview


Pearson Education, Inc., 221 River Street, Hoboken, New Jersey 07030, (Pearson) presents this site to provide information about products and services that can be purchased through this site.

This privacy notice provides an overview of our commitment to privacy and describes how we collect, protect, use and share personal information collected through this site. Please note that other Pearson websites and online products and services have their own separate privacy policies.

Collection and Use of Information


To conduct business and deliver products and services, Pearson collects and uses personal information in several ways in connection with this site, including:

Questions and Inquiries

For inquiries and questions, we collect the inquiry or question, together with name, contact details (email address, phone number and mailing address) and any other additional information voluntarily submitted to us through a Contact Us form or an email. We use this information to address the inquiry and respond to the question.

Online Store

For orders and purchases placed through our online store on this site, we collect order details, name, institution name and address (if applicable), email address, phone number, shipping and billing addresses, credit/debit card information, shipping options and any instructions. We use this information to complete transactions, fulfill orders, communicate with individuals placing orders or visiting the online store, and for related purposes.

Surveys

Pearson may offer opportunities to provide feedback or participate in surveys, including surveys evaluating Pearson products, services or sites. Participation is voluntary. Pearson collects information requested in the survey questions and uses the information to evaluate, support, maintain and improve products, services or sites, develop new products and services, conduct educational research and for other purposes specified in the survey.

Contests and Drawings

Occasionally, we may sponsor a contest or drawing. Participation is optional. Pearson collects name, contact information and other information specified on the entry form for the contest or drawing to conduct the contest or drawing. Pearson may collect additional personal information from the winners of a contest or drawing in order to award the prize and for tax reporting purposes, as required by law.

Newsletters

If you have elected to receive email newsletters or promotional mailings and special offers but want to unsubscribe, simply email information@informit.com.

Service Announcements

On rare occasions it is necessary to send out a strictly service related announcement. For instance, if our service is temporarily suspended for maintenance we might send users an email. Generally, users may not opt-out of these communications, though they can deactivate their account information. However, these communications are not promotional in nature.

Customer Service

We communicate with users on a regular basis to provide requested services and in regard to issues relating to their account we reply via email or phone in accordance with the users' wishes when a user submits their information through our Contact Us form.

Other Collection and Use of Information


Application and System Logs

Pearson automatically collects log data to help ensure the delivery, availability and security of this site. Log data may include technical information about how a user or visitor connected to this site, such as browser type, type of computer/device, operating system, internet service provider and IP address. We use this information for support purposes and to monitor the health of the site, identify problems, improve service, detect unauthorized access and fraudulent activity, prevent and respond to security incidents and appropriately scale computing resources.

Web Analytics

Pearson may use third party web trend analytical services, including Google Analytics, to collect visitor information, such as IP addresses, browser types, referring pages, pages visited and time spent on a particular site. While these analytical services collect and report information on an anonymous basis, they may use cookies to gather web trend information. The information gathered may enable Pearson (but not the third party web trend services) to link information with application and system log data. Pearson uses this information for system administration and to identify problems, improve service, detect unauthorized access and fraudulent activity, prevent and respond to security incidents, appropriately scale computing resources and otherwise support and deliver this site and its services.

Cookies and Related Technologies

This site uses cookies and similar technologies to personalize content, measure traffic patterns, control security, track use and access of information on this site, and provide interest-based messages and advertising. Users can manage and block the use of cookies through their browser. Disabling or blocking certain cookies may limit the functionality of this site.

Do Not Track

This site currently does not respond to Do Not Track signals.

Security


Pearson uses appropriate physical, administrative and technical security measures to protect personal information from unauthorized access, use and disclosure.

Children


This site is not directed to children under the age of 13.

Marketing


Pearson may send or direct marketing communications to users, provided that

  • Pearson will not use personal information collected or processed as a K-12 school service provider for the purpose of directed or targeted advertising.
  • Such marketing is consistent with applicable law and Pearson's legal obligations.
  • Pearson will not knowingly direct or send marketing communications to an individual who has expressed a preference not to receive marketing.
  • Where required by applicable law, express or implied consent to marketing exists and has not been withdrawn.

Pearson may provide personal information to a third party service provider on a restricted basis to provide marketing solely on behalf of Pearson or an affiliate or customer for whom Pearson is a service provider. Marketing preferences may be changed at any time.

Correcting/Updating Personal Information


If a user's personally identifiable information changes (such as your postal address or email address), we provide a way to correct or update that user's personal data provided to us. This can be done on the Account page. If a user no longer desires our service and desires to delete his or her account, please contact us at customer-service@informit.com and we will process the deletion of a user's account.

Choice/Opt-out


Users can always make an informed choice as to whether they should proceed with certain services offered by InformIT. If you choose to remove yourself from our mailing list(s) simply visit the following page and uncheck any communication you no longer want to receive: www.informit.com/u.aspx.

Sale of Personal Information


Pearson does not rent or sell personal information in exchange for any payment of money.

While Pearson does not sell personal information, as defined in Nevada law, Nevada residents may email a request for no sale of their personal information to NevadaDesignatedRequest@pearson.com.

Supplemental Privacy Statement for California Residents


California residents should read our Supplemental privacy statement for California residents in conjunction with this Privacy Notice. The Supplemental privacy statement for California residents explains Pearson's commitment to comply with California law and applies to personal information of California residents collected in connection with this site and the Services.

Sharing and Disclosure


Pearson may disclose personal information, as follows:

  • As required by law.
  • With the consent of the individual (or their parent, if the individual is a minor)
  • In response to a subpoena, court order or legal process, to the extent permitted or required by law
  • To protect the security and safety of individuals, data, assets and systems, consistent with applicable law
  • In connection the sale, joint venture or other transfer of some or all of its company or assets, subject to the provisions of this Privacy Notice
  • To investigate or address actual or suspected fraud or other illegal activities
  • To exercise its legal rights, including enforcement of the Terms of Use for this site or another contract
  • To affiliated Pearson companies and other companies and organizations who perform work for Pearson and are obligated to protect the privacy of personal information consistent with this Privacy Notice
  • To a school, organization, company or government agency, where Pearson collects or processes the personal information in a school setting or on behalf of such organization, company or government agency.

Links


This web site contains links to other sites. Please be aware that we are not responsible for the privacy practices of such other sites. We encourage our users to be aware when they leave our site and to read the privacy statements of each and every web site that collects Personal Information. This privacy statement applies solely to information collected by this web site.

Requests and Contact


Please contact us about this Privacy Notice or if you have any requests or questions relating to the privacy of your personal information.

Changes to this Privacy Notice


We may revise this Privacy Notice through an updated posting. We will identify the effective date of the revision in the posting. Often, updates are made to provide greater clarity or to comply with changes in regulatory requirements. If the updates involve material changes to the collection, protection, use or disclosure of Personal Information, Pearson will provide notice of the change through a conspicuous notice on this site or other appropriate way. Continued use of the site after the effective date of a posted revision evidences acceptance. Please contact us if you have questions or concerns about the Privacy Notice or any objection to any revisions.

Last Update: November 17, 2020