Single point of failure

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In this diagram the router is a single point of failure for the communication network between computers. Single Point of Failure.png
In this diagram the router is a single point of failure for the communication network between computers.

A single point of failure (SPOF) is a part of a system that, if it fails, will stop the entire system from working. [1] SPOFs are undesirable in any system with a goal of high availability or reliability, be it a business practice, software application, or other industrial system. If there is a SPOF present in a system, it produces a potential interruption to the system that is substantially more disruptive than an error would elsewhere in the system.

Contents

Overview

Systems can be made robust by adding redundancy in all potential SPOFs. Redundancy can be achieved at various levels.

The assessment of a potential SPOF involves identifying the critical components of a complex system that would provoke a total systems failure in case of malfunction. [2] Highly reliable systems should not rely on any such individual component.

For instance, the owner of a small tree care company may only own one woodchipper. If the chipper breaks, they may be unable to complete their current job and may have to cancel future jobs until they can obtain a replacement. The owner could prepare for this in multiple ways. The owner of the tree care company may have spare parts ready for the repair of the wood chipper, in case it fails. At a higher level, they may have a second wood chipper that they can bring to the job site. Finally, at the highest level, they may have enough equipment available to completely replace everything at the work site in the case of multiple failures.

Computing

A fault-tolerant computer system can be achieved at the internal component level, at the system level (multiple machines), or site level (replication).

One would normally deploy a load balancer to ensure high availability for a server cluster at the system level. [3] In a high-availability server cluster, each individual server may attain internal component redundancy by having multiple power supplies, hard drives, and other components. System-level redundancy could be obtained by having spare servers waiting to take on the work of another server if it fails.

Since a data center is often a support center for other operations such as business logic, it represents a potential SPOF in itself. Thus, at the site level, the entire cluster may be replicated at another location, where it can be accessed in case the primary location becomes unavailable. This is typically addressed as part of an IT disaster recovery program. While previously the solution to this SPOF was physical duplication of clusters, the high demand for this duplication led multiple businesses to outsource duplication to 3rd parties using cloud computing. It has been argued by scholars, however, that doing so simply moves the SPOF and may even increase the likelihood of a failure or cyberattack. [4]

Paul Baran and Donald Davies developed packet switching, a key part of "survivable communications networks". Such networks – including ARPANET and the Internet  – are designed to have no single point of failure. Multiple paths between any two points on the network allow those points to continue communicating with each other, the packets "routing around" damage, even after any single failure of any one particular path or any one intermediate node.

Software engineering

In software engineering, a bottleneck occurs when the capacity of an application or a computer system is limited by a single component. The bottleneck has lowest throughput of all parts of the transaction path. A common example is when a used programming language is capable of parallel processing, but a given snippet of code has several independent processes run sequentially rather than simultaneously.

Performance engineering

Tracking down bottlenecks (sometimes known as hot spots – sections of the code that execute most frequently – i.e., have the highest execution count) is called performance analysis. Reduction is usually achieved with the help of specialized tools, known as performance analyzers or profilers. The objective is to make those particular sections of code perform as fast as possible to improve overall algorithmic efficiency.

Computer security

A vulnerability or security exploit in just one component can compromise an entire system. One of the largest concerns in computer security is attempting to eliminate SPOFs without sacrificing too much convenience to the user. With the invention and popularization of the internet, several systems became connected to the broader world through many difficult to secure connections. [4] While companies have developed a number of solutions to this, the most consistent form of SPOFs in complex systems tends to remain user error, either by accidental mishandling by an operator or outside interference through phishing attacks. [5]

Other fields

The concept of a single point of failure has also been applied to fields outside of engineering, computers, and networking, such as corporate supply chain management [6] and transportation management. [7]

Design structures that create single points of failure include bottlenecks and series circuits (in contrast to parallel circuits).

