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The terms high availability, continuous operation, and continuous availability are generally used to express how available a system is. [3] [4] The following is a definition of each of these terms. High availability refers to the ability to avoid unplanned outages by eliminating single points of failure. This is a measure of the reliability of ...
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." [ 3 ] Threats and challenges for services can range from simple misconfiguration over large scale natural disasters to targeted attacks. [ 4 ]
In reliability engineering, the term availability has the following meanings: . The degree to which a system, subsystem or equipment is in a specified operable and committable state at the start of a mission, when the mission is called for at an unknown, i.e. a random, time.
proceed with the operation and thus provide availability but risk inconsistency. Note this doesn't necessarily mean that system is highly available to its users. [5] CAP theorem Euler diagram. Thus, if there is a network partition, one has to choose between consistency or availability.
Quality of service (QoS) is the description or measurement of the overall performance of a service, such as a telephony or computer network, or a cloud computing service, particularly the performance seen by the users of the network.
Reliability, availability and serviceability (RAS), also known as reliability, availability, and maintainability (RAM), is a computer hardware engineering term involving reliability engineering, high availability, and serviceability design. The phrase was originally used by IBM as a term to describe the robustness of their mainframe computers.
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Mean Time To Recover (MTTR) is the length of time required to restore operation to specification. This includes three values. Mean Time To Discover; Mean Time To Isolate; Mean Time To Repair; Mean Time To Discover is the length of time that transpires between when a failure occurs and the system users become aware of the failure.