High availability (HA) is a characteristic of a system that aims to ensure an agreed level of operational performance, usually uptime, for a higher than normal period. There is now more dependence on these systems as a result of modernization. For example, to carry out their regular daily tasks, hospitals and data centers need their systems to be highly available. Availability refers to the ability of the user to access a service or system, whether to submit new work, update or modify existing work, or retrieve the results of previous work. If a user cannot access the system, it is considered unavailable from the user's perspective. The term downtime is generally used to refer to describe periods when a system is unavailable.
Resilience High availability is a property of network resilience, the ability to "provide and maintain an acceptable level of service in the face of faults and challenges to normal operation." Threats and challenges for services can range from simple misconfiguration over large scale natural disasters to targeted attacks. As such, network resilience touches a very wide range of topics. In order to increase the resilience of a given communication network, the probable challenges and risks have to be identified and appropriate resilience metrics have to be defined for the service to be protected. The importance of network resilience is continuously increasing, as communication networks are becoming a fundamental component in the operation of critical infrastructures. Consequently, recent efforts focus on interpreting and improving network and computing resilience with applications to critical infrastructures. As an example, one can consider as a resilience objective the provisioning of services over the network, instead of the services of the network itself. This may require coordinated response from both the network and from the services running on top of the network. These services include:
supporting distributed processing supporting network storage maintaining service of communication services such as video conferencing instant messaging online collaboration access to applications and data as needed Resilience and survivability are interchangeably used according to the specific context of a given study.
Principles
There are three principles of systems design in reliability engineering that can help achieve high availability.
Elimination of single points of failure. This means adding or building redundancy into the system so that failure of a component does not mean failure of the entire system. Reliable crossover. In redundant systems, the crossover point itself tends to become a single point of failure. Reliable systems must provide for reliable crossover. Detection of failures as they occur. If the two principles above are observed, then a user may never see a failure – but the maintenance activity must.
Scheduled and unscheduled downtime
A distinction can be made between scheduled and unscheduled downtime. Typically, scheduled downtime is a result of maintenance that is disruptive to system operation and usually cannot be avoided with a currently installed system design. Scheduled downtime events might include patches to system software that require a reboot or system configuration changes that only take effect upon a reboot. In general, scheduled downtime is usually the result of some logical, management-initiated event. Unscheduled downtime events typically arise from some physical event, such as a hardware or software failure or environmental anomaly. Examples of unscheduled downtime events include power outages, failed CPU or RAM components (or possibly other failed hardware components), an over-temperature related shutdown, logically or physically severed network connections, security breaches, or various application, middleware, and operating system failures. If users can be warned away from scheduled downtimes, then the distinction is useful. But if the requirement is for true high availability, then downtime is downtime whether or not it is scheduled. Many computing sites exclude scheduled downtime from availability calculations, assuming that it has little or no impact upon the computing user community. By doing this, they can claim to have phenomenally high availability, which might give the illusion of continuous availability. Systems that exhibit truly continuous availability are comparatively rare and higher priced, and most have carefully implemented specialty designs that eliminate any single point of failure and allow online hardware, network, operating system, middleware, and application upgrades, patches, and replacements. For certain systems, scheduled downtime does not matter, for example, system downtime at an office building after everybody has gone home for the night.
Percentage calculation Availability is usually expressed as a percentage of uptime in a given year. The following table shows the downtime that will be allowed for a particular percentage of availability, presuming that the system is required to operate continuously. Service level agreements often refer to monthly downtime or availability in order to calculate service credits to match monthly billing cycles. The following table shows the translation from a given availability percentage to the corresponding amount of time a system would be unavailable. Availability is often quoted in terms of "nines", with 90% availability being called "one nine", 99% "two nines", 99.9% "three nines" and so on. As the number of nines gets larger, the availability targets get exponentially more stringent. Reliability levels of more than nine nines are rare, and typically only achieved by distributed networks of redundant systems, and even then largely only in theory since it is effectively impossible to measure such low levels of downtime in any reasonable period; even a single second of system-wide downtime in 30 years (say, through an unanticipated common-mode software error) would be sufficient to dethrone an 11-nines system to nine nines of availability.
… excerpt ends here. Continue reading the full article.