In transportation, some noted recent examples of the concept's application have included the Nipigon River Bridge in Canada, where a partial bridge failure in January 2016 entirely severed road traffic between Eastern Canada and Western Canada for several days because it is located along a portion of the Trans-Canada Highway where there is no alternate detour route for vehicles to take; [8] and the Norwalk River Railroad Bridge in Norwalk, Connecticut, an aging swing bridge that sometimes gets stuck when opening or closing, disrupting rail traffic on the Northeast Corridor line. [7]

The concept of a single point of failure has also been applied to the fields of intelligence. Edward Snowden talked of the dangers of being what he described as "the single point of failure" – the sole repository of information. [9]

Life-support systems

A component of a life-support system that would constitute a single point of failure would be required to be extremely reliable.

See also

Concepts

Applications

In literature

Related Research Articles

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<span class="mw-page-title-main">Safety engineering</span> Engineering discipline which assures that engineered systems provide acceptable levels of safety

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<span class="mw-page-title-main">Server (computing)</span> Computer to access a central resource or service on a network

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<span class="mw-page-title-main">Embedded system</span> Computer system with a dedicated function

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<span class="mw-page-title-main">Load balancing (computing)</span> Set of techniques to improve the distribution of workloads across multiple computing resources

In computing, load balancing is the process of distributing a set of tasks over a set of resources, with the aim of making their overall processing more efficient. Load balancing can optimize response time and avoid unevenly overloading some compute nodes while other compute nodes are left idle.

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<span class="mw-page-title-main">Failover</span> Automatic switching from failed computer system to standby computers

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<span class="mw-page-title-main">Computer cluster</span> Set of computers configured in a distributed computing system

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A centralized database is a database that is located, stored, and maintained in a single location. This location is most often a central computer or database system, for example a desktop or server CPU, or a mainframe computer. In most cases, a centralized database would be used by an organization or an institution Users access a centralized database through a computer network which is able to give them access to the central CPU, which in turn maintains to the database itself.

Continuous availability is an approach to computer system and application design that protects users against downtime, whatever the cause and ensures that users remain connected to their documents, data files and business applications. Continuous availability describes the information technology methods to ensure business continuity.

High availability software is software used to ensure that systems are running and available most of the time. High availability is a high percentage of time that the system is functioning. It can be formally defined as *100%. Although the minimum required availability varies by task, systems typically attempt to achieve 99.999% (5-nines) availability. This characteristic is weaker than fault tolerance, which typically seeks to provide 100% availability, albeit with significant price and performance penalties.

References

  1. ↑ 1: Designing Large-scale LANs – Page 31, K. Dooley, O'Reilly, 2002
  2. ↑ Ulbrich, Peter, et al. "Eliminating single points of failure in software-based redundancy." 2012 Ninth European Dependable Computing Conference. IEEE, 2012.
  3. ↑ Bezek, Andraz, and Matjaz Gams. "Comparing a traditional and a multi-agent load-balancing system." Computing and Informatics 25.1 (2006): 17-42.
  4. 1 2 Lever, Kirsty E., Madjid Merabti, and Kashif Kifayat. "Single Points of Failure Within Systems-of-Systems." 14th Annual Post Graduate Symposium on the Convergence of Telecommunications, Networking and Broadcasting (PGNet). Vol. 183. 2013.
  5. ↑ Alkhalil, Zainab; Hewage, Chaminda; Nawaf, Liqaa; Khan, Imtiaz (2021-03-09). "Phishing Attacks: A Recent Comprehensive Study and a New Anatomy". Frontiers in Computer Science. 3. doi: 10.3389/fcomp.2021.563060 . ISSN   2624-9898.
  6. ↑ Gary S. Lynch (Oct 7, 2009). Single Point of Failure: The 10 Essential Laws of Supply Chain Risk Management. Wiley. ISBN   978-0-470-42496-4.
  7. 1 2 "Crucial, Century-Old, And Sometimes Stuck: Connecticut Bridge Is Key To Northeast Corridor". Connecticut Public Radio, August 8, 2017.
  8. ↑ "The Nipigon River Bridge and other Trans-Canada bottlenecks". Global News, January 11, 2016.
  9. ↑ "Edward Snowden: the true story behind his NSA leaks" . Telegraph.co.uk. Archived from the original on 2022-01-12. Retrieved 2016-12-13.
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